If we want to build a data-driven business, we need to appreciate the various roles that data and intelligence can play in the business - whether improving a single business service, capability or process, or improving the business as a whole. The examples in this post are mainly from retail, but a similar approach can easily be applied to other sectors.
Sense-Making and Decision Support
The traditional role of analytics and business intelligence is helping the business interpret and respond to what is going on.
Once upon a time, business intelligence always operated with some delay. Data had to be loaded from the operational systems into the data warehouse before they could be processed and analysed. I remember working with systems that generated management information based on yesterday's data, or even last month's data. Of course, such systems don't exist any more (!?), because people expect real-time insight, based on streamed data.
Management information systems are supposed to support individual and collective decision-making. People often talk about actionable intelligence, but of course it doesn't create any value for the business until it is actioned. Creating a fancy report or dashboard isn't the real goal, it's just a means to an end.
Analytics can also be used to calculate complicated chains of effects on a what-if basis. For example, if we change the price of this product by this much, what effect is this predicted to have on the demand for other products, what are the possible responses from our competitors, how does the overall change in customer spending affect supply chain logistics, do we need to rearrange the shelf displays, and so on. How sensitive is Y to changes in X, and what is the optimal level of Z?
Analytics can also be used to support large-scale optimization - for example, solving complicated scheduling problems.
Automated Action
Increasingly, we are looking at the direct actioning of intelligence, possibly in real-time. The intelligence drives automated decisions within operational business processes, often without a human-in-the-loop, where human supervision and control may be remote or retrospective. A good example of this is dynamic retail pricing, where an algorithm adjusts the prices of goods and services according to some model of supply and demand. In some cases, optimized plans and schedules can be implemented without a human in the loop.
So the data doesn't just flow from the operational systems into the data warehouse, but there is a control flow back into the operational systems. We can call this closed loop intelligence.
(If it takes too much time to process the data and generate the action, the action may no longer be appropriate. A few years ago, one of my clients wanted to use transaction data from the data warehouse to generate emails to customers - but with their existing architecture there would have been a 48 hour delay from the transaction to the email, so we needed to find a way to bypass this.)
Managing Complexity
If you have millions of customers buying hundreds of thousands of products, you need ways of aggregating the data in order to manage the business effectively. Customers can be grouped into segments, products can be grouped into categories, and many organizations use these groupings as a basis for dividing responsibilities between individuals and teams. However, these groupings are typically inflexible and sometimes seem perverse.
For example, in a large supermarket, after failing to find maple syrup next to the honey as I expected, I was told I should find it next to the custard. There may well be a logical reason for this grouping, but this logic was not apparent to me as a customer.
But the fact that maple syrup is in the same product category as custard doesn't just affect the shelf layout, it may also mean that it is automatically included in decisions affecting the custard category and excluded from decisions affecting the honey category. For example, pricing and promotion decisions.
A data-driven business is able to group things dynamically, based on affinity or association, and then allows simple and powerful decisions to be made for this dynamic group, at the right level of aggregation.
Automation can then be used to cascade the action to all affected products, making the necessary price, logistical and other adjustments for each product. This means that a broad plan can be quickly and consistently implemented across thousands of products.
Experimentation and Learning
In a data-driven business, every activity is designed for learning as well as doing. Feedback is used in the cybernetic sense - collecting and interpreting data to control and refine business rules and algorithms.
In a dynamic world, it is necessary to experiment constantly. A supermarket or online business is a permanent laboratory for testing the behaviour of its customers. For example, A/B testing where alternatives are presented to different customers on different occasions to test which one gets the best response. As I mentioned in an earlier post, Netflix declares themselves "addicted" to the methodology of A/B testing.
In a simple controlled experiment, you change one variable and leave everything else the same. But in a complex business world, everything is changing. So you need advanced statistics and machine learning, not only to interpret the data, but also to design experiments that will produce useful data.
Managing Organization
A traditional command-and-control organization likes to keep the intelligence and insight in the head office, close to top management. An intelligent organization on the other hand likes to mobilize the intelligence and insight of all its people, and encourage (some) local flexibility (while maintaining global consistency). With advanced data and intelligence tools, power can be driven to the edge of the organization, allowing for different models of delegation and collaboration. For example, retail management may feel able to give greater autonomy to store managers, but only if the systems provide faster feedback and more effective support.
Transparency
Related to the previous point, data and intelligence can provide clarity and governance to the business, and to a range of other stakeholders. This has ethical as well as regulatory implications.
Among other things, transparent data and intelligence reveal their provenance and derivation. (This isn't the same thing as explanation, but it probably helps.)
Obviously most organizations already have many of the pieces of this, but there are typically major challenges with legacy systems and data - especially master data management. Moving onto the cloud, and adopting advanced integration and robotic automation tools may help with some of these challenges, but it is clearly not the whole story.
Some organizations may be lopsided or disconnected in their use of data and intelligence. They may have very sophisticated analytic systems in some areas, while other areas are comparatively neglected. There can be a tendency to over-value the data and insight you've already got, instead of thinking about the data and insight that you ought to have.
Making an organization more data-driven doesn't always entail a large transformation programme, but it does require a clarity of vision and pragmatic joined-up thinking.
Related posts: Rhyme or Reason: The Logic of Netflix (June 2017), Setting off towards the Data-Driven Business (August 2019)
Updated 13 September 2019
Showing posts with label strategy. Show all posts
Showing posts with label strategy. Show all posts
Saturday, August 03, 2019
Saturday, November 07, 2015
The New Economics of Manufacturing
Popped over to Turin this week to give a presentation at a seminar on the Future of Manufacturing.
A lot of the other presentations focused on the technology (3D Printers, Cyber-Physical Systems, Internet of Things), so I wanted to look at the broader economic picture. I drew some inspiration from a recent interview with the French writer Jacques Attali, who predicted the crisis in the music industry.
Attali now says manufacturing will be hit by an identical crisis - this time caused by 3D printing. Apparently some spare parts have already started to appear on pirate websites. Thus instead of paying the manufacturer for a spare part, you might be able to download and print it yourself. Given that many manufacturers sell their products at low margin, in order to make money from spare parts and maintenance, this could seriously disrupt the economics of manufacturing.
By the way, making money from the consumable part of the product is a very old idea - business schools usually attribute the idea to Gillette's strategy of giving away the razors in order to sell the blades, although Randy Picker argues that the history of Gillette's innovation was a bit more complicated than the usual story.
There are two possible responses to this challenge. Firstly a shift from the cost of the fabrication to the cost of the materials. The materials used by 3D printers are very expensive compared with normal material. And secondly, designing the whole product to frustrate the use of generic spare parts.
We can see both of these tactics in the world of 2D printers. Printers for home use are really cheap, but the replacement ink cartridges cost almost as much as the printer. Printer ink is the most expensive liquid most people ever buy - much more expensive than good champagne. Or for that matter, human blood. (Not that I've ever needed to buy any, thank goodness.)
Which brings us to the second tactic. Yes you can refill ink cartridges or use generic replacements. But the printer can be equipped with software to detect and frustrate this, degrading its performance and efficiency when it detects a third party or refilled cartridge. As we discovered in the Volkswagen
Manufacturing is shifting away from products (including spare parts) and towards services. Instead of trying to sell you overpriced tyres, the car manufacturer must make sure that only its accredited partners have the software to balance the wheels properly. In other words, not just architecting the product or even the process, but architecting the whole ecosystem.
And of course, music the harbinger. Famous popstars used to do free concerts in order to sell more albums. Now they might as well give away the albums in order to sell more concert tickets.
But we've been here before. Attali makes the point that when musicians in the 18th Century - like the composer Handel - started selling tickets for concerts, rather than seeking royal patronage, they were breaking new economic ground. They were signalling the end of feudalism and the beginning of a new order of capitalism.
A lot of the other presentations focused on the technology (3D Printers, Cyber-Physical Systems, Internet of Things), so I wanted to look at the broader economic picture. I drew some inspiration from a recent interview with the French writer Jacques Attali, who predicted the crisis in the music industry.
For Attali, music is not simply a reflection of culture, but a harbinger of change, an anticipatory abstraction of the shape of things to come.from a review of Attali's 1985 book Noise
Attali now says manufacturing will be hit by an identical crisis - this time caused by 3D printing. Apparently some spare parts have already started to appear on pirate websites. Thus instead of paying the manufacturer for a spare part, you might be able to download and print it yourself. Given that many manufacturers sell their products at low margin, in order to make money from spare parts and maintenance, this could seriously disrupt the economics of manufacturing.
By the way, making money from the consumable part of the product is a very old idea - business schools usually attribute the idea to Gillette's strategy of giving away the razors in order to sell the blades, although Randy Picker argues that the history of Gillette's innovation was a bit more complicated than the usual story.
There are two possible responses to this challenge. Firstly a shift from the cost of the fabrication to the cost of the materials. The materials used by 3D printers are very expensive compared with normal material. And secondly, designing the whole product to frustrate the use of generic spare parts.
We can see both of these tactics in the world of 2D printers. Printers for home use are really cheap, but the replacement ink cartridges cost almost as much as the printer. Printer ink is the most expensive liquid most people ever buy - much more expensive than good champagne. Or for that matter, human blood. (Not that I've ever needed to buy any, thank goodness.)
Which brings us to the second tactic. Yes you can refill ink cartridges or use generic replacements. But the printer can be equipped with software to detect and frustrate this, degrading its performance and efficiency when it detects a third party or refilled cartridge. As we discovered in the Volkswagen
defeat devicescandal, the embedded software in any product may be designed to serve the commercial interests of the manufacturer rather than the consumer.
Manufacturing is shifting away from products (including spare parts) and towards services. Instead of trying to sell you overpriced tyres, the car manufacturer must make sure that only its accredited partners have the software to balance the wheels properly. In other words, not just architecting the product or even the process, but architecting the whole ecosystem.
And of course, music the harbinger. Famous popstars used to do free concerts in order to sell more albums. Now they might as well give away the albums in order to sell more concert tickets.
But we've been here before. Attali makes the point that when musicians in the 18th Century - like the composer Handel - started selling tickets for concerts, rather than seeking royal patronage, they were breaking new economic ground. They were signalling the end of feudalism and the beginning of a new order of capitalism.
Related Posts
Tethering (August 2004)
Defeating the Device Paradigm (October 2015)
Weaving in Three Dimensions (November 2015)
Right to Repair (March 2017)
Other Sources
T.W. Adorno, A Social Critique of Radio Music (Kenyon Review, Spring 1945. Reprinted in Kenyon Review New Series, Vol 18 3/4, Summer/Autumn 1996) pp 229-235
Azeem Azhar, Trade, globalisation and 3-d printers (Exponential View, 4 October 2019)
Alex Hudson, Is digital piracy possible on any object? (BBC Click, 9 December 2013)
Randy Picker, Gillette’s Strange History with the Razor and Blade Strategy (HBR Sept 2010)
Sam York, The pop star and the prophet (BBC News Magazine, 17 September 2015)
Monday, April 08, 2013
Multi-Sided Platform Strategies
A multi-sided platform business has the following characteristic features.
1. The platform serves two or more distinct categories of customer. For example, a credit card platform serves both cardholders and merchants. For example, a heterosexual dating agency serves both men and women.
2. The platform provides a mechanism for connecting customers from different categories. The credit card increases the potential interaction between cardholders and merchants, as well as processing the transactions. And the dating agency brings men and women together.
3. The value of the platform to one category of customers depends on the quantity and quality of the other categories. For example, the value of a credit card to the cardholder depends on the number of merchants that accept the card. Meanwhile, the value of the card to the merchant depends on the number of cardholders.
Under certain circumstances, it might be possible to build one side of the platform first. For example, if you had some brilliant idea for a entirely new kind of credit card, and had a lot of funding and a persuasive sales team, you might conceivably be able to recruit a large number of merchants into the scheme before you had any cardholders at all. Or imagine persuading a group of men to invest all their spare time for two years building a nightclub that would (when finished) attract the hottest women in the city. But this strategy requires a considerable degree of confidence and trust. So in practice it usually makes sense to build up both sides at the same time.
There are various strategies that can be used to create a multi-sided platform. Sometimes it is possible to start small. When Frank McNamara created Diners Club in 1950, he started in a small geographical area (Manhatten), with 14 merchants and a few hundred cardholders. Within a year, he had 300 merchants and 40,000 cardholders.
When American Express wished to enter the market in 1958, it needed to create something quickly that could compete with Diners Club. One way to do this was to acquire and consolidate some existing schemes. But the key element to the American Express's success was a marquee strategy - recruiting the most desirable customers (e.g. business travellers on expense accounts) and the most desirable merchants (e.g. high status hotels, restaurants and stores).
A marquee strategy depends on a degree of exclusivity, real or imagined. In a multi-sided market, you don't gain directly from the number of people on your own side, since they may be competing with you for the attention of the people on the other side.
American Express is now much larger than Diners Club. So much for first-mover advantage then. The most desirable customers are not necessarily the ones with the greatest willingness to experiment with a novel platform. Novel platforms tend to attract early adopters and low-value customers (AltaVista, MySpace, OnSale). Once the platform concept is understood, a new entrant may be more successful in recruiting the high-value and mainstream customers (Google, Facebook, eBay).
Among users of Facebook and Twitter, a gulf is emerging between celebrities and other users. Facebook is currently experimenting with charging a fee for ordinary users to send messages to celebrities. According to the Independent, Facebook plans to keep this money itself. Presumably the only benefit to the celebrity is helping to filter incoming messages. And of course many celebrities are now dependent on Facebook and Twitter for maintaining their public profile, so they are not able to walk away.
The growing distinction between different categories of user marks a transition from same-side network effects (which assume a single category of user) into a multi-sided platform. Linked-In is another platform that is making this transition. Linked-In gets much of its revenue from the recruitment business, so it is essentially a market-making platform. Whereas Facebook and Twitter remain largely audience-making platforms.
(For the distinction between market-making and audience-making platforms, as well as a third category of demand-coordination platforms, see David S Evans.)
I spoke at the IASA UK Architecture Summit on 26th April on Architecting the Multi-Sided Business. Please contact me if you have any practical challenges in this area.
Pieter Ballon, Platform Types and Gatekeeper Roles: the Case of the Mobile Communications Industry (2009)
Mark Bonchek and Sangeet Paul Choudary, Three Elements of a Successful Platform Strategy (HBR Blog Network Jan 2013)
David S. Evans, Managing the Maze of Multisided Markets (Strategy+Business Fall 2003)
David S. Evans, The Antitrust Economics of Multi-Sided Platform Markets (Yale Journal on Regulation, 2003)
David S. Evans and Richard Schmalensee, Failure to Launch: Critical Mass in Platform Businesses (Sept 2010)
Thomas Eisenmann, Geoffrey Parker, and Marshall W. Van Alstyne, Strategies for Two-Sided Markets (HBR October 2006)
James Legge, Facebook now charges you for messages sent to celebrities and people you aren't friends with (Independent 7 April 2013)
Lisa O'Carroll, Facebook starts charging users up to £11 to contact celebrities (Guardian 8 April 2013)
Geoffrey Parker and Marshall Van Alstyne, A Digital Postal Platform: Definitions and a Roadmap (MIT Jan 2012)
Richard Veryard, The Component-Based Business: Plug and Play (Springer 2001)
Understanding LinkedIn Business Model (BMI Matters May 2012)
Related Posts: On the Nature of Platforms (July 2017)
Links added 7 September 2017
1. The platform serves two or more distinct categories of customer. For example, a credit card platform serves both cardholders and merchants. For example, a heterosexual dating agency serves both men and women.
2. The platform provides a mechanism for connecting customers from different categories. The credit card increases the potential interaction between cardholders and merchants, as well as processing the transactions. And the dating agency brings men and women together.
3. The value of the platform to one category of customers depends on the quantity and quality of the other categories. For example, the value of a credit card to the cardholder depends on the number of merchants that accept the card. Meanwhile, the value of the card to the merchant depends on the number of cardholders.
Under certain circumstances, it might be possible to build one side of the platform first. For example, if you had some brilliant idea for a entirely new kind of credit card, and had a lot of funding and a persuasive sales team, you might conceivably be able to recruit a large number of merchants into the scheme before you had any cardholders at all. Or imagine persuading a group of men to invest all their spare time for two years building a nightclub that would (when finished) attract the hottest women in the city. But this strategy requires a considerable degree of confidence and trust. So in practice it usually makes sense to build up both sides at the same time.
There are various strategies that can be used to create a multi-sided platform. Sometimes it is possible to start small. When Frank McNamara created Diners Club in 1950, he started in a small geographical area (Manhatten), with 14 merchants and a few hundred cardholders. Within a year, he had 300 merchants and 40,000 cardholders.
When American Express wished to enter the market in 1958, it needed to create something quickly that could compete with Diners Club. One way to do this was to acquire and consolidate some existing schemes. But the key element to the American Express's success was a marquee strategy - recruiting the most desirable customers (e.g. business travellers on expense accounts) and the most desirable merchants (e.g. high status hotels, restaurants and stores).
A marquee strategy depends on a degree of exclusivity, real or imagined. In a multi-sided market, you don't gain directly from the number of people on your own side, since they may be competing with you for the attention of the people on the other side.
American Express is now much larger than Diners Club. So much for first-mover advantage then. The most desirable customers are not necessarily the ones with the greatest willingness to experiment with a novel platform. Novel platforms tend to attract early adopters and low-value customers (AltaVista, MySpace, OnSale). Once the platform concept is understood, a new entrant may be more successful in recruiting the high-value and mainstream customers (Google, Facebook, eBay).
Among users of Facebook and Twitter, a gulf is emerging between celebrities and other users. Facebook is currently experimenting with charging a fee for ordinary users to send messages to celebrities. According to the Independent, Facebook plans to keep this money itself. Presumably the only benefit to the celebrity is helping to filter incoming messages. And of course many celebrities are now dependent on Facebook and Twitter for maintaining their public profile, so they are not able to walk away.
The growing distinction between different categories of user marks a transition from same-side network effects (which assume a single category of user) into a multi-sided platform. Linked-In is another platform that is making this transition. Linked-In gets much of its revenue from the recruitment business, so it is essentially a market-making platform. Whereas Facebook and Twitter remain largely audience-making platforms.
(For the distinction between market-making and audience-making platforms, as well as a third category of demand-coordination platforms, see David S Evans.)
I spoke at the IASA UK Architecture Summit on 26th April on Architecting the Multi-Sided Business. Please contact me if you have any practical challenges in this area.
Pieter Ballon, Platform Types and Gatekeeper Roles: the Case of the Mobile Communications Industry (2009)
Mark Bonchek and Sangeet Paul Choudary, Three Elements of a Successful Platform Strategy (HBR Blog Network Jan 2013)
David S. Evans, Managing the Maze of Multisided Markets (Strategy+Business Fall 2003)
David S. Evans, The Antitrust Economics of Multi-Sided Platform Markets (Yale Journal on Regulation, 2003)
David S. Evans and Richard Schmalensee, Failure to Launch: Critical Mass in Platform Businesses (Sept 2010)
Thomas Eisenmann, Geoffrey Parker, and Marshall W. Van Alstyne, Strategies for Two-Sided Markets (HBR October 2006)
James Legge, Facebook now charges you for messages sent to celebrities and people you aren't friends with (Independent 7 April 2013)
Lisa O'Carroll, Facebook starts charging users up to £11 to contact celebrities (Guardian 8 April 2013)
Geoffrey Parker and Marshall Van Alstyne, A Digital Postal Platform: Definitions and a Roadmap (MIT Jan 2012)
Richard Veryard, The Component-Based Business: Plug and Play (Springer 2001)
Understanding LinkedIn Business Model (BMI Matters May 2012)
Related Posts: On the Nature of Platforms (July 2017)
Links added 7 September 2017
Sunday, December 09, 2012
Co-Production of Strategy and Execution
#antifragile In my post
Structure Follows Strategy?, I discussed the reciprocal relationship between strategy and structure, and discussed my friend Patrick Hoverstadt's mission to connect enterprise architects with the strategy processes in an enterprise.
My thoughts about strategy are influenced by Mintzberg, who sees strategy formulation as an emergent process of trial and error that takes place during implementation. A company may start with a broad-brush deliberate strategy, but this strategy often overlooks some significant issues and risks.
