Awhile back I was consulting on a project where the client wanted to apply more science to their decision-making. Though my team and I did a great job assisting this client, that request has been bouncing about the recesses of my mind for some time. I spent long hours appreciating and defining the problem to be solved and researching the related landscape. A few questions I am grappling with include:
- Where should we start with data?
- Is it appropriate for a transformational initiative or program to have its own data strategy?
- How would a program data strategy align with an enterprise data strategy?
- What are the critical components of a data strategy?
I read many books on data, including topics ranging from establishing corporate data strategy and the use of analytics to harnessing big data for competitive advantage.
I wanted a concise template that I could put in my consulting toolbox and use to help clients posture their program for success by creating a programmatic approach to data before they jumped into the process without a thoughtful plan. Due to the nature of consulting, in which every company’s needs are different, I asked myself if I was being realistic in my quest for a template where “one size fits all.”
My research uncovered some common data strategy themes. I also came to the conclusion that it is completely appropriate to have a data strategy at the program or initiative level. My position is that when you know you will be working with data, you are well served if you begin with a strategy.
I did not find the simple, concise data strategy tool that I wanted. So I developed my own tool, as shown in Figure 1.
Each component of my tool deserves at least a chapter, its own book, or a lengthy conversation to fully grasp its rationale, nuances, considerations, and approaches as you begin to work through them for your specific company.
This blog is not the place to immerse you in all this information. Suffice to say, Figure 1 is a data strategy template that is scalable from project level to enterprise level. As you consider working with data, use this tool to prepare for and guide your thinking and discussion about a data strategy for your unique situation.
Figure 1. Data Strategy Critical Components
| Determine your overall business purpose. Clarify the problem you want to solve: improve decision-making, improve operations, monetize data; identify the decisions you need to make to solve this business problem. |
| Determine the data needed. Determine what data is needed to solve the strategic business purpose/problem; target that data specifically. |
| Determine data sourcing and collection approach. Determine where data will come from, structured/unstructured data, cloud/server based. Determine what you need to do to make the needed data available (i.e., build an Application Program Interface [API]; coordinate with different parts of the business). Determine if you need proxy data. |
| Determine how to turn data into insights. Determine the tools, algorithms, processes, and approaches needed to generate actionable intelligence, that will inform the business decisions. |
| Create a technology and data infrastructure. Determine what data integrations, data storage, organizational capacity, and security firewalls are needed. |
| Identify critical data analytics skills. Inventory your internal data and analytic capability and capacity; upskill, hire, or purchase talent as needed. |
| Establish visualization and reporting requirements. Consider the breadth of access to data summaries and reports; identify the frequency, access, and tools needed to consume the actionable intelligence. |
| Establish data security. Consider regulatory requirements, theft prevention, and malicious attack prevention; define strategies for data security (i.e., customer information, encryption, firewalls, data segmentation, access). |
| Create data governance. Determine enforcement for compliance, data maintenance, access, etc. |
I believe business today is at an inflection point; I see more and more businesses asking for assistance to apply science to their decisions. We are watching the information age unfold before our eyes. Each day, we are experiencing new ways of data collection and learning how data is being used to grow businesses and enrich our lives. We are also seeing examples of when data planning gaps are exposed (collecting the wrong data, data breaches, etc.) and even when data may be used for nefarious purposes (influence elections, etc.).
Embracing a data strategy will not only contribute to a more comprehensive data plan, it can help align your work with corporate business goals, drive efficiencies, and improve decision-making confidence—it is also necessary to help you stay ahead and win in a competitive market.
How does this data strategy template compare to the way you think about data?
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