Every business decision can be backed up by "data evidence"

By Miran Varga, 12.10.2017.
IKT Informator
Translated into English

We have sat down with Hana Kvartová, country manager in SAS Central Europe and Adriatics, the company that has »the power to know«. She shared with us how simply better decision making can grow on what some people just see as raw data.

What is being data-driven all about?

The goal of having superior analytics is having superior insights. Data-driven organizations process and use ever more data to improve and speed up their decision-making. In data-driven organisations, decisions that aren’t supported by data, are considered suspicious. Smarter analytics technologies now enable every company to become more data-driven.

So there will be no "gut feeling decision making" anymore?

Gut feeling is not good enough anymore to differentiate yourself from your competitors. To be truly competitive, you will need data, and lots of it. Luckily, any organization can set out on the journey to become data-driven. You no longer need to be a data scientist to work with data. ‘Citizen’ data  scientists are not your professional statistician or trained analyst , nor your maths wizard or computer scientist, but rather regular business users who create and use advanced analytical models.
As consultancy firm McKinsey says: “Businesses no longer have to go on gut instinct; they can use data and analytics to make faster decisions and more accurate forecasts supported by a mountain of evidence.”

Can every company become data driven? Or are there some obvious obstacles that prevent them from doing so?

Sure, there are still a few hurdles to overcome. But I believe that technological advancements bring data analytics within reach of an increasing number of organizations. Experts are quick to point out four major challenges. Two have to do with data and two with IT environment. Unstructured data - the data that is not predefined or does not fit the mold of traditional data models - is hard to analyze for traditional analytics programs, although it contains valuable information. And there is the question of data quality: sometimes, the data simply isn’t good enough. It is hard to get good business intelligence from poor – or plain wrong – data.

As for the IT part unconnected systems are proving difficult: organizations often use multiple information storage systems side by side with no or difficult connections between them. These systems may even offer conflicting information because they use different sources, processing methods or naming conventions. Also an overreliance on IT for data analytics complicates IT’s workload. IT is under pressure to keep delivering more at lower costs anyway, and your data analytics requests may end up on the bottom of their list.

So where should companies start their data-driven journey?

Anywhere is good, as long as it isn’t everywhere. A ‘big bang’ approach is risky: it can overcomplicate things or may simply lack focus. We recommend a step-by-step approach as the surest way forward to success. Choose a logical starting point first. This can be a team (e.g. the marketing department) or a specific data source. Consider collecting data from your CRM system to get a better insight in customer behavior, or begin with productivity data from the manufacturing floor. Recorded customer service calls or data from your finance department could equally be your first project. It is best if your starting point is something you’re already familiar with, and if you have a clear goal in mind.

After that you should make a distinction between must-have data sets that will work towards your goal and nice-to-have data sets that are only loosely related.  At first, these data will likely be a mix of structured, semi-structured and unstructured data. Look at what your analytics platform comes up with and whether the results are actionable. Consider if additional data management (e.g. data cleaning) is needed or whether you can already continue using the current data sets.

What comes next?

You should be aware that being data-driven is not an end-state. It’s the beginning of an exploration of exciting possibilities. As the pace of technology innovation keeps accelerating, yesterday’s science fiction becomes today’s reality. The data-driven organization of the future will be fueled by more quality data, IoT and other edge technologies.

Such as?

Such as beacon technology that can track consumers’ in-store behavior and pair it with the right kind of offer bundles to attract attention and capture the needs of the individual. This effectively creates the segment of one. We will see also a wealth of data generated by IoT-capable machines - your production lines could map out ways to become even more productive, discover hidden costs and unlikely sources of revenue. The Industrial Internet of Things (IIoT) will revolutionize the production floor. And it’s just around the corner.