These weaknesses need to be addressed as part of the execution of the strategy. Thus a more complete and correct strategy emerges out of the execution process.
Senior management sometimes take a long time to recognize and acknowledge the fact that the defacto (emergent) strategy is now better than the original (deliberate) strategy. And in some companies the original strategy is so bad, and the senior management so pig-headed, that there is little chance of a more sensible strategy emerging.
In order to see strategy and execution as co-evolving, we need to link both strategy and execution to outcomes. If the outcomes turn out unsatisfactory, it is surely a subjective judgement whether this is blamed on weak strategy or weak execution. And if the overall outcomes turn out to be satisfactory then we may suppose that any weakness in strategy was compensated by excellent execution, and any weakness in execution was compensated by brilliant strategy.
This of course depends on our notion of excellence. Some people might think that perfect execution means doing exactly what it says in the strategy, no more or less. Alternatively, we might define excellence in terms of achieving the best possible outcomes, thus excellent execution may need to depart from the official strategy if that's what it takes.
Which brings me to Nassim Nicholas Taleb's notion of antifragility. If fragility means that something is harmed when bad things happen, antifragility means that something becomes better or stronger when bad things happen.
So let me try to apply this notion to the current discussion. A fragile strategy is one that would fail if there are any deviations in execution. A robust strategy is one that would be unaffected by the quality of the execution. And an antifragile strategy is one that would grow better with deviations in execution.
Partly based on my contributions to a Linked-In discussion I wonder what the EA team is doing? (One person has deleted his contributions, so the discussion as a whole no longer makes much sense.) See also Fragile Strategy or Fragile Execution? via Storify.
My thoughts about strategy are influenced by Mintzberg, who sees strategy formulation as an emergent process of trial and error that takes place during implementation. A company may start with a broad-brush deliberate strategy, but this strategy often overlooks some significant issues and risks.
These weaknesses need to be addressed as part of the execution of the strategy. Thus a more complete and correct strategy emerges out of the execution process.
Senior management sometimes take a long time to recognize and acknowledge the fact that the defacto (emergent) strategy is now better than the original (deliberate) strategy. And in some companies the original strategy is so bad, and the senior management so pig-headed, that there is little chance of a more sensible strategy emerging.
In order to see strategy and execution as co-evolving, we need to link both strategy and execution to outcomes. If the outcomes turn out unsatisfactory, it is surely a subjective judgement whether this is blamed on weak strategy or weak execution. And if the overall outcomes turn out to be satisfactory then we may suppose that any weakness in strategy was compensated by excellent execution, and any weakness in execution was compensated by brilliant strategy.
This of course depends on our notion of excellence. Some people might think that perfect execution means doing exactly what it says in the strategy, no more or less. Alternatively, we might define excellence in terms of achieving the best possible outcomes, thus excellent execution may need to depart from the official strategy if that's what it takes.
Which brings me to Nassim Nicholas Taleb's notion of antifragility. If fragility means that something is harmed when bad things happen, antifragility means that something becomes better or stronger when bad things happen.
So let me try to apply this notion to the current discussion. A fragile strategy is one that would fail if there are any deviations in execution. A robust strategy is one that would be unaffected by the quality of the execution. And an antifragile strategy is one that would grow better with deviations in execution.
Partly based on my contributions to a Linked-In discussion I wonder what the EA team is doing? (One person has deleted his contributions, so the discussion as a whole no longer makes much sense.) See also Fragile Strategy or Fragile Execution? via Storify.
Carole Cadwalladr, Nassim Taleb: my rules for life (The Observer, 24 Nov 2012)
John Crace, Antifragile by Nassim Nicholas Taleb – digested read (The Guardian, 2 Dec 2012)
David Runciman, Antifragile: How to Live in a World We Don't Understand by Nassim Nicholas Taleb – review (The Guardian, 21 Nov 2012)
Wednesday, October 31, 2012
Architecture and the Imagination
"Thinking about the future is a form of unreality." Leif Frenzel, Lost time, sedimentation, and the future as a form of unreality (March 2011)
An architect looks at a valley and imagines a viaduct. She then describes this imaginary viaduct in great detail. As a result of her imagination, and the efforts of many engineers and other workers, when we visit the valley ten years later we too can see the viaduct, now fully realized in graffiti-daubed concrete.
Similarly, much of the work of enterprise and solution architects refers to things that don't exist yet. Most obviously, this applies to systems that haven't been built yet. But it can also apply to business concepts that haven't been "realized" yet.
For example, before Apple launched the iPhone, it must already have had a reasonably well-elaborated concept of IPHONE-USER, and it would had ensured that this concept was adequately supported by a combination of existing and new systems. (Of course, the concept of IPHONE-USER may well be a specialization of the concept of CUSTOMER, but there is a lot of new conceptual matter to accommodate.)
The concept of IPHONE-USER is essentially an exercise in imagination. However this imagination can be grounded by various practical experiments - for example, test engineers creating artificial or proxy instances of IPHONE-USER to make sure everything works properly.
Some 1980s methodologies, including Information Engineering, preached that a conceptual or business information model was in some sense timeless, and that Information Strategy could essentially be reduced to Information Systems Strategy. (This agenda was of course promoted by companies who wanted to sell information systems.)
I now think it is perfectly reasonable for the conceptual model of the enterprise to evolve over time, as the business starts to conceive of previously unconceivable things. Here are some well-worn examples.
So as I see it, Information Strategy includes imagining new things for the business to pay attention to. This is a lot broader and more interesting than Information Systems Strategy, and is just one of the areas where the architect needs to use some imagination.
See also
Updated 30 March 2013
An architect looks at a valley and imagines a viaduct. She then describes this imaginary viaduct in great detail. As a result of her imagination, and the efforts of many engineers and other workers, when we visit the valley ten years later we too can see the viaduct, now fully realized in graffiti-daubed concrete.
Similarly, much of the work of enterprise and solution architects refers to things that don't exist yet. Most obviously, this applies to systems that haven't been built yet. But it can also apply to business concepts that haven't been "realized" yet.
For example, before Apple launched the iPhone, it must already have had a reasonably well-elaborated concept of IPHONE-USER, and it would had ensured that this concept was adequately supported by a combination of existing and new systems. (Of course, the concept of IPHONE-USER may well be a specialization of the concept of CUSTOMER, but there is a lot of new conceptual matter to accommodate.)
The concept of IPHONE-USER is essentially an exercise in imagination. However this imagination can be grounded by various practical experiments - for example, test engineers creating artificial or proxy instances of IPHONE-USER to make sure everything works properly.
Some 1980s methodologies, including Information Engineering, preached that a conceptual or business information model was in some sense timeless, and that Information Strategy could essentially be reduced to Information Systems Strategy. (This agenda was of course promoted by companies who wanted to sell information systems.)
I now think it is perfectly reasonable for the conceptual model of the enterprise to evolve over time, as the business starts to conceive of previously unconceivable things. Here are some well-worn examples.
- The introduction of loyalty cards into retail, allowing retailers to recognize their customers as "the same again", and therefore replacing the concept of a customer-per-visit with the concept of a customer with continuity over time.
- The ability to track activity at ever-finer levels of granularity. For example, monitoring every click on your website, or watching your customers navigating the store. (Did she pick up the lemons from the display next to the fish or from the display next to the gin?)
- Exposing a wealth of associations between products and customers. For example, Amazon's development of the "people-who-bought-this-also-bought-that" pattern.
So as I see it, Information Strategy includes imagining new things for the business to pay attention to. This is a lot broader and more interesting than Information Systems Strategy, and is just one of the areas where the architect needs to use some imagination.
See also
- Architecture and Reality (Nov 2012)
- EA Archetypes (June 2009)
- The Value of Models (April 2005)
- The Value of Models 2 (Sept 2010)
Updated 30 March 2013
Thursday, May 10, 2012
Does everyone (except Google) have a platform strategy?
#bizarch The obvious ones - Apple, Amazon, Microsoft
General comments
Disney
eBay
Elsevier
Nike
Nokia
Walmart
and finally Google
General comments
"The new market disruption is the migration of a large number of demanding customers away from phones-as-voice-products to phones-as-computing-products. The low-end disruption is the migration of a large number of less demanding customers from branded phones to unbranded, commodity phones. ... The new market disruption is evidenced by the shift of fortunes to Apple and Samsung and away from every other device maker." Horace Dediu, The phone market in 2012: a tale of two disruptions (May 2012)
"Apple is the most valuable company in technology (and indeed in the world) because it integrates hardware, software and services. It’s the first, and only, company to do all these three well in service of jobs that the vast majority of consumers want done." Horace Dediu, Which is best: hardware, software or services? (May 2012)
Disney
- John Hagel, Disney, Pixar and Jobs (February 2006)
- Disney, Pixar, Apple and Jobs (February 2006)
eBay
- Dare Obasanjo, eBay Web Services: A Marketplace Platform for Fun and Profit (March 2006)
- Haydn Shaughnessy, eBay's Platform Strategy (Oct 2011)
Elsevier
- Smart Content (Oct 2011)
Nike
- Nick Vitalari, Competition and the Elastic Enterprise: Business Platforms, Personal Biometrics and Strategic Options: Nike and FuelBand (Jan 2012)
- Art Petty, Systems Thinking Meets Platform Strategy and Social Media via Nike+ (March 2012)
Nokia
- Ron Adner, A Sad Lesson in Collaborative Innovation (HBR May 2012)
- The partnership between Nokia and Microsoft "is a clear admission that Nokia's own-platform strategy has faltered," said Ben Wood, an analyst with research firm CCS: Insight. (BBC News, Feb 2011)
Walmart
- Nick Vitalari, Walmart and The Power of the Business Platform (Sept 2011)
and finally Google
- Steve Yegge, “Stevey’s Google Platforms Rant” (Oct 2011)
- Christopher Meyer, Steve Yegge's Google Platform Rant (Oct 2011)
- "Page and his management team have mandated that all Googlers focus on seven business areas, and that they don’t look to expand Google’s reach beyond these core initiatives." Farhad Manjoo, Google's Grand Plan (Slate, March 2012)
- "Page's emphasis on streamlining Google's product line has made the company's thousands of employees focused on how -- and if -- a tool adequately fulfills users' needs." Bianca Bosker, Google's Future (Huffington Post, March 2012)
- Eric Jackson, Google's Paranoid Structure has made it less innovative, not more (Forbes, April 2012)
Saturday, March 10, 2012
Structure Follows Strategy?
