The beginning of Data Strategy, four key lessons

Having worked on data strategy projects for some large and very large enterprises I have encountered many different business contexts for an organization to think strategically about their data. Here are some important considerations that should be made at the outset:

1. Decisions:

It’s about the decisions that you make, both tactically and strategically as you go about your business. The insights will make those decisions better. And you need the data that will generate those insights. The leading organizations understand the decisions they make and they know how an insight will affect that decision so they make sure they measure the outcomes and feed them back into the system.

2. Process:

Build experimentation into the process, use data and experiments to learn what drives your customers to behave in certain ways. Then use those insights to change how you engage with your customers. Data collection should be an intrinsic part of the process. In my opinions, the leading organizations collect data from their customers at every touchpoint, from their business processes at every interface and transaction.

3. Data:

The data will be harder than you think to get hold of, for various reasons – either is was not collected, it is poor quality, it has been archived, it is not in the right format, people get territorial and political, there are privacy regulations. If your product is an insight, then data is your raw material. Make sure that you have a reliable supply of data and start the process to get that as soon as possible. The leading organizations treat their data as a ‘first class citizen’

4. Change:

Organizations generally have business objectives. In successful organizations people are busy focused on those objectives. ‘Big Data’ projects can be huge distractions and they are mandated strategically, yet individuals are measured on their tactical performance measures. So once people leave the strategic workshop, they go back to their business as usual jobs – they will only pay attention to the data project if it helps them. So the successful projects are able to combine a business objective with a data objective and they have mutually dependent success.