Assembling your Data Strategy - walk in the way of insight

How many pillars (or components or building blocks) does your data strategy need? I found lots of different answers, from random bloggers to the UK Government.

3

An anonymous blogger who writes under the pen-name Beautiful Data identifies three pillars of data strategy.

• Data Management - managing data as an asset
• Data Democratization - putting data into the hands of the business
• Data Monetization - driving direct and indirect business benefit

4

SnapAnalytics identifies People, Process, Data and Technology as its four pillars, and that's a popular approach for many things.

For a different approach, we have four pillars of data strategy from Aleksander Velkoski, the Director of Data Science at the National Association of Realtors.

• Data Literacy
• Data Acquisition and Governance
• Knowledge Mining
• Business Implementation

Olga Lagunova, Chief Data Analytics Officer at Pitney Bowes, identifies four pillars that are roughly similar.

• Business Outcome - knowing what you want to achieve
  
• Mature Data Ecosystem - including data sourcing and data governance
• Data Science - practices and organization
  
• Culture that values data-driven decision

In his conversation with her, Anthony Scriffignano, Chief Data Scientist at Dun & Bradstreet, replies that "we have many of those same elements". Perhaps because he is in the business of selling data, Anthony looks at data strategy from two directions, which broadly correspond to Olga's first two pillars.

• Customer-centric - addressing customer needs, solving ever more complex business problems
• Data-centric - data supply chain, including sourcing, quality assurance and governance

The UK National Data Strategy also has four pillars.

• Data Foundations
• Data Skills
• Data Availability
• Responsible Data
  

5

A white paper from SAS defines five essential components of a data strategy - Identify, Store, Provision, Process and Govern. But a component isn't a pillar. So the editors of Ingenium magazine have turned these into five pillars - Identify, Store, Provision, Integrate and Govern.

(The SAS paper talks a lot about integration, so the Ingenium modification of the SAS list seems fair.)

6

For six pillars, we can turn to Cynozure, a UK-based data and analytics strategy consultancy.

• Vision and Value
• People and Culture
• Operating Model
• Technology and Architecture
• Data Governance
• Roadmap

Cynozure has also published seven building blocks.

• Data Vision
• Data Sources
• Data Governance and Management
• Data Analysis
• Data Team
• Tech Stack
• Measuring Success
  

7

At last we get to the magic number seven, thanks to @EvanLevy.

• The Questions (aka Problems) - the more valuable your question, the more valuable analytics is to the company
• Technical Implementation - he argues that the most valuable datasets require high levels of customization
  
• The Users - access and control (this links to the Data Democratization pillar mentioned above)
  
• Data Storage and Structure - including data retention
  
• Data Security - risk and compliance
  
• Personally Identifiable Information (PII) - privacy
  
• Visualization and Analysis Needs - flexibility and timeliness
  

 

Lawrence of Arabia's autobiography was entitled Seven Pillars of Wisdom, and this is of course a reference to the Bible. 

Wisdom has built her house; she has set up its seven pillars. ...
Leave your simple ways and you will live; walk in the way of insight.

Proverbs 9.1

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Maybe it doesn't matter how many pillars your data strategy has, as long as it gets you walking in the way of insight. (Whatever that means.)

Obviously not everyone is using the pillar metaphor in the same way - there is presumably some difference between a foundation, a pillar and a building block - but there is a lot of commonality here as well, with a widely shared emphasis on business value and people, as well as a few interesting outliers. 

While most of the sources listed in this blogpost are fairly brief, the UK National Digital Strategy contains a lot of detail. While it deserves credit for the attention devoted to ethics and accountability in the Responsibility pillar, it is not yet clear to me how it addresses some of the other concerns mentioned in this blogpost. I plan to post a more thorough review in a separate blogpost.

 

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"Beautiful Data", Three Pillars of a Data Strategy (19 Sept ??)

Cynozure, Building A Data Strategy For Business Success (Cynozure, 29 May 2019)

Jason Foster, The Six Pillars of a Data Strategy (Cynozure via YouTube, 19 April 2019)

Ingenium, The 5 Pillars of a Data Strategy (Ingenium Magazine, 24 August 2017)

Evan Levy, 7 Pillars of Data Strategy (HighFive, 1 March 2018)

SAS, The 5 Essential Components of a Data Strategy (SAS 2018)

Anthony Scriffignano and Olga Lagunova, Data Strategy - Key Pillars That Define Success (Dun & Bradstreet via YouTube, 29 March 2018)

UK Government, UK National Data Strategy (Department for Digital, Culture, Media and Sport, 9 September 2020)

Aleksander Velkoski, The Four Pillars of Data and Analytics Strategy (Business Quick, 24 August 2020)