#entarch In his talk to the BCS Enterprise Architecture Group this week, Patrick Hoverstadt suggested that traditional enterprise architecture obeyed Alfred Chandler's principle: Structure Follows Strategy. In other words, first the leadership defines a strategy, and then enterprise architecture helps to create a structure (of sociotechnical systems) to support the strategy.
Chandler's principle was published in 1962, and is generally regarded nowadays as much too simplistic. In 1980, Hall and Saias published a paper asserting the converse principle Strategy Follows Structure! (pdf), and most modern writers now follow Henry Mintzberg in regarding the relationship between strategy and structure as reciprocal.
What are the implications of this for enterprise architecture? Patrick offered us a simple syllogism: if enterprise architects determine structure, and if structure determines strategy, then enterprise architects are (consciously or unconsciously) determining strategy. In particular, the strategies that are available to the enterprise are limited by the information systems that the enterprise uses (a) to understand what is going on both internally and externally, and (b) to anticipate future developments. In many situations, the information isn't readily accessible in the form that managers would need to mobilize a strategic response to the complexity of the demand ecosystem.
Of course it isn't as simple as this. The defacto structure (including its information systems) is hardly ever as directed by enterprise architecture, but is created by countless acts of improvisation by managers and workers just trying to get things done. (The late Claudio Ciborra wrote brilliantly about this.) People somehow get most of the information they need, not thanks to the formal information systems but despite them. Thus the emergent structures are a lot more powerful and rich than the official structures that enterprise architects and others are mandated to produce. Patrick cites the example of a wallpaper factory where productivity was markedly reduced after smoking was banned; a plausible explanation for this was that smoking had provided a pretext for informal communication between groups.
Meanwhile, Minztberg drew our attention to a potential gulf between the official strategy and the defacto emergent strategy. (I have always especially liked his example of the Canadian Film Board, published in HBR July-Aug 1987.)
Nevertheless, Patrick's mission (which I endorse) is to connect enterprise architects with the strategy processes in an enterprise. He is a strong advocate of Stafford Beer's Viable Systems Model (VSM). Using his approach, which he encourages enterprise architects to adopt, VSM provides a unique lens for viewing the structure of enterprise, and for recognizing some common structural errors, which he calls pathological; I encourage enterprise architects to read his book on The Fractal Organization.
Related post: Co-Production of Strategy and Execution (December 2012)
Chandler's principle was published in 1962, and is generally regarded nowadays as much too simplistic. In 1980, Hall and Saias published a paper asserting the converse principle Strategy Follows Structure! (pdf), and most modern writers now follow Henry Mintzberg in regarding the relationship between strategy and structure as reciprocal.
What are the implications of this for enterprise architecture? Patrick offered us a simple syllogism: if enterprise architects determine structure, and if structure determines strategy, then enterprise architects are (consciously or unconsciously) determining strategy. In particular, the strategies that are available to the enterprise are limited by the information systems that the enterprise uses (a) to understand what is going on both internally and externally, and (b) to anticipate future developments. In many situations, the information isn't readily accessible in the form that managers would need to mobilize a strategic response to the complexity of the demand ecosystem.
Of course it isn't as simple as this. The defacto structure (including its information systems) is hardly ever as directed by enterprise architecture, but is created by countless acts of improvisation by managers and workers just trying to get things done. (The late Claudio Ciborra wrote brilliantly about this.) People somehow get most of the information they need, not thanks to the formal information systems but despite them. Thus the emergent structures are a lot more powerful and rich than the official structures that enterprise architects and others are mandated to produce. Patrick cites the example of a wallpaper factory where productivity was markedly reduced after smoking was banned; a plausible explanation for this was that smoking had provided a pretext for informal communication between groups.
Meanwhile, Minztberg drew our attention to a potential gulf between the official strategy and the defacto emergent strategy. (I have always especially liked his example of the Canadian Film Board, published in HBR July-Aug 1987.)
Nevertheless, Patrick's mission (which I endorse) is to connect enterprise architects with the strategy processes in an enterprise. He is a strong advocate of Stafford Beer's Viable Systems Model (VSM). Using his approach, which he encourages enterprise architects to adopt, VSM provides a unique lens for viewing the structure of enterprise, and for recognizing some common structural errors, which he calls pathological; I encourage enterprise architects to read his book on The Fractal Organization.
Related post: Co-Production of Strategy and Execution (December 2012)
Friday, December 23, 2011
Three or Four Schools of Enterprise Architecture
#entarch @lapalj has written an interesting article on the Three Schools of Enterprise Architecture.
The schools are distinguished along two dimensions: scope and ends (purpose).
Besides scope and purpose, I have always considered it important to identify a third dimension of perspective (viewpoint). (For example, I talk about these three dimensions in my 1992 book on Information Modelling, pages 16-22.)
Among other things, perspective helps us to address the question: What kind of system is the enterprise being understood as? For example, the (micro-)economic perspective views the enterprise as a production system (value chain or value network), while the management cybernetic perspective (such as Stafford Beer's Viable Systems Model) views the enterprise as a thinking system or brain. Gareth Morgan's book Images of Organization contains a good survey of several contrasting perspectives.
Most enterprise architects in the first school adopt the traditional IT perspective of regarding the enterprise as an information processing system. Most of the well-known EA frameworks (such as those listed on the ISO 42010 website) are solidly within the first school.
Lapalme's second school explicitly invokes the socio-cultural perspective, and calls for all facets of the enterprise to be considered - this clearly implies going beyond the traditional IT perspective.
However, there is a considerable body of work that looks at the enterprise-in-environment, but remains within the IT perspective. This would include the Open Group work on the extended enterprise, as well as the Systems-of-Systems community. A key scoping question here is the exercise of governance over large distributed systems of systems. Mark Maier distinguished between directed and emergent systems (or we might think about directed and emergent enterprises), and this has been developed into a four-part schema by the US Department of Defense: Directed, Acknowledged, Collaborative and Virtual. Some useful work at the SEI, where this thinking has been connected into work on SOA and enterprise architecture.
Lapalme's article identifies James Martin as one of the leaders of the third school, based on a minor work published in 1995, but most of Martin's work belongs solidly within the first school. In his 1982 book, Strategic Data-Planning Methodologies, Martin shows how IBM's BSP methodology could be used to decompose the activities of the organization, as a precursor to planning IT systems. The primary aim of such methodologies from the 1980s onwards was to identify opportunities to install more computers and develop more software, and I think it is no coincidence that a number of the pioneers of enterprise architecture (from Martin to John Zachman) had worked for IBM. See my note on The Sage Kings of Antiquity.
So I think it makes sense to divide Lapalme's third school into two distinct sub-schools. There is clearly a lot of work in School Three A, which extends the scope of architecture without introducing the socio-cultural or other perspectives which Lapalme associates with School Two. There is as yet very little formal work in School Three B.
James Lapalme, "3 Schools of Enterprise Architecture," IT Professional, 14 Dec. 2011. IEEE computer Society Digital Library. IEEE Computer Society, http://doi.ieeecomputersociety.org/10.1109/MITP.2011.109
The schools are distinguished along two dimensions: scope and ends (purpose).
Scopes | Ends |
Enterprise wide IT platform (EIT). All components (software, hardware, etc.) of the enterprise IT assets. | Effective enterprise strategy execution and operation through IT-Business alignment. The end is to enhance business strategy execution and operations. The primary means to this end is the aligning of the business and IT strategies so that the proper IT capabilities are developed to support current and future business needs. |
Enterprise (E). The enterprise as a socio-cultural—techno-economic system; hence ALL the facets of the enterprise are considered – the enterprise IT assets being one facet. | Effective enterprise strategy implementation through execution coherency. The end is effective enterprise strategy implement. The primary means to this end is designing the various facets of the enterprise (governance structures, IT capabilities, remuneration policies, work design, etc.) to maximize coherency between them and minimize contradictions. |
Enterprise-in-environment (EiE). Includes the previous scope but adds the environment of the enterprise as a key component as well as the bidirectional relationship and transactions between the latter and its environment. | Innovation and adaption through organizational learning. The end is organizational innovation and adaption. The primary means is the fostering of organizational learning by designing the various facets of the enterprise (governance structures, IT capabilities, remuneration policies, work design, etc.) as to maximize organizational learning throughout the enterprise. |
Besides scope and purpose, I have always considered it important to identify a third dimension of perspective (viewpoint). (For example, I talk about these three dimensions in my 1992 book on Information Modelling, pages 16-22.)
Among other things, perspective helps us to address the question: What kind of system is the enterprise being understood as? For example, the (micro-)economic perspective views the enterprise as a production system (value chain or value network), while the management cybernetic perspective (such as Stafford Beer's Viable Systems Model) views the enterprise as a thinking system or brain. Gareth Morgan's book Images of Organization contains a good survey of several contrasting perspectives.
Most enterprise architects in the first school adopt the traditional IT perspective of regarding the enterprise as an information processing system. Most of the well-known EA frameworks (such as those listed on the ISO 42010 website) are solidly within the first school.
Lapalme's second school explicitly invokes the socio-cultural perspective, and calls for all facets of the enterprise to be considered - this clearly implies going beyond the traditional IT perspective.
However, there is a considerable body of work that looks at the enterprise-in-environment, but remains within the IT perspective. This would include the Open Group work on the extended enterprise, as well as the Systems-of-Systems community. A key scoping question here is the exercise of governance over large distributed systems of systems. Mark Maier distinguished between directed and emergent systems (or we might think about directed and emergent enterprises), and this has been developed into a four-part schema by the US Department of Defense: Directed, Acknowledged, Collaborative and Virtual. Some useful work at the SEI, where this thinking has been connected into work on SOA and enterprise architecture.
Lapalme's article identifies James Martin as one of the leaders of the third school, based on a minor work published in 1995, but most of Martin's work belongs solidly within the first school. In his 1982 book, Strategic Data-Planning Methodologies, Martin shows how IBM's BSP methodology could be used to decompose the activities of the organization, as a precursor to planning IT systems. The primary aim of such methodologies from the 1980s onwards was to identify opportunities to install more computers and develop more software, and I think it is no coincidence that a number of the pioneers of enterprise architecture (from Martin to John Zachman) had worked for IBM. See my note on The Sage Kings of Antiquity.
