5 ways for CFOs to better understand their data

It’s no secret that the best companies rely on data to make decisions. It’s also no secret that even for the most data-savvy CFO, there are still some significant challenges associated with achieving data-driven financial planning.

The sheer volume of information can be difficult to analyze in a meaningful way. And Excel, the CFO’s go-to app for ad hoc reports, can be tricky to use, especially given the many man-hours it generally takes to import and standardize the latest numbers.

Rather than tackling the challenges of dynamic financial reporting, many companies feel more comfortable than making an informed decision based on the metrics they’ve gathered. However, this can have even more serious consequences. For example, it will cost small businesses between £ 3 billion and £ 5.75 billion in 2020 if auto-renewal contracts and subscriptions are not properly tracked.

Rather than trying to deal with all of the data or avoiding mention of data altogether, it is important for CFOs to demonstrate what can be possible when data is properly used and understood. Here are five ways for CFOs to make better use of their data.

1. Remove both types of preload

As a CFO, you want to be sure that the numbers you are looking at represent objective truth. However, biased data is widespread in businesses. In a study by KPMG, 74 percent of executives overlooked the findings from the data analysis simply because the results contradicted their own intuition.

Data distortion can be viewed in two ways. First, the data collection can be incorrect. As the CFO, take the time to ensure that the data collection streams are as neutral as possible. What questions do you ask and where does the data come from?

Mixpanel, an analytics company, described how they turned away from 1: 1 interviews to understand their customers’ product usage. Instead, they opted for automated, neutral reporting, identified a target action, and determined what actions were correlated with that action in order to make customer-centric design decisions.

Second, the presentation of data can be skewed. This is more of a human point of view. Of course, people want to please their superiors. Even if you prefer to get hard numbers, employees may be reluctant to come up with something unfavorable or bad. To combat this, make sure that you have cultivated an atmosphere of collaboration and constructive problem-solving.

Bias is a real problem in business. The best financial reporting has no agenda. CFOs should make every effort to ensure that their business intelligence analysts and data analysts do not select sources or draw conclusions that they believe their CFO will like better. It’s impossible to get rid of all prejudice – we are only human, after all – but if you make an effort to reduce it and become aware of its possibility, you can better understand the financial realities of your business.

2. Clean up the data to be reliable

To be trustworthy, the data should be clean. Even a single misplaced comma or accidental null value can render a report completely unusable. More dangerous is that sometimes there is no indication that data was not ready to be used before the report was created, which means companies are making decisions based on inaccurate data.

A 2018 report by The Royal Mail Data Services found that companies believe that bad data costs them about 6 percent of their annual revenue – but that a third of respondents don’t even have an estimate of how much bad data costs.

There are three steps to ensure that the data is clean before use. First, make sure that data collection is set up correctly. If it’s manual, make sure your reps know you value accuracy over speed. If it’s automated, make sure there are reviews in place to stop duplicates or accidental zeros. The more standardized the data collection is at the beginning, the cleaner it becomes for step two.

Next, after you’ve collected and entered the data, do a series of verifications. For example, if one of your streams is email lists, make sure you have accurate lists by checking email addresses. This ensures that the information is maintained reliably and cleanly.

Finally, clean it while it is reported. Most of the data is not reported immediately. CFOs may want to know if it makes sense to increase the Facebook ad spend budget. The data that answer this question may have been collected months or years ago. When retrieving the data for analysis, make sure that the data is free of errors, not duplicated, and not old or out of date.

You can do this by doing reasonable verifications and making sