Many accounting firm owners we speak with have the misconception that data analytics and similar technology are reserved only for larger companies—the massive management consulting firms with offices in every country and ten-figure annual revenue.
The reality is that anyone can take advantage of sophisticated data management and analysis tools thanks to new software that makes these practices more accessible.
Below are a few tips from us on how to incorporate data-driven decision-making without getting bogged down in complicated technology that creates a roadblock to implementation.
Before you can make data-driven decisions, you have to make choices about where specifically you want to use data analytics in your business.
The most common examples are sales, client performance, marketing campaigns, and project management. Modern technology and internet access have brought us applications for data analytics across the entire accounting firm. If you’re new to these approaches, you shouldn’t try to do everything at once.
Here are a few examples of how you might define a scope for data-driven decision-making in your firm:
Of course, these are just a few broad starting points. With creativity and the right sources, you can make data-driven decisions about almost any business area.
While data-driven decision-making is important as a tenet of your firm’s strategy, it also shouldn’t be the only method by which you make decisions. The cutting-edge nature of data analytics technology makes it easy to get away from the human elements of decision-making. This is especially true of decisions that involve hiring, terminating, and managing people at your firm.
There is always some variability when you incorporate the human element—sometimes, data alone won’t tell you if a new candidate will work out, for example, or if a new sales campaign is actually resonating with prospects.
The best leaders in business see all factors and then make decisions. On the other hand, shortsighted leaders tend to base their decision-making too much on quantitative data or go too far the other way and lean too much on their instincts and gut feelings. Analyzing data patterns in areas of your firm, such as sales, employee productivity, and project efficiency, can provide a lot of information about your business, but it’s not the whole story.
Computers and apps are more sophisticated than ever—the smartphones we hold in our pockets today have more computing power than all the systems used to land Apollo 11 on the moon in 1969.
As powerful as they may be, these software and hardware tools are only as useful as the information we put into them. There’s a popular phrase in the computing world to describe this concept: “Garbage in, garbage out.” All the trends and patterns identified by data analytics technology won’t be very useful to your firm if data isn’t coming from the right source.
For example, tracking an increase in quarterly revenue might be beneficial in showing the firm’s bottom-line growth. But revenue alone may not show the whole story if it took an abnormal effort from your team to achieve that growth. Remember to provide your data models with the right source material, and always try to give context to the patterns they create.
One of the big reasons that data analytics and modeling have become so popular over the last few years across various industries is that new software tools have made them more accessible than ever before. There are all sorts of options for data analytics software, from mainstream offerings from the biggest players like Microsoft and Google to more niche solutions from smaller providers.
The technological challenges involved with data analytics have shifted—the issue now isn’t access to the tools but choosing the right one. For example, if you plan to use data analysis on anything involving clients, you’ll need to ensure that your software tool has an extra level of security. If your firm has any kind of plans for growth, you’ll need an option that gives you the ability to scale up the number of resources you have available. The same goes for hiring more team members, as most modern platforms will give you a limit on the number of users (or seats) that you can have before you’re required to upgrade to a higher level of service.
As you’re working on implementing the right data analytics platforms, you should also incorporate a firm-wide practice management solution that integrates with the tools you use for data-driven decision-making. Just like data analysis, accounting practice management software will help you tie everything together and get a more holistic sense of how your bookkeeping firm is performing.
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