So I think it makes sense to divide Lapalme's third school into two distinct sub-schools. There is clearly a lot of work in School Three A, which extends the scope of architecture without introducing the socio-cultural or other perspectives which Lapalme associates with School Two. There is as yet very little formal work in School Three B.
School OneSingle EnterpriseIT Perspective | School TwoSingle EnterpriseMultiple Perspective |
School Three AExtended EnterpriseSystem of Systems | School Three BEcosystemMultiple Perspective |
James Lapalme, "3 Schools of Enterprise Architecture," IT Professional, 14 Dec. 2011. IEEE computer Society Digital Library. IEEE Computer Society, http://doi.ieeecomputersociety.org/10.1109/MITP.2011.109
Sunday, October 16, 2011
Intelligence Failure at Kodak
@mkplantes sees the demise of Kodak as an intelligence failure.
This is effectively an OODA loop. Dr Plantes identifies a number of possible errors in this loop.
1. Incorrect estimate of the pace of change. "Successful companies often underestimate the speed of industry evolution."
2. Incorrect understanding of the value proposition from the customers' perspective. "People don’t buy film, they use film to capture the pictures they want."
3. Incorrect optimization of the basis of competition - commodity wars.
If it was a strategic error for Kodak to get caught up in a dogfight with Fuji, we should also ask how Fuji is faring? Has Fuji committed the same errors as Kodak, and is it suffering the same fate? Meanwhile, Stuart Henshall compares Kodak with HP: two inventive companies, who "failed time and time again to find a more agile footing". (HP - What's Your strategy? August 2011).
Dr Plantes complains that Kodak was focused on the product rather than the value received by its customers - in other words, a platform strategy. But Kodak has been trying to shift its business model from product to a service-oriented platform for at least five years. In November 2006, an article in BusinessWeek described this transformation, and outlined some of the big challenges then facing Kodak (Mistakes made on the road to innovation, BusinessWeek November 2006). In February 2007, Clayton Christensen and Scott D. Anthony saw the Kodak strategy as an ambitious attempt to implement Christensen's concept of disruptive innovation (Will Kodak's New Strategy Work? Forbes February 2007).
Antonio Perez (who spent much of his career at HP) has been the CEO throughout this period, and has watched the Kodak share price drop from around $25 to less than $1. We may infer that Kodak has failed to overcome the challenges identified by BusinessWeek and Christensen. But why?
What's missing from Dr Plantes' analysis is an appreciation of how these four steps operated as an effective OODA loop, with feedback and learning, rather than merely repetition. In a detailed analysis of Kodak strategy, George Mendes concludes
There is a great deal on the Internet about Kodak's social media strategy - but it seems to be largely about Kodak marketing communications. Journalist Courtney Boyd Myers (@CBM) invites us to Meet the brilliant and beautiful woman behind Kodak’s social media strategy (September 2011). The woman in question is extremely photogenic and obviously good at self-promotion, but there is nothing strategic in the article. The big strategic error here is to regard social media and content management as a marketing issue, separate from the business model itself. This seems to suggest a lack of joined-up thinking - and ultimately a failure of organizational intelligence.
In 2007, Jacob McNulty thought that that instilling the elements of a learning organization would have strongly contributed to a different story for Kodak’s recent years.
Other sources claim that Kodak is a learning organization. In which case, why has it failed to learn the things that matter?
book now Business Architecture Bootcamp (November 22-23, 2011)
book now Workshop: Organizational Intelligence (November 24th, 2011)
Put yourself in their Kodak leaders’ chairs for a moment and consider the four expectations of a leadership team and, more importantly, consider the speed with which they had to work though all of the expectations:
• Sense what’s going on around you? (“Digital is coming!”)
• Make sense of what you see, hear, and feel (“Film is dying, but we can’t kill it now. It’s too important!”)
• Decide on a course of action (“OMG! Nothing is as big as film is now. Let’s think about this and be careful.”)
• Act on your decisions (“Well, this is a big ship! Hard to change course overnight!”)
Kay Plantes, A sad “Kodak moment” business model failure WTN News 7 October 2011
This is effectively an OODA loop. Dr Plantes identifies a number of possible errors in this loop.
1. Incorrect estimate of the pace of change. "Successful companies often underestimate the speed of industry evolution."
2. Incorrect understanding of the value proposition from the customers' perspective. "People don’t buy film, they use film to capture the pictures they want."
3. Incorrect optimization of the basis of competition - commodity wars.
If it was a strategic error for Kodak to get caught up in a dogfight with Fuji, we should also ask how Fuji is faring? Has Fuji committed the same errors as Kodak, and is it suffering the same fate? Meanwhile, Stuart Henshall compares Kodak with HP: two inventive companies, who "failed time and time again to find a more agile footing". (HP - What's Your strategy? August 2011).
Dr Plantes complains that Kodak was focused on the product rather than the value received by its customers - in other words, a platform strategy. But Kodak has been trying to shift its business model from product to a service-oriented platform for at least five years. In November 2006, an article in BusinessWeek described this transformation, and outlined some of the big challenges then facing Kodak (Mistakes made on the road to innovation, BusinessWeek November 2006). In February 2007, Clayton Christensen and Scott D. Anthony saw the Kodak strategy as an ambitious attempt to implement Christensen's concept of disruptive innovation (Will Kodak's New Strategy Work? Forbes February 2007).
Antonio Perez (who spent much of his career at HP) has been the CEO throughout this period, and has watched the Kodak share price drop from around $25 to less than $1. We may infer that Kodak has failed to overcome the challenges identified by BusinessWeek and Christensen. But why?
What's missing from Dr Plantes' analysis is an appreciation of how these four steps operated as an effective OODA loop, with feedback and learning, rather than merely repetition. In a detailed analysis of Kodak strategy, George Mendes concludes
Kodak is an example of repeat strategic failure – it was unable to grasp the future of digital quickly enough, and even when it did so, it was implemented too slowly under a continuous change strategy and ultimately it did not fit coherently as a core competency.
George Mendes, What went wrong at Eastman Kodak (pdf), TheStrategyTank
There is a great deal on the Internet about Kodak's social media strategy - but it seems to be largely about Kodak marketing communications. Journalist Courtney Boyd Myers (@CBM) invites us to Meet the brilliant and beautiful woman behind Kodak’s social media strategy (September 2011). The woman in question is extremely photogenic and obviously good at self-promotion, but there is nothing strategic in the article. The big strategic error here is to regard social media and content management as a marketing issue, separate from the business model itself. This seems to suggest a lack of joined-up thinking - and ultimately a failure of organizational intelligence.
In 2007, Jacob McNulty thought that that instilling the elements of a learning organization would have strongly contributed to a different story for Kodak’s recent years.
A learning organization is one that learns from its mistakes and successes, spots trends in the market and acts on them by being nimble enough to do so. A culture of learning rewards knowledge sharing which reduces the chances that you’ll be blindsided by something like digital in 2007. Kodak could have presented themselves as a picture company many years ago - whether those pictures are on film or in a file it shouldn’t matter. Part of making that transition would require a company that is ready to learn and develop.
Jacob McNulty, Not a Kodak Moment (2007)
Other sources claim that Kodak is a learning organization. In which case, why has it failed to learn the things that matter?
book now Business Architecture Bootcamp (November 22-23, 2011)
book now Workshop: Organizational Intelligence (November 24th, 2011)
Monday, September 06, 2010
Generalization as Business Strategy
#entarch @BBCRadio4 Just listening to a business story on the radio: the music retailer HMV is now going to be selling clothes from its flagship Oxford Street store. Of course this kind of thing is nothing new - retailers have always tried to diversify, and there are clothes shops in Oxford Street that are trying to sell CDs, while large retail chains that started as grocery stores now sell books, clothing, computers, mobile phones and furniture, as well as financial services.
For many enterprise architects, this kind of diversification strategy seems like a "no-brainer". If you have a robust retail process, together with the assets and infrastructure to support the process, then surely it makes sense to make as much use of the process as you can.
But successful diversification is by no means a "no-brainer" (how I despise that term and its implications), but requires careful consideration and planning. This kind of planning should be meat and drink for enterprise architects, but not if they imagine that the decision follows automatically from some abstract process model.
So what models and techniques would be relevant to support an intelligent diversification strategy? And how comfortable are enterprise architects with using these models and techniques to support business decision-making?
These are questions I've looked at before on this blog (see the generic v specific category) and will certainly look at again. Meanwhile, I'd welcome your ideas.
For many enterprise architects, this kind of diversification strategy seems like a "no-brainer". If you have a robust retail process, together with the assets and infrastructure to support the process, then surely it makes sense to make as much use of the process as you can.
But successful diversification is by no means a "no-brainer" (how I despise that term and its implications), but requires careful consideration and planning. This kind of planning should be meat and drink for enterprise architects, but not if they imagine that the decision follows automatically from some abstract process model.
So what models and techniques would be relevant to support an intelligent diversification strategy? And how comfortable are enterprise architects with using these models and techniques to support business decision-making?
These are questions I've looked at before on this blog (see the generic v specific category) and will certainly look at again. Meanwhile, I'd welcome your ideas.
Saturday, May 15, 2010
Differentiation and Integration 2
In my previous post on Differentiation and Integration, I mentioned the Operating Model propounded by Jeanne W. Ross, Peter Weill and David C. Robertson in their book Enterprise Architecture as Strategy (Harvard Business School Press 2006). I shall continue to refer to this book as RWR.
The publisher offers a pdf extract from the book, in which you will see the following diagram, depicting what RWR call a “traditional” approach to IT solutions. (It's a secure pdf, so I've had to scan my library copy instead.)
According to RWR, the “traditional” approach is characterized as follows
Sounds like there is “good integration” and “bad integration”. Which brings us to the squiggles in the diagram. RWR appear to have adopted a notation in which “good integration” is denoted by straight lines and “bad integration” is denoted by squiggly lines. As far as I am aware, this notation has not been not formally defined, and is therefore purely a rhetorical device.
While I accept the need for enterprise architecture to create a powerful strategic narrative, I fear that these rhetorical devices permit and even encourage a kind of woolly uncritical thinking, which is not capable of dealing with the real challenges of enterprise strategy, and could easily be dismissed as intellectually lightweight by sharp CEOs presented with this kind of stuff. Vague diagrams with undefined notation are no substitute for proper analysis.
It doesn't matter how often the three characteristics identified by RWR above are found together, the key question is whether it is possible and practical to separate them. Is data sharing (as RWR believe) the only way to achieve “good integration”, or are (as I believe) other aspects of integration (coordination, organizational intelligence) more strategically important?
Furthermore, both questions seem to be questions of degree ("to what extent") rather than questions of kind (either/or) - so where are the examples of companies whose rightful place is half-way along the path, rather than at one or other extreme?
I find this statement puzzling, because there is no obvious connection between the two dimensions of the operating model identified by RWR (viz standardization and integration qua data sharing) and the idea of competitive differentiation.
There are methods that focus on identifying which business processes will distinguish a company from its competitors, such as the method developed by my former CBDI colleagues out of the ideas of Geoffrey Moore (see my post Tesco Outsources Core ECommerce) but this is not the same as the RWR method.
“A strategic partnership forces a shared-services mentality, requiring business leaders to come to agreement on which services will be provided centrally and which will be provided locally.” (RWR p148)
The decision of which services will be provided centrally or locally is a matter of standardization, and therefore an aspect of enterprise-architecture-as-strategy.
The publisher offers a pdf extract from the book, in which you will see the following diagram, depicting what RWR call a “traditional” approach to IT solutions. (It's a secure pdf, so I've had to scan my library copy instead.)
According to RWR, the “traditional” approach is characterized as follows
- Each strategic initiative results in a separate IT solution, each implemented on a different technology, producing a set of silos.
- The company’s data is patchy, error-prone, and not up-to-date.
- Companies often extract from silos to aggregate data from multiple systems in a data warehouse; but the warehouse is useful only as a reference – it does not offer real-time data across applications.
Sounds like there is “good integration” and “bad integration”. Which brings us to the squiggles in the diagram. RWR appear to have adopted a notation in which “good integration” is denoted by straight lines and “bad integration” is denoted by squiggly lines. As far as I am aware, this notation has not been not formally defined, and is therefore purely a rhetorical device.
While I accept the need for enterprise architecture to create a powerful strategic narrative, I fear that these rhetorical devices permit and even encourage a kind of woolly uncritical thinking, which is not capable of dealing with the real challenges of enterprise strategy, and could easily be dismissed as intellectually lightweight by sharp CEOs presented with this kind of stuff. Vague diagrams with undefined notation are no substitute for proper analysis.
It doesn't matter how often the three characteristics identified by RWR above are found together, the key question is whether it is possible and practical to separate them. Is data sharing (as RWR believe) the only way to achieve “good integration”, or are (as I believe) other aspects of integration (coordination, organizational intelligence) more strategically important?
Contingency Theory
RWR identify two key questions for determining your organization’s strategy.- To determine your organization’s integration requirements, ask yourself to what extent the successful completion of one business unit’s transactions is dependent on the availability, accuracy and timeliness of other business units’ data. (RWR p30)
- To determine your organization’s standardization requirements, ask yourself to what extent the company benefits by having business units run their operations in the same way. (RWR p30)
Furthermore, both questions seem to be questions of degree ("to what extent") rather than questions of kind (either/or) - so where are the examples of companies whose rightful place is half-way along the path, rather than at one or other extreme?
Differentiation
RWR then introduce the notion of strategic differentiation. "The operating model concept requires that management put a stake in the ground and declare which business processes will distinguish a company from its competitors." (RWR p43).I find this statement puzzling, because there is no obvious connection between the two dimensions of the operating model identified by RWR (viz standardization and integration qua data sharing) and the idea of competitive differentiation.
There are methods that focus on identifying which business processes will distinguish a company from its competitors, such as the method developed by my former CBDI colleagues out of the ideas of Geoffrey Moore (see my post Tesco Outsources Core ECommerce) but this is not the same as the RWR method.
Shared Services
One way of achieving some kinds of standardization is through shared infrastructure. When talking about shared services, RWR implicitly shift the scope of “the enterprise” from a single organization to a partnership ecosystem.“A strategic partnership forces a shared-services mentality, requiring business leaders to come to agreement on which services will be provided centrally and which will be provided locally.” (RWR p148)
The decision of which services will be provided centrally or locally is a matter of standardization, and therefore an aspect of enterprise-architecture-as-strategy.
Enterprise Architecture as Quantitative Practice
What I find troubling in many popular accounts of enterprise architecture, including RWR, is the apparent disregard for economics. RWR talk glibly about the costs and benefits of standardization, but they are not willing to explore the economies and diseconomies of scale, or the distribution of fixed and variable costs, and there isn't much meaningful quantification. Handwaving as strategy?Monday, May 10, 2010
Differentiation and Integration
In my post on Business Design Choices, I suggested that the real challenge for business architecture was to appreciate the economic and social impact of structure. I identified some advanced business design choices where business architecture has a useful role to play, and where some IT people might have some relevant aptitude. In this post, I am going to expand on one of these.
Where does standardization make sense, and where should requisite variety be deployed? This question goes back to the work of Lawrence and Lorsch (L2), and has recently been rediscovered (in slightly different terms) by Ross, Weill and Robertson (RWR).
In their book Enterprise Architecture as Strategy, RWR define something they call an Operating Model, with two independent dimensions, business process standardization and integration. "Although we often think of standardization and integration as two sides of the same coin, they impose different demands. Executives need to recognize standardization and integration as two separate decisions." (p27)
Many people in the IT world take for granted that standardization (reduction in variety) is a good thing. RWR acknowledge the benefits of standardization not only in terms of throughput and efficiency, but also predictability. However, they point out the potential downside of standardization both as a state (standardized processes limit local innovation) and as a state-change (politically difficult and expensive to rip out and replace perfectly good and occasionally superior systems and processes).
Integration, which RWR define primarily in terms of data sharing, is also assumed to be a good thing. RWR identify the benefits of integration in terms of efficiency, coordination, transparency and agility, and acknowledge the challenge of integration as a state-change in terms of "difficult, time-consuming decisions".
The two dimensions of standardization and integration produce a two-by-two matrix as follows.
Operating Model Quadrants (Adapted by Clive Finkelstein from Figure 2.3 of “Enterprise Architecture as Strategy”) - Source The Enterprise Newsletter #38.
Although RWR are careful to present a contingency theory of enterprise strategy, in which any of these four operating models may be strategically valid, the conventional rhetoric of the two-by-two matrix places the preferred strategy into the top right quadrant - thus Unification. Many enterprise architects from a traditional IT background may feel most comfortable with the Unification quadrant. (There may be a process of idealization here - see Schwartz.) Indeed, RWR go on to present an Enterprise Architecture Maturity Model, which starts with the easy bits of enterprise architecture (where things are already Unified) and ends with the challenging bits (where things are or should be Diversified).
L2 also identify two dimensions, which they call differentiation and integration. They tend to see increasing differentiation as a healthy response to increasing opportunity and complexity - a growing organization in a growing market - "faster change and greater heterogeneity" (p 235). Differentiation is not merely a difference in working practices, but includes at its core "the difference in cognitive and emotional orientation among managers in different functional departments" (p11).
Integration is then the administrative response to this increasing differentiation - how to maintain the overall coherence and viability of the enterprise as a whole. Integration is defined as "the quality of the state of collaboration that exists among departments that are required to achieve unity of effort by the demands of the environment" (p11). The topic of integration covers both the organizational state and the mechanisms to produce and support this state. For L2, the challenges of integration are not primarily IT related (data sharing) but personal and political (conflict resolution).
L2 don't offer a two-by-two matrix of Differentiation and Integration in their 1967 book (I guess the two-by-two matrix hadn't then established itself as an essential consultancy tool), but if they did then presumably the top-right quadrant would be High Differentiation, High Integration. This very roughly corresponds to what RWR call Coordination.
But in any case, a two-by-two matrix would be misleading. The point isn't to choose whether you have differentiation and integration or not; the point is to determine how much and what kinds of differentiation and integration you need. L2 are explicit in their support of contingency theory (different strategies being appropriate for different organizations depending on environmental factors). The more complex and dynamic the environment, the greater the need for differentiation and integration.
If we are to take business architecture seriously as a discipline, then this kind of question is clearly central. In his post on Contingency Theory and Enterprise Architecture, Andy Blumenthal argues that contingency theory entails keeping your options open, but sometimes it just means making appropriate strategic choices. If the slogan "enterprise architecture as strategy" is to mean anything at all, then surely this is what it means.
Lawrence, P., and Lorsch, J., "Differentiation and Integration in Complex Organizations" Administrative Science Quarterly 12, (1967), 1-30. (see summary here)
Paul R. Lawrence and Jay W. Lorsch, Organization and Environment, Managing Differentiation and Integration. Harvard University 1967.
Jeanne W. Ross, Peter Weill and David C. Robertson, Enterprise Architecture as Strategy. Harvard Business School Press 2006.
Howard S. Schwartz, Narcissistic Process and Corporate Decay – The Theory of the Organizational Ideal. 1990. See his paper On the Psychodynamics of Organizational Disaster (Columbia Journal of World Business, Spring 1987) See also Joe Bormel's blogpost on Narcissism, Oxygen and HCIT Vision (June 2009).
Related posts
Business Design Choices (January 2010)
EA Effectiveness and Process Standardization (August 2012)
Where does standardization make sense, and where should requisite variety be deployed? This question goes back to the work of Lawrence and Lorsch (L2), and has recently been rediscovered (in slightly different terms) by Ross, Weill and Robertson (RWR).
In their book Enterprise Architecture as Strategy, RWR define something they call an Operating Model, with two independent dimensions, business process standardization and integration. "Although we often think of standardization and integration as two sides of the same coin, they impose different demands. Executives need to recognize standardization and integration as two separate decisions." (p27)
Many people in the IT world take for granted that standardization (reduction in variety) is a good thing. RWR acknowledge the benefits of standardization not only in terms of throughput and efficiency, but also predictability. However, they point out the potential downside of standardization both as a state (standardized processes limit local innovation) and as a state-change (politically difficult and expensive to rip out and replace perfectly good and occasionally superior systems and processes).
