Data – it’s something everyone is hearing about these days, whether it’s IBM stating how twitter can help you build better products to Google talking about self driving cars saving the environment through the power of data-driven route optimization.
That’s all well and good, but when you’re sitting at your desk looking at the list of things you have to accomplish today, and bring about new ways to grow revenues or build efficiencies into your business, where does one even begin?
No, you don’t always need a small army of data ninjas (though that can sometimes help) nor do you need a lot of high priced tools and solutions to help find buried gold in your troves of silo’ed business data.
To really drive to change, and begin leveraging your data to drive revenue it starts with the following steps
A) Start with the right hypothesis
If you don’t know what questions you’re trying to ask, then it’ll be very hard to find what you’re looking for that’ll help you achieve your business objectives. Asking questions like “where should I sell my goods” or “what products should I build” would require very expensive, intelligent systems capable of translating english into problems that computers could try and solve along with the tribal knowledge and understanding of the industry you’re in. Those systems exist, but man are they expensive along with the IBM consultants you’d need to hire to go between you and the outcomes.
Instead, focus on a specific question based on the types of data you know your business has. Start with things you think you know about your business, like what your key demographic is or where you source your raw materials from. Then go deeper and ask why those folks are your core demographics, or why you went to that one country for zinc. Good data mining starts with understanding the problem space better, and exploring things at a granular enough level that you can understand where intuition, guessing, or laziness came into place vs finding the right outcomes at the right level. You tell me you sell products in Seattle to women 44-55 years of age, I’ll ask what neighborhoods is that least or most true and if that answer is biasing you from growing your customer base because you’re focusing on metropolitan areas from a broad national study you paid a firm to do 5 years ago.
Sure, the same answer might be true, but having those metrics and answers in place means you’ll be able to see the shift and know when those answers are no longer the case, more importantly it’ll cause you to ask why the answers are they way they are and those levers or foundational factors will become more obvious and allow you to get granular enough to spot the outliers biasing your answers which get lost in the high level aggregated dashboards most execs use today.
B) Understand where your data lives
If you live and die by your profit and loss statements, or your quarter earnings reports, chances are that there is a complicated network of data analysts and administrators that compile all that information together to come out with a single answer. If you are getting your core business metrics from the same group you’re measuring against outcomes, be careful about unintentionally biased data that leans on rounding up vs rounding down and know where that data is coming from.
Too much data exists today, and decisions get made by people along the way on how that data is compiled and delivered, so build a culture of transparency and make sure you don’t have data points stacked on top of data points where errors can slowly creep in.
Aside from transparency, agile systems built the right way means you can do ad hoc reporting and build your own metrics with the ability to drill up and down without having to wait weeks for someone to compile a report on only the question you asked. Too much legacy infrastructure, and data scattered across the company along with an over reliance on key information being locked away in spreadsheets means a mess for really getting down to the bottom of things.
C) Figure out how the data is (or is not) related
If you’d like to see how twitter is affecting your supply chain, spend a little time thinking about how the two inter-relate. Twitter is going to be something tagged by date and location at a high level, but is a bunch of key words and a user name so prepare to invest in interpretive systems that aggregate and analyze or figure out ways twitter data might tie to a critical business system. There’s lots of ways to get at the answer, but high quality dashboards with pretty graphics may be just interesting and not at all useful if you don’t have the right data behind that tool giving you meaningful answers. It’s not about big data, it’s about meaningful data.
D) Ask an expert (whether or not you intent to hire one)
Data, like engineering or medicine, is a very complicated space that gets increasingly complicated by the day. Rather than becoming a data scientist yourself, find someone you know and trust that works with data and use them as a sounding board to run your ideas and suggestions by. It’s not that you may have a bad idea on how to leverage data to achieve business insights, but having it structured in the right way while learning what’s possible and what isn’t without a lot of investment is important to finding meaningful, bite sized ways to leverage data without breaking the budget and overspending for fancy whiz bang data systems.
E) Start small, grow big, track and measure along the way
The most important thing is to not bite off a big problem, like how do you end world hunger, but something small you know you could get good insights around relatively easily, such as where you spent what and how that goes against what you make with the ability to drill down into where that changes. If you typically get profit and loss statements saying you’re profitable in washington state, understand what city that is and is not the case and why one would be different than the other. Sometimes it’s just getting more granular data to what you already receive that can have the biggest insights into your day to day business.
At the end of the day, data isn’t a silver bullet, but it can make a difference in a big way when approached the right way. Start small, build a meaningful hypothesis, and strap in for the revenue growth that will follow.
Daniel Maycock is the Director of Strategy and Analytics at Transform, a data services
company. Our mission is to help drive impactful outcomes with data for our clients. We do this by providing tailored solutions that help people get tangible applications from their information.
His new book, Building The Expo, was published in January, 2015.