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Data analytics is the art of using the data your business already collects to spot trends and patterns that might not be visible to the naked eye, and then make informed decisions. There’s a lot of buzz about data analytics in the news these days, and a lot of misinformation. As a guy who spends a lot of time thinking about data analytics and working up solutions for clients of all sizes, I thought I’d clear up a few of the most common misconceptions.
Data Analytics Myth 1: It’s just for solving complicated problems for big companies, period.
Reality: Most managers can make more confident decisions with the help of analytics.
It’s true that analytics practitioners have a wide variety of tools at the ready to do things such as forecasting, fraud analysis and business experimentation, and that we love it when we can break out our nerdy heavy artillery for big clients with big problems.
Most often, though, what our clients really need – even our big clients — are simple, well-thought-out charts and graphs that match the right data with the right questions in a way that makes the right decision almost impossible to miss for the decision maker – and the people to whom he or she reports.
As an analytics practitioner, I have a few tricks up my sleeve to make sure that I always show my clients the “right” charts and graphs – but those tricks don’t have anything to do with the size of the company asking the questions.
Data Analytics Myth 2: Our organization doesn’t collect enough data.
Reality: If your company has an accounting system – and a few spreadsheets – you’re in the game.
Almost all organizations record their work in an accounting system, an enterprise database or a set of spreadsheets. Once that data has been recorded it can be interpreted – and whether you have ten terabytes of it or only a few thousand lines, as long as it’s the right data for the question you want answered – analytics can help.
Let’s say you’re a small manufacturing company and you want to really know which products are profitable for you and which are not. In your accounting system, you probably already record all of the materials costs that go into making your products, along with all of the employee time that is logged to manufacturing and a record of your sales. From that data alone, an analyst with a basic reporting tool can calculate your profit-per-product – and with a few other statistical tricks, determine what really drives profitability for your products.
The term Big Data itself did originally refer to a very specific set of problems and solutions – when very large companies needed to process terabytes of unstructured information in real time in order to do things such as retail price analysis or real-time social network monitoring. The broader term “data analytics,” though is about approaching business questions in a structured way, using the right metrics to measure the health of a business or to drive a decision.
Data Analytics Myth 3: It’s all about powerful, expensive software.
Reality: Data analytics is more about technique than tools – and you may already own the tools you need to get the job done.
While it’s true that software packages such as SAS, SAP BusinessObjects and Tableau are tools that I love having at my disposal, many clients don’t need that kind of firepower. And without an analyst who knows how to use them, they’d be useless anyway.
When I help a client with a business problem, I need four things:
- A good business question.
- The data it takes to answer that question recorded in spreadsheet or a relational database.
- A tool that can create charts and graphs.
- Knowledge of which technique works best for the problem at hand.
So back to my manufacturing example: All I really need is a data extract from that accounting system, and with a tool such as Excel, I can work up the answer to my client’s questions.
Now, if I have more complicated tools at my disposal – such as a low-cost statistics package or a good reporting tool – I can produce reports and analyses that are easier to refresh and share. But at the end of the day, if I as an analyst have chosen the wrong data and the wrong questions to ponder, the results will be meaningless.
DataClear is a Baton Rouge-based data analytics consulting firm. Contact Us for a free 30-minute consultation and discover how your company can profit from data-driven decision making using tools that won’t break your budget.