The data analysis skills every businessperson needs today

Businesspeople in the 2020s do not need to be data analysts. In fact, data analysis is a whole career in its own right, with significant qualifications, disciplines, and program-knowledge needed to progress in it. But, not least because the time of a fully qualified data analyst is expensive, every businessperson should have at least some data analysis skills, so they can run or manage their businesses effectively.

Let’s take a look at the minimum data analysis skills every businessperson needs today.

Know the right questions to ask.

This might not seem like a data analysis skill – you ask the questions you need to ask, right? But actually, the first principle of data analysis is finding the right questions. They’re your compass directions in the sea of data that is your business. Understanding the right questions to ask is the only way you can guarantee that everything else – your data interrogation, your data interpretation, etc – serves your needs and the needs of your business.

Develop a set of regular questions for your business – how are sales of each product or service doing, month by month. Who’s made what contacts this month? Who’s turned contacts into customers – and who hasn’t? What are your payroll overheads? What activity is generating the most profit, and what is more trouble than its economic worth?

These are just a handful of starting points – your mileage will vary depending on the nature and size of your business. But knowing the questions you need to ask will not only make your data analysis journey profitable, it will define the data analysis skills you most need to make a success of your business.

Data interrogation – master your spreadsheets.

As we mentioned, your business is a sea of data. It generates potentially valuable data every day it’s alive and operating. Depending on its size and complexity, you might have financial data in Excel, sales, lead, and contact data in Salesforce, project data in Hubspot, payroll data on a linked app, and more.

While no-one will necessarily expect you to be able to statistically predict sales trends for particular products to within 3% based on previous sales, you should at least be able to discover what your previous sales are.

That means, for instance, being able to master the Sort, Filter, and Pivot Table functions in Excel. Those are skills that will allow you to pull the data you need out of your whole mass of sales data. Whether you’re looking to deliver sales reports, month-by-month or quarter-by-quarter profit analyses, or any other specific combination of data points, knowing your way around your spreadsheet, and its Sort, Filter, and Pivot Table functions will help you create the reports you need fast, allowing you to spend the rest of our day doing what you do best – running your business.

Data interpretation.

How confident are you that you understand the results your systems are showing you?

If, say, you sold 25,000 lug nuts in December, and when you run a query on your January numbers, the system tells you you suddenly sold 75,000, do you trust it blindly? Interpreting data depends on being able to backtrack the context of the data with which you’re presented.

That means being able to run advanced queries on your systems, so you can build the chain of data that connects cause and effect. Again, your systems will contain all the data that defines every aspect of your business, including, for instance, any sales surge that triples your lug nut profit. You should be able to interrogate whichever system you’re using so that everything you need makes contextual sense on its journey from the past to the present.

Whether that’s building advanced pivot table queries in Excel, showing the first orders of a big new lug nut customer in Salesforce, or anything else that might explain anomalous data, be aware of the context of your business from month to month, and invest the time in higher-level query techniques, like those advanced pivot table queries, so that you can a) understand when data from simple queries doesn’t look “right,” and b) have the skills at your fingertips to provide the context that explains why something doesn’t look right, and correct it as necessary.

It’s possible that might involve a cash investment too, in professional training to master those more complex queries. While, depending on the size of your business, that might feel like an unnecessary expense, any training that allows you to boost your data analysis and contextual interpretation skills will repay your investment every month after you pay it out, by putting you in control of your data.

Data visualization.

Sometimes, it’s not enough to analyze your data for your own benefit. Sometimes, you need to be able to render the data in simple, visual ways for presentation to team leaders or staff in general.

Using, for instance, the Charts facility in Excel, will let you turn most data – either native or imported from other programs – into easy-to-label, easy-to-understand visuals, that can communicate the data you need to share in seconds, rather than having to explain it at length.

Again, your program mileage may vary, but if you have a spreadsheet program of any kind, the chances are there will be a simple option to transfer data into graphics, and they can be a hugely effective way of getting a message across, whether it’s celebratory (you really did sell 75,000 lug nuts last month!) or concerning (your sales team fell behind their targets for the last three months).

By knowing the right questions to ask, mastering your spreadsheet and its data-wrangling functions, investing in an understanding of your systems’ contextual data-paths (even to the point of getting trained to that higher level), and learning how to use the usually-simple graphical functions on your programs to turn data into simple charts, you’ll develop the data analysis skills that ever businessperson needs to run a business successfully in the 2020s.