This may be one of your “business resolutions” this year. You’ve decided to raise your data game in 2020.
But how? And where do you start?
So, great idea. (Really! We like it.) But it’s the wrong goal. At some level, your customers (or stakeholders) don’t care a whit about your data prowess – they care about their product or service or benefit. You need to put data to work to improve something, and 19 times out of 20 that will touch a customer. (Yes, there are some “internal only” use cases, but they are fewer and harder to justify.)
What you need is data that will help a customer make the next purchase. Or add-on to the purchase. Or will help you make the next purchase more profitable, so you can reinvest some of that in further improvements. It may be data that lowers your costs. It could be data that reduces fraud. It could be data that prices your product more competitively. Or raises engagement. (Or you might analyze your processes to make them better.)
Those are some of the many things data can do. But it’s not data, exactly. It’s using data to create actions. It’s the actions that matter. And while we’ll talk about data, every data project has an action at the end of it.
We see the job of “putting data to work” as being in one of several distinct categories:
- Data strategy – figuring out what you want to do, how you might do it, and how it will benefit you
- Making High Quality Data Readily Available – You likely have some of the data you need, maybe even partly in the form you need. But if you’re going to act on data, it has to be the right data, and you have to trust it. (Hint: your transaction data is a good starting point, but there’s lots to do to make it good data.) This turns out to be a complex stumbling block some companies never get past.
- BI – Business Intelligence – sometimes the first step is knowing, seeing, measuring, monitoring and reporting. We call this BI generally. It sometimes includes some predicting. But if you’re going to define “how to win” in the strategy – you’ll need to measure how you’re doing. It’s nice to score touchdowns, but you don’t know if you’re winning if you aren’t keeping track or counting them.
- Models and Predictions – This is one of the trickier bits. Typically, you need to have “good data” and your project should be “on strategy.” And you’ll likely want baseline measurements of how you did before and after (that would be the BI piece). The models themselves need to be a) developed, b) tested, c) maybe revised, and d) operationalized. Without d (operationalized), you get no benefit at all. So planning for d is critical. This may include “fancy” AI (Artificial Intelligence) but usually it is more about operationalization than fancy.
- Digital Transformations – while we work with lots of “Digital Transformation” initiatives, the case studies repeatedly tell us the successful digital transformation initiatives are the ones that are strategically important to improving the lives of clients or stakeholder groups. A successful initiative often links or integrates several elements together.
What will be most important to you, will be up to you. But if it’s going to have impact, it will be focused on actions that make someone’s life better.
So let’s raise your data game – by improving something a customer or stakeholder cares about. Call us to talk to us about how we can help, or browse some of our case studies to see how we’ve helped other clients.
