Data Analytics 4 min

Data analytics done right- looking beyond the Big Data obsession

RZW pasfoto 2020
Ruben van der Zwan
CEO & Co-Founder
Data analytics big data obsession chocolate obsession scaled

Data analytics - big data obsession - chocolate obsession.jpegCEO: “I found this cool new analytics tool to monitor customer behavior. Can you integrate it on our data platform?” You: “….”

Sure, you can. You’re CIO of a big company and you can do pretty much everything. The question is not whether you know how to integrate new analytical tools; the question is whether it’s going to get you anywhere. As with many other things, investing in tools is only worthwhile if these tools are well integrated in your business model. I won’t have to tell you how often this fails. So, what needs to happen before you can turn data analytics into ROI? I suggest you start by telling your colleagues to find another obsession.

What’s up with this Big Data obsession?

Many people say data is the new oil. And as is the case with oil, you need a lot of it to put it to great use. When you have a lot of data (hence, Big Data), you have a lot of information you can analyze. This provides you with new information on, for example, customer behavior, production efficiency and pretty much all other things you want to know more about. So far so good. Information is needed to optimize services, products, customer experience and process efficiency, so the more you have, the better. The problem lies in the next steps, as information doesn’t necessarily come with high ROI. The result: you’re stuck with a lot of data and insights and no plan.

1. Set your goals

The first piece of advice I’d like to give you is an often-missed open door: determine your goals! Beforehand, that is. In this article, you can read about a Mexican financial group, who decided to set up an entire business unit for analytics alone. This Analytics Business Unit (ABU) functioned as a profit center and directly communicated with the C-suite. Together, they set goals, deadlines and measurable targets to get the most out of their data analytics. ABUs are nothing new, but the way this company aligned its analytics department with the C-suite is remarkably clever.

2. Involve key stakeholders

Involving the C-suite is a great way of keeping your eyes on the ball. But the support of other business units is equally important. I therefore advise you to start collaborating with the top management and work your way down while working on your credibility. Setting some short-term goals will help you proof the value of your analytics business unit to other departments, and get you the right support. In the best-case scenario, you convince other departments to play a part in your new analytics strategy, which creates important partnerships between players that normally would work independently.

3. Determine how you’re going to measure results

The impact of data analytics in terms of money is not always clear. Therefore, distinguish two types of ROI: the income it generates and the costs it saves. For example, if you use analytical tools to improve customer experience, you may realize a growth in number of customers, which may lead to more revenue. However, when you use analytics to make your production process more efficient, you save out on money. Both examples are great results, but in a completely different way. In both cases, you turned information into profit, so make sure you incorporate both in your evaluation.

4. Communication throughout the entire process

Speaking of evaluations: communicate your results with stakeholders as often as possible. First of all, this helps you get the support of the C-suite throughout the analytics transformation, which you need to execute your plans. Second, sharing results will motivate other departments to join your movement. But most importantly, communicating your results helps you set the right expectations. When colleagues know what you’re analyzing, why and how, chances are high they’ll appreciate the outcomes too. When you don’t communicate and just start analyzing, how will the rest know whether you succeeded or failed?

5. Find your people

We’ve discussed your role in the analytical transformation of your company, and the way you should include internal stakeholders. But what about your own team? To start a analytical movement, software skills are not enough. I therefore suggest you hire IT professionals that know how to deal with colleagues from other business units and see the bigger picture. They don’t have to know everything about your company and sector; they must be fast learners that know how to put targets into action.

Did you notice how I didn’t mentioned Big Data once in this story? To turn data analytics into ROI, you should focus on the way your plans match your business model and whether they’re supported by the rest of the company. So, let go of your data obsession (or if you don’t have one, cure your colleagues) and focus on what’s really important.

Want to know more about the place of data analytics in your digital transformation? Download our white paper Go Digital below.

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