Integration, which RWR define primarily in terms of data sharing, is also assumed to be a good thing. RWR identify the benefits of integration in terms of efficiency, coordination, transparency and agility, and acknowledge the challenge of integration as a state-change in terms of "difficult, time-consuming decisions".
The two dimensions of standardization and integration produce a two-by-two matrix as follows.
Operating Model Quadrants (Adapted by Clive Finkelstein from Figure 2.3 of “Enterprise Architecture as Strategy”) - Source The Enterprise Newsletter #38.
Although RWR are careful to present a contingency theory of enterprise strategy, in which any of these four operating models may be strategically valid, the conventional rhetoric of the two-by-two matrix places the preferred strategy into the top right quadrant - thus Unification. Many enterprise architects from a traditional IT background may feel most comfortable with the Unification quadrant. (There may be a process of idealization here - see Schwartz.) Indeed, RWR go on to present an Enterprise Architecture Maturity Model, which starts with the easy bits of enterprise architecture (where things are already Unified) and ends with the challenging bits (where things are or should be Diversified).
L2 also identify two dimensions, which they call differentiation and integration. They tend to see increasing differentiation as a healthy response to increasing opportunity and complexity - a growing organization in a growing market - "faster change and greater heterogeneity" (p 235). Differentiation is not merely a difference in working practices, but includes at its core "the difference in cognitive and emotional orientation among managers in different functional departments" (p11).
Integration is then the administrative response to this increasing differentiation - how to maintain the overall coherence and viability of the enterprise as a whole. Integration is defined as "the quality of the state of collaboration that exists among departments that are required to achieve unity of effort by the demands of the environment" (p11). The topic of integration covers both the organizational state and the mechanisms to produce and support this state. For L2, the challenges of integration are not primarily IT related (data sharing) but personal and political (conflict resolution).
L2 don't offer a two-by-two matrix of Differentiation and Integration in their 1967 book (I guess the two-by-two matrix hadn't then established itself as an essential consultancy tool), but if they did then presumably the top-right quadrant would be High Differentiation, High Integration. This very roughly corresponds to what RWR call Coordination.
But in any case, a two-by-two matrix would be misleading. The point isn't to choose whether you have differentiation and integration or not; the point is to determine how much and what kinds of differentiation and integration you need. L2 are explicit in their support of contingency theory (different strategies being appropriate for different organizations depending on environmental factors). The more complex and dynamic the environment, the greater the need for differentiation and integration.
If we are to take business architecture seriously as a discipline, then this kind of question is clearly central. In his post on Contingency Theory and Enterprise Architecture, Andy Blumenthal argues that contingency theory entails keeping your options open, but sometimes it just means making appropriate strategic choices. If the slogan "enterprise architecture as strategy" is to mean anything at all, then surely this is what it means.
Lawrence, P., and Lorsch, J., "Differentiation and Integration in Complex Organizations" Administrative Science Quarterly 12, (1967), 1-30. (see summary here)
Paul R. Lawrence and Jay W. Lorsch, Organization and Environment, Managing Differentiation and Integration. Harvard University 1967.
Jeanne W. Ross, Peter Weill and David C. Robertson, Enterprise Architecture as Strategy. Harvard Business School Press 2006.
Howard S. Schwartz, Narcissistic Process and Corporate Decay – The Theory of the Organizational Ideal. 1990. See his paper On the Psychodynamics of Organizational Disaster (Columbia Journal of World Business, Spring 1987) See also Joe Bormel's blogpost on Narcissism, Oxygen and HCIT Vision (June 2009).
Related posts
Business Design Choices (January 2010)
EA Effectiveness and Process Standardization (August 2012)
Thursday, October 29, 2009
Ecosystem SOA
The SOA world is finally catching up with some of the ecosystem ideas that I published in my 2001 book on the Component-Based Business (see my Slideshare presentation) and developed further in several articles and presentations for the CBDI Forum over a number of years.
The biological approach to creating business and software services is radically different to the solution-driven approach, and is based on biological and ecological metaphors.
(Some people use the term Web Oriented Architecture (WOA) for what I'm calling Ecosystem SOA.)
If we regard these as phases of maturity, then we can have a straightforward roadmap from left to right, as in for example the CBDI SOA Roadmap. However, some organizations may need to tackle these styles of SOA in parallel rather than in sequence.
A service portfolio plan for Enterprise SOA can be based on an enterprise model that identifies the capabilities of the enterprise and clusters these into domains. In the CBDI Forum's SAE methodology, the domains are classified as Core and Contextual according to a matrix derived from Geoffrey Moore. (Note how the domains migrate around the matrix over time.) See for example my blogpost Tesco outsources core eCommerce.
A similar model, derived from Amin and Cohendet's book Architecture of Knowledge, explicitly describes Core and Periphery in terms of knowledge intensity. In other words, the reason something is classified as Core is because it encapsulates some important (strategic) knowledge.
For example, an insurance company knows more about insurance than about cars, so when providing car insurance it may decide to partner with other organizations that know more about cars than about insurance. This results in a composition of insurance-related services and car-related services (for example, determining the insurable value of a used car). Such compositions can be either directed (in other words, composed by a single dominant player) or collaborative (in other words, emerging from the interaction between multiple players within the ecosystem).
For example, an online retailer knows about her products and services, but doesn't wish to become an expert in credit card handling, or to be responsible for data protection and security, so she delegates these concerns to a specialist provider that knows more about these matters.
Similar considerations can apply to industry consortia, such as ACORD (for the insurance market). ACORD can define generic service-based assets (such as models, schemas, interfaces and so on) for insurance. However, insurance companies will also wish to use generic service-based assets to cover requirements that are not insurance-specific, such as customer management or complaints handling, where ACORD may not be able to add any knowledge-value, and it would be appropriate for ACORD to regard these as peripheral to its own activities rather than core.
So one approach to Ecosystem SOA is to push out from the enterprise into the ecosystem. John Hagel calls this Inside-Out Architecture, which he contrasts with Outside-In Architecture. (See my post on Outside-In Architecture.)
An Outside-In Architecture starts with a model of (the flows of) knowledge and value in the ecosystem as a whole. The strategic question for an enterprise is how to find way of both contributing value to the ecosystem, and drawing value from the ecosystem, through the provision of ecologically viable services.
For example, a telecoms company might reasonably consider that its core competence is something to do with communications. So a positional strategy would drive it to a dominant position in the middle of a large communication ecosystem, providing a platform of services that add value to a diverse range of communication activities by other people. The dominant position would allow it to negotiate a strong share of the value generated.
However, respect for the ecosystem would lead it to leave sufficient value to third parties to maintain the economic health of the remainder of the ecosystem. Instead of a simple positional strategy, a relational strategy (based on mutual trust with ecosystem partners) should produce a more sustainable and ecologically sound ecosystem.
- Supply and Fit (September 2000)
- Identifying Components 2 (October 2001)
- Opportunities in the Insurance Ecosystem (December 2004)
- Business Strategy Planning for the Service Economy (May 2006)
The biological approach to creating business and software services is radically different to the solution-driven approach, and is based on biological and ecological metaphors.
- First we identify an ecosystem, which may contain both human users and existing artefacts.
- Then we identify services that would be meaningful and viable in this ecosystem.
- Then we procure devices that enable the release and delivery of these services into the ecosystem.
Solution-Driven (Specific)
|
Solution-Driven (General)
|
Evolution-Driven
|
| Identify Business Problem Identify "Users" Negotiate Requirements Define Solution | Identify Domain Identify Domain Experts Define Requirements Design Solution Kit | Identify Ecosystem Identify Services Procure and Release Devices |
| Experimental SOA | Enterprise SOA | Ecosystem SOA |
(Some people use the term Web Oriented Architecture (WOA) for what I'm calling Ecosystem SOA.)
If we regard these as phases of maturity, then we can have a straightforward roadmap from left to right, as in for example the CBDI SOA Roadmap. However, some organizations may need to tackle these styles of SOA in parallel rather than in sequence.
A service portfolio plan for Enterprise SOA can be based on an enterprise model that identifies the capabilities of the enterprise and clusters these into domains. In the CBDI Forum's SAE methodology, the domains are classified as Core and Contextual according to a matrix derived from Geoffrey Moore. (Note how the domains migrate around the matrix over time.) See for example my blogpost Tesco outsources core eCommerce.
A similar model, derived from Amin and Cohendet's book Architecture of Knowledge, explicitly describes Core and Periphery in terms of knowledge intensity. In other words, the reason something is classified as Core is because it encapsulates some important (strategic) knowledge.
For example, an insurance company knows more about insurance than about cars, so when providing car insurance it may decide to partner with other organizations that know more about cars than about insurance. This results in a composition of insurance-related services and car-related services (for example, determining the insurable value of a used car). Such compositions can be either directed (in other words, composed by a single dominant player) or collaborative (in other words, emerging from the interaction between multiple players within the ecosystem).
For example, an online retailer knows about her products and services, but doesn't wish to become an expert in credit card handling, or to be responsible for data protection and security, so she delegates these concerns to a specialist provider that knows more about these matters.
Similar considerations can apply to industry consortia, such as ACORD (for the insurance market). ACORD can define generic service-based assets (such as models, schemas, interfaces and so on) for insurance. However, insurance companies will also wish to use generic service-based assets to cover requirements that are not insurance-specific, such as customer management or complaints handling, where ACORD may not be able to add any knowledge-value, and it would be appropriate for ACORD to regard these as peripheral to its own activities rather than core.
So one approach to Ecosystem SOA is to push out from the enterprise into the ecosystem. John Hagel calls this Inside-Out Architecture, which he contrasts with Outside-In Architecture. (See my post on Outside-In Architecture.)
An Outside-In Architecture starts with a model of (the flows of) knowledge and value in the ecosystem as a whole. The strategic question for an enterprise is how to find way of both contributing value to the ecosystem, and drawing value from the ecosystem, through the provision of ecologically viable services.
For example, a telecoms company might reasonably consider that its core competence is something to do with communications. So a positional strategy would drive it to a dominant position in the middle of a large communication ecosystem, providing a platform of services that add value to a diverse range of communication activities by other people. The dominant position would allow it to negotiate a strong share of the value generated.
