How to craft a data strategy?

[Harikumar]

Bringing together the data strategy of a large organization with diverse business portfolios and varying targets require significant effort, especially when each portfolio has different levels of data maturity. As any other strategy, data strategy should land on the WHY, WHAT and HOW and it requires regular updates, especially with the rapid changes in technology and macroeconomic factors that influence the business direction.

Purpose and outcomes (WHY)

• Why is it crucial to have an effective data strategy? The data strategy must support the organizational mission, vision and overall business strategy; It should draw a picture of what the organization would look like in next 5 years leveraging data capabilities. The data strategy must describe the value(s) and the choices with prioritization to reach the future star.
• It is important to establish a baseline of the organization’s data maturity. Achieving this requires engagements and interviews with various key stakeholders who represent different portfolios. Identifying a focal point from each portfolio can simplify the process.
• For the interview, your questionnaire should encompass various dimensions including governance, data quality, platforms and tools, data access, value derived from data, etc. This would also be a good time to foster a sense of partnership and ownership among the stakeholders.
• Once you have collected information from your stakeholders and scored against each dimension, identify the top common themes that needs improvement and underpins the organizational strategy.

Key capabilities (WHAT)

• Bringing the optics of process, people and technology is important.
• What are the process changes to augment governance and ways of working? Should data accountabilities be assigned to roles and reinforced during goals settings?
• To create a data community, what are the people related transformation needed with respect to skills & mindset?
• Engagements with architecture team is important to understand the point C vision on platforms and tools.
• Externalization during this stage can prove helpful. What are partners, competitors doing, gathering insights from industry research done by Gartner, Forrester, etc. What are the advancements in technology? Would you prefer to be an early adopter or follower?
• After gathering various inputs, summarize the value levers that lead to desired outcomes and prioritize which opportunities to pursue. Then create a heatmap of the various capabilities to exploit the opportunities. Identify the top enablers to execute and barriers to address.  

Roadmap (HOW)

• Create a plan to execute the strategy, a roadmap with improvements to pursue and by when.
• Execution of opportunities and improvements should be done by the respective departments or focal. Hence it is important to continuously secure buy in for the data strategy from stakeholders and executive leaders on a recurring manner, to ensure alignment, commitment and support.

Monitoring execution of the plan is essential and as previously mentioned, the strategy must be flexible to accommodate changing priorities and circumstances.