Here Are The Benefits of Data-Driven Decision Making
Fledgling businesses tend to be agile, and are highly likely to experiment with multiple growth paths. Larger, well-established companies on the other hand find it difficult to adopt new or unfamiliar strategies. As a result, their smaller, nimbler, more adventurous counterparts make far more consequential business decisions than they do.
For a lot of entrepreneurs, their decisions are driven by their gut instincts, not by data. It's fine to rely on instinct when your company's just getting off the ground, and its core agenda is being conceptualised. In the long run however, such an approach narrows your horizons and compromises your ability to spot potential market opportunities.
How to Make Good Use of Data
The best ideas are the ones that come from your gut, but when you start making more tactical decisions within your business then data always helps. A couple of examples illustrate this best.
Take marketing. What kind of marketing creative works best with your audience? In the digital ad space, my company uses images of actual people rather than animated images. Now everyone has their own opinions about what will or won't work, but having the ability to test different strategies to see what's truly effective, gives you greater confidence in the choices you make than when you rely purely on your gut instincts.
There's a lot more data available now than there was 10 years ago (and definitely 20 years ago) and until very recently businesses performed analytics on data that they got from their own data bases. Now there's a lot of internal data bases available, so an entrepreneur not only has to look at internal company-specific data, but also external data, and have the skills to analyse/mine it for insights.
As we strive to stay ahead of the curve in an increasingly data-driven world, we must remain mindful of our rivals who (like us) are utilising data analytics to grow their businesses. We must continue do the same in order to maintain our competitive edge.
Incorporating Data Analytics into Decision-Making Processes: Some Caveats
If you want to be data-driven, then you have to be data-driven in everything that you do. You can't pick and choose, you can't say "oh, here I'll rely on data, but here I won't.' Look at businesses like Amazon, where even the smallest decisions are data-based. I once worked at a company where even the colour of the walls was decided by data. So that is the type of approach to take if you want to take a data-driven approach.
Secondly, when she's just starting out, an entrepreneur has to rely quite heavily on her gut, simply because a) there isn't much internal, company-specific information available at that time and b) even when it starts becoming available, and your business starts generating information, there still isn't enough data for you to be able to make out general trends and patterns from that data. Things at this stage are moving so rapidly, and are in such great flux, that you can't even rely on data that's all of two-months old.
That's because two months ago you were doing vastly different things than what you're doing now. At an early stage businesses change so rapidly that something that happened three months ago, won't be relevant to you right now. Whereas in a mature business you can go back 12 months, 24 months, 36 months and get good data & insights
Facts (Data) vs. Opinions
When it comes to making decisions, people have their own distinct suggestions. The more time they spend at a job, the more opinionated they become. In such situations, I take my cue from James Barksdale, former CEO of Netscape, who famously said "If we have data, let's look at data. If all we have are opinions, let's go with mine." To put it succinctly, I'm the CEO. Opinions are essential, and as your employees become more mature at their jobs, they will definitely form them. Without the numbers to back them up however, those opinions are suppositions, not actionable data-based insights.
Data Curation Should Become a Habit
Entrepreneurs should focus on building robust data-collection processes within their organisations from the get-go. If they don't do this from the start, they won't amass enough data, and if they don't have sufficient data to analyse they won't be able to extract useful insights; they will be left feeling like their company has no use for data.
However, if they methodically collected data from the start, they'd soon have enough to work with. They'd start analysing it to gain insights; the more useful those insights proved, the more they would start believing in the power of analytics, and the more likely they would be to use it.
It's a cycle; if you don't invest (in data), you won't be able to enjoy the returns (insights), and you will become even less likely to consider it in the future. If you DO invest, you will see its value, and you will focus more on it.
Tying Business Decisions to Analytics Insights
Entrepreneurs must open their eyes to data's boundless possibilities. When they actually delve into the data start analysing, they realise that there are at least 20 different approaches they can take. A lot of the time, young organisations spend a lot of time mining data, but end up with no useful insights. That's because they don't have a fixed end goal in mind prior to starting data collection and analysis.
So, one good rule of thumb is to always have a clear analytical objective. What is it you want to achieve? Do you a) want to assess an opportunity or b) diagnose a particular business problem? The more clarity you have with respect to your end objective, the more focussed and rewarding your analysis will be. On the other hand, the more ambiguous your objective, the less focussed your analysis and the less likely it is to yield good insights.