Building a Solid Analytics Foundation

Chris Lee
Sep 15, 2021

Key takeaways:

The kind of foundation your organization should build depends on its current cultural and technical capabilities.
Start by understanding where your organization is today using this framework.

In an earlier blog post, we wrote about building foundations on which predictive analytic capabilities could be built. The key idea was this:

Analytic capabilities are defined by the combination of organizational culture and technology which a company brings to bear in using the data it generates. Ultimately, the goal is to have enough strength in both culture and technology that productive business outcomes can be achieved.
– From Analytics Success is a Process

One way to think about building this foundation is to consider what technical and cultural capabilities an organization already has. With this understanding you can determine which actions to take to effectively move towards a predictive level of analytics capacity. Figure 1 below shows this idea.

Figure 1 – Quad chart showing various readiness stances from which to build a foundation for predictive analytics

To be clear, these quadrants should not be viewed as levels – we’re not suggesting that an organization move through the quadrants “mastering” each one on the way. There is no need to create an “expert” organization before predictive analytics can be used effectively. It is also worth saying that we don’t view any of the quadrants as necessarily better than any of the others. Each one simply reflects a starting point that comes with its own opportunities and challenges.

The first step in building a foundation is to determine where your organization is starting from. The table below provides a description of the characteristics of each quadrant to help in making this assessment.

Technical readiness	Cultural readiness	Characteristics
Low	Low	General belief that data and analytics might be important but it isn’t THAT important – there are always more important things to get done. May use data to drive some decisions. There may be a number of different tools for analyzing that data. But the organization lacks a consistently applied process and set of sufficiently sophisticated tools to effectively use across groups.
Low	High	Strong belief that data and analytics are the key to “breaking out.” It isn’t a question of “if.” It’s a question of “how.” This belief in data is hampered by the lack of consistently applied processes, tools and expertise which enable the effective collection or use of data.
High	Low	Strong technical know-how and belief by a subset of the organization that data and analytics are important for solving business problems. Organization has a host of analytic tools and a number of experts to use them but those tools are inconsistently applied due to a lack of general buy-in or incentives.
High	High	There is a cultural expectation that data and the “right” analytic methods will be used across the organization and equipment. The organization has a “complete” set of tools for gathering and using data as well as the processes and metrics which ensure those tools are used. “Complete” is understood to be a journey with a fluid definition that changes as problems and as technologies change.

The capabilities that your organization will need and be able to leverage will suggest the kind of foundation you should build. We’ll start looking at the various starting points and the path to becoming predictive practitioners in the next post.