By using tdwi.org website you agree to our use of cookies as described in our cookie policy. Learn More

TDWI Articles

How Pyramid Thinking Can Revolutionize Your Data Strategy

By taking a top-down approach to developing your data strategy, you can meet your organizational goals even more efficiently.

Data is now essential to the way in which most companies operate and set their strategy -- from optimizing supply chains and creating better customer experiences to strategic use in future planning. However, before you can get the most out of your data, it’s imperative for you to consider how you use it and what the desired impact of doing so is. In essence, what is your data strategy?

For Further Reading:

Anatomy of a Data Strategy: From Operational Intelligence to Artificial Intelligence

5 Steps to Creating a Data Strategy to Drive Your Nonprofit's Social Good

Must-Know Data Strategy Priorities for CIOs

The Pyramid Approach Puts Business Goals First

Before devising a corporate data strategy, the main things you need to know are the strategy and objectives of your organization as a whole. Data can be a truly transformative tool, but even the sharpest knife needs to be used accurately to get the best results -- which is why you need to know the end goal before you can understand how data can help you achieve it. This end goal forms the very peak of the pyramid and it is by looking downwards from it that you can understand the role that data can play.

For organizations struggling to pinpoint that goal (as oftentimes happens when the business strategy isn’t well-defined and documented), it is worth considering key business problems and the consequent opportunities for improvement. Take the example of a retailer. Efforts may be concentrated in sourcing and pricing cost-effective products, processing them through the various points of the supply chain, getting them into shops or online, marketing those products, looking at the customer experience, and then improving the product. By looking at this value chain from a business-first perspective, you can start to identify where the right data, insights, and analytics can play a part in improving some or all of that value chain.

Once you know the business goals and objectives, it is important to understand the outcomes needed to reach the goal. Do you need to consider reducing business running costs, entering new markets, or boosting customer acquisition? Are there other, more specialized sector outcomes to be considered? Achieving these smaller milestones will lead to ultimately reaching your main goal, so identifying those benefits and putting them against specific figures or value statements can help you visualize the end result. This isn’t about defining the business strategy or operations but understanding them in a way that allows you to apply data-guided thinking.

The Pyramid Formula

Identifying business goals gives you the basis upon which to build your data strategy, and with that you can begin to be more specific about the change you are looking to make. An actionable and measurable formula helps you shape those changes with clarity, such as “we want to do x by measuring/tracking/analyzing y in order to do z.”

This helps you identify the data points needed to take action and measure impact. For example, say we have established the business goal of reducing operating costs. A possible pyramid formula would be “we want to improve the efficiency of the warehouse by measuring the travel time for products moving between warehouse zones in order to remove blockers and increase the throughput.” This is a clear, measurable statement of change that links directly back to our goal.

Asking the Right Questions

Although data is hugely valuable to achieve business goals, simply collecting data is not enough. Thorough data analysis is essential to reveal actionable insights. By asking the right questions, an organization can gain a deeper understanding of its processes and use this insight to drive better performance.

The more specific the questions, the more focused the data strategy. Continuing with the warehouse example, business questions that can enable better data management and hence improve performance could concentrate on whether the warehouse is operating effectively and which, if any, problems are currently affecting efficiency. These questions can help businesses to make more informed decisions about where to focus efforts to achieve the best results.

Why the Pyramid Approach Works

Although working down from the top rather than from the bottom up may seem counterintuitive, if we had done this the other way around, we wouldn’t necessarily know where the focus should be and therefore whether our efforts were aligned with business goals.

For example, say we have data including product hierarchy, warehouse schedule, and warehouse timesheets. Without the business goal and the pyramid formula, we wouldn’t know why we need a product hierarchy in the central data warehouse. We wouldn’t know what we do with the warehouse timesheets or the supply chain movements because we haven’t thought it through from the point of view of linking back to the overall goals of the organization.

Pyramid Thinking in Action

Now that we have considered why we are approaching the data strategy this way and how we can reach our goal, we can understand what a top-down pyramid thinking data strategy may look like. For example:

  • A goal might be to improve the warehouse efficiency, with an aim to reducing overhead.
  • The benefits of improved efficiency could be better resource allocation, increased outbound deliveries, or reduced overheads.
  • The formula for this goal may be “to improve the efficiency of our warehouse by measuring the travel time for products moving between zones, in order to remove blockers and increase throughput.”
  • The business questions used to unpack that formula might be: How many products pass through our warehouse? Which products take the longest time to move from zone A to zone B? Which packers are the slowest? Are there certain days when throughput is low?

With this strategy in place, we know the business questions that can help deliver the formula and that, as a result, we will need data including product hierarchy, the warehouse schedule, the warehouse timesheet, supply chain movements, working hours, and working patterns.

Without a clear data strategy that aligns with overall goals, businesses risk wasting time and resources on data that doesn’t help them achieve their objectives. By aligning the data strategy with their business goals, businesses can ensure they are collecting and using data in a way that supports their larger objectives.

About the Author

Jason Foster is founder and CEO of Cynozure, a data and analytics consultancy, named in the Sunday Times’ top 50 fastest-growing private companies in 2022. He is co-author of "Data Means Business," host of the Hub & Spoken podcast, and on the board of the Data Literacy Academy. Jason was featured in the DataIQ 100 Most Influential People in Data in 2020, 2021, 2022 and 2023. You can contact the author on Twitter.


TDWI Membership

Accelerate Your Projects,
and Your Career

TDWI Members have access to exclusive research reports, publications, communities and training.

Individual, Student, and Team memberships available.