In this mini episode, Jason talks about how to align your data strategy around the goals of a business through a top-down pyramid approach.
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Data is an incredibly valuable asset but sometimes data experts get carried away implementing systems and models that are not necessarily the best fit. By using this top-down pyramid approach you can connect the goals of a business to a data strategy that is relevant.
[01:00] Top-down thinking to identify the right things to work on
[03:23] How do we know what those goals are
[04:41] How to pick out goals when they aren’t that obvious
[05:59] What the benefits are
[07:00] Putting together a solid use cases
[09:10] How to ask questions that pull the top layers of the pyramid together into a cohesive data strategy
[12:01] A working example using the top-down system
When devising a data strategy, it is crucial to first understand the business goals of the organisation. Data can be used in a variety of ways, so it is important to have a clear idea of how it can help the organisation achieve its objectives. One way to find out the goals of a business is to look for hotspots within the organisation and to look across the business value chain of the organisation and identify where there are problems and opportunities to improve the business.
A retailer, for example, might go through the sort of value chain of ranging products, sourcing those products, pricing those products, putting them through the supply chain, getting them into shops or into online website, marketing those products, looking at the customer experience, and then improving the product, ranging, sourcing, pricing and supply chain based on the things that they may learn. By looking at this value chain you can start to identify where data can play a part in improving some or all of that chain.
Now, once we’ve got our goals sorted, we need to understand what are the benefits, the positive outcome that we can achieve that contributes to us delivering that goal.
Doug Laney in his book Infonomics shares twelve benefits of doing data within your organisation. These range from increasing customer acquisition, to reducing costs of running the business, to bartering for goods and services, to entering new markets, to introducing new business lines.
All of these things are benefits that help us to contribute to the goals that we want to achieve. So identifying what those benefits are, putting a number or at least putting a value statement against those specific, tangible or even intangible benefits helps us to visualise what achieving those goals actually may result in.
In order to come up with data-driven use cases, we can use the following formula that is actionable and measurable: “we want to do x by measuring/tracking/analysing y, in order to do z.”
This formula helps us to identify what data we need in order to take action and measure the impact of that action. So it might be something like, “improving the efficiency of the warehouse by measuring the travel time for products moving between zones, in order to remove blockers and increase the throughput.”
Simply collecting data on its own is not enough. The data must be analysed in order to reveal actionable insights. This is where business questions come in. By asking the right questions, businesses can gain a deep understanding of their data and use it to drive better performance.
The more specific the questions are, the more focused your data strategy can become. What we want to do is pull out the business questions that help us to better understand the things that contribute to and the things that could directly drive the use case that we’ve defined.
Continuing with the warehouse example, some of the business questions that can enable better data management and hence improve performance might include:
Asking these types of questions can help businesses to make more informed decisions about where to focus their efforts in order to achieve the best results.
The really important thing here is that if we had done this the other way around and said, we have a bunch of data like the product hierarchy, warehouse schedule, warehouse timesheets, and thought what can we do with that data? Or let’s put it all in a central data warehouse and do something with it, we wouldn’t necessarily know where the focus should be, and therefore be sure it was lined up with business goals
We wouldn’t know why we need a product hierarchy in a 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 it back to the goals of the organisation.
So a full example of applying top down pyramid thinking data strategy may look like this:
These are business questions that help us to understand and deliver on that use case. And then the data that we might need will be things like the product hierarchy, the warehouse schedule, the warehouse timesheet, supply chain movements, working hours, working patterns.
In order to get the most out of data, businesses need to have a data strategy that aligns with their overall goals. Without a clear data strategy, businesses risk wasting time and resources on data that doesn’t help them achieve their objectives. By aligning their data strategy with their business goals, businesses can ensure that they are collecting and using data in a way that supports their larger objectives.