However, respect for the ecosystem would lead it to leave sufficient value to third parties to maintain the economic health of the remainder of the ecosystem. Instead of a simple positional strategy, a relational strategy (based on mutual trust with ecosystem partners) should produce a more sustainable and ecologically sound ecosystem.
Sunday, March 15, 2009
Business Strategy and Alignment
Which relationships dominate an organization? Some organizations are driven by customer relationships, some by partner/supplier relationships, and some by technology and research.
One of the ideas I picked up many years ago from a paper by Professor Joseph Tidd was the strategic importance of this choice: which external relationships are dominant, and how this affects the internal power relationships within the organization.
Obviously such business strategies will need to be supported by information systems that communicate across and between organizations in an appropriate manner. Some strategies may require so-called Chinese walls, providing a level of protection from information leaking prematurely to competitors. Some strategies require a degree of proximity bordering on intimacy - business jargon refers to this as "getting into bed with" your suppliers or customers or business partners.
So I was interested to read an interview with Prith Banerjee, director of HP Labs (Riding the Recession the HP Way, BBC News, 14 March 2009). Here are some key quotes.
In other words, HP believes the business architecture implemented last year gives it greater viability in the current environment. We shall see if they are right.
Tidd, J. 'Technological Innovation, Organizational Linkages and Strategic Degrees of Freedom', Technology Analysis and Strategic Management 5(3) 1993, pp 273-284
One of the ideas I picked up many years ago from a paper by Professor Joseph Tidd was the strategic importance of this choice: which external relationships are dominant, and how this affects the internal power relationships within the organization.
- For example, a technology breakthrough strategy would be driven by R&D, often in close collaboration with companies that would normally be regarded as competitors.
- By contrast, a strategy of technology fusion would require a much stronger role for production, with close links to suppliers of component technology.
Obviously such business strategies will need to be supported by information systems that communicate across and between organizations in an appropriate manner. Some strategies may require so-called Chinese walls, providing a level of protection from information leaking prematurely to competitors. Some strategies require a degree of proximity bordering on intimacy - business jargon refers to this as "getting into bed with" your suppliers or customers or business partners.
So I was interested to read an interview with Prith Banerjee, director of HP Labs (Riding the Recession the HP Way, BBC News, 14 March 2009). Here are some key quotes.
The world's largest technology company says a major reorganisation of research efforts last year will help it survive the downturn and secure its future. In 2008 HP announced a "groundbreaking" move to align the work done in its labs more closely with business goals. ... While most companies keep their most valuable research projects under wraps, HP has taken a different tack. Everything is out in the open and there is a real emphasis on collaboration with universities, government and other industry players.
In other words, HP believes the business architecture implemented last year gives it greater viability in the current environment. We shall see if they are right.
Tidd, J. 'Technological Innovation, Organizational Linkages and Strategic Degrees of Freedom', Technology Analysis and Strategic Management 5(3) 1993, pp 273-284
Sunday, July 13, 2008
Strategy isn't a Direction
Someone called Guilhem (possibly a descendent of Guilhem de Peitieu) dismissed my post on Enterprise Architect - Joke or Joker with the comment
I am not quite sure what I said to give him that impression. My view of strategy is a bit like a dungeons and dragons game or Maoist opera ("Taking Tiger Mountain by Strategy") - you pursue (not drive) a complex strategy, going in many directions, sometimes picking up useful tools (technology initiatives), which may help to kill or tame some of the dragons (or Kuomintang bandits).
But of course there is an important difference. In a game, every tool you find may have some meaning or use within the context of the game. In real life (or work, which is the nearest approximation to real life for most of us), the dungeons are littered with flashy software and services, and the best strategy is to ignore most of it. (Twitter, anyone?)
But not all of it. Find some useful tools, and learn to use them properly and appropriately: that's my technology initiative.
"i am sure you are the kind of guy who enjoys driving strategic direction through technology initiatives"
I am not quite sure what I said to give him that impression. My view of strategy is a bit like a dungeons and dragons game or Maoist opera ("Taking Tiger Mountain by Strategy") - you pursue (not drive) a complex strategy, going in many directions, sometimes picking up useful tools (technology initiatives), which may help to kill or tame some of the dragons (or Kuomintang bandits).
But of course there is an important difference. In a game, every tool you find may have some meaning or use within the context of the game. In real life (or work, which is the nearest approximation to real life for most of us), the dungeons are littered with flashy software and services, and the best strategy is to ignore most of it. (Twitter, anyone?)
But not all of it. Find some useful tools, and learn to use them properly and appropriately: that's my technology initiative.
Sunday, May 01, 2005
Service-Oriented Business Strategy
A service-oriented modelling approach helps us to identify alternative business strategies, involving the creation and deployment of added-value services.
Pharma appears to illustrate some general characteristics of complex service networks, so this example should be of relevance to other industry sectors.
Above all, for SOA illustration purposes, pharma has two advantages. Firstly, it isn't the same old boring examples everyone else is using (finance, travel, retail). And secondly, it isn't military.
In the past, drug companies have been able to make substantial profits from an essentially drug-centric process, getting high sales volumes for its blockbuster drugs from a largely undifferentiated mass of patients with a given condition. This business model treated the physician or clinic as pretty much equivalent to a retail outlet, and did not involve any relationship with the end-customer (the drug consumer). But this business model is subject to major challenge from several directions.
We model a service-oriented business as a system of systems. Services here may include tasks automated in software (typically but not necessarily rendered as web services) as well as human tasks.
SOA is not just about decomposition – producing fine-grained services with maximum decoupling. Equally important is to think about composition – how these services can be integrated in many different ways to support a wide variety of demand.
In general terms, there are a number of distinct categories of stakeholder, each performing fairly complex functions in relation to the pharma value chain. A key SOA challenge for a drug company is to provide services to all these different stakeholders in a consistent and coordinated yet flexible way. In order to meet this challenge, we need to produce a series of models, from different stakeholder perspectives, showing how the services can be composed in various contexts of use.
In our view, the essential shift for service-oriented modeling is to view the services, not from the provider's perspective, but from the customer's perspective, and in the customer's context of use.
The ultimate source of value for the patient is defined in terms of health. The provision of health to patients is based on the deployment of complex medical knowledge by a physician, and this in turn relies on information about particular drugs and combinations of drugs from the drug company and elsewhere. This essentially defines a value ladder, in which the value of the drugs contributes to the value of the heathcare.
While this kind of strategic reframing is widely discussed, what service-oriented modeling provides is a systematic way of determining and analyzing the strategic options, in terms of the value ladders that can be supported.
Can the drug company solve all the problems of healthcare? Can the physician solve all the problems of healthcare? The answer in both cases is of course NO. There is huge complexity involved, and the design goal for SOA is to define a reasonable separation of concerns between the physician and the drug company, that allows each of them to manage an appropriate part of the complexity.
Previous Post: SOA Pharma
- Identify value-added business services that can be seen (by customers) as more relevant to the context of use.
- Identify value-added business services that are flexible / reusable (by customers) in multiple use-contexts.
- Compose value-added business services in an efficient and reliable manner from internal and external capabilities.
- Provide a service platform to support customers in composing our business services to solve their problems.
Why Pharma?
We selected the pharmaceutical industry for a worked example because it provides a good example of a complex information supply chain. A drug company (in collaboration with a distributed network of research and test) produces a drug, together with lots of information relating to the drug. There are several different categories of information user: the patient who takes the drug, the medical practitioner who prescribes and/or dispenses the drug, the health service or insurer that pays for the drug, and the regulator who monitors the safety of the drug.Pharma appears to illustrate some general characteristics of complex service networks, so this example should be of relevance to other industry sectors.
Above all, for SOA illustration purposes, pharma has two advantages. Firstly, it isn't the same old boring examples everyone else is using (finance, travel, retail). And secondly, it isn't military.
In the past, drug companies have been able to make substantial profits from an essentially drug-centric process, getting high sales volumes for its blockbuster drugs from a largely undifferentiated mass of patients with a given condition. This business model treated the physician or clinic as pretty much equivalent to a retail outlet, and did not involve any relationship with the end-customer (the drug consumer). But this business model is subject to major challenge from several directions.
Approach
We model a business as an open system, whose viability depends on robust and appropriate interactions with a dynamic environment. (This contrasts with the closed system approach adopted by many traditional business modeling methods, whose focus is on producing a complete and coherent account of some internal configuration of processes and services, against a fixed view of the environment.)We model a service-oriented business as a system of systems. Services here may include tasks automated in software (typically but not necessarily rendered as web services) as well as human tasks.
SOA is not just about decomposition – producing fine-grained services with maximum decoupling. Equally important is to think about composition – how these services can be integrated in many different ways to support a wide variety of demand.
In general terms, there are a number of distinct categories of stakeholder, each performing fairly complex functions in relation to the pharma value chain. A key SOA challenge for a drug company is to provide services to all these different stakeholders in a consistent and coordinated yet flexible way. In order to meet this challenge, we need to produce a series of models, from different stakeholder perspectives, showing how the services can be composed in various contexts of use.
In our view, the essential shift for service-oriented modeling is to view the services, not from the provider's perspective, but from the customer's perspective, and in the customer's context of use.
Strategic Reframe
From the perspective of business strategy, what we are looking at here is a strategic reframe of the pharma business. What is the drug company actually selling, and to whom? How does information and services become an integral component of the overall product offering?The ultimate source of value for the patient is defined in terms of health. The provision of health to patients is based on the deployment of complex medical knowledge by a physician, and this in turn relies on information about particular drugs and combinations of drugs from the drug company and elsewhere. This essentially defines a value ladder, in which the value of the drugs contributes to the value of the heathcare.
While this kind of strategic reframing is widely discussed, what service-oriented modeling provides is a systematic way of determining and analyzing the strategic options, in terms of the value ladders that can be supported.
Can the drug company solve all the problems of healthcare? Can the physician solve all the problems of healthcare? The answer in both cases is of course NO. There is huge complexity involved, and the design goal for SOA is to define a reasonable separation of concerns between the physician and the drug company, that allows each of them to manage an appropriate part of the complexity.
Previous Post: SOA Pharma
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