5 keys to data success: Integration

Mik Data Science June 17, 2016

Your strategy is ultimately led by how your company will use your data discoveries.
Your strategy is ultimately led by how your company will use your data discoveries.

Turning data into gold.

We hope you’ve been following along in our “5 Keys to Data Success” series. Starting from data collection we’ve travelled all the way to our final installment: How do I actually make use of all the data and analysis in my business? We hope the series will boost your success and show that while a data strategy involves some important questions, it is something every company can develop.

You might notice questions seem repeated across this series. That is true, in part, because many facets of a sound data strategy face the same tough questions. But more importantly, we’ve hope if you take nothing else away, you’ll take away the need to have a comprehensive goal in mind before you start down the Big Data path. While the specifics be worked out as you go along, having a clear vision of the final goal will save you a lot of money and headaches in the long run.

Sadly, the most frequently forgotten piece of a data strategy is how the results will actually be used to boost your business. Seems like the first question you should ask, right? Turns out, it is not so simple as saying “I want my marketing to be more effective,” or some similar broad goal. While those are good places to start, you want to be sure you dive into some more detail in the data strategy. Here’s 5 questions to help you:

1. Are the insights actionable?

We all want Big Data, but plenty of companies have wasted money on the hype. Do you expect insights to be actionable?
Or are you asking for ways to improve a business process that can’t be altered? Be honest with yourself and consider all the stakeholders.

2. How does my work flow integrate new insights?

You planned an objective for your data, but did you consider how you’d actually put them use? You don’t just want results that are actionable, you want them delivered such that they are easy to act on. Insights that aren’t integrated into your workflow never give good ROI.

3. Who will actually use the results?

Are the results there to support better or additional company reporting? Does an automated software platform need to consume these insights? Or does human action need to start incorporating them? Each of those have their own complexities (especially human action), and their own set of expenses. Keep roles and capabilities in mind, too.

4. What’s the timeline?

Whether it’s making use of time sensitive results, or proving ROI in a reasonable time frame, consider what the timeline needs to be for getting the most out of the data. And then consider how you can reasonably achieve that timeline when setting your strategy.

5. Are my expectations reasonable?

Here it is: the final question. And undoubtedly the most important. Whether it’s the ROI or just how much it will impress your board of directors, make sure you have reasonable expectations. Data mining, machine learning and all of the other great things we have available are not silver bullets for a company. Yes, they can create massive benefit and drive a serious advantage. But data has limitations. Know this ahead of time, and get serious with what you expect and what you promise stakeholders. This makes sure you integrate insights at the optimal point in your business.

Thanks for joining us on this series. Now get started on designing your own data strategy with confidence and turn your company’s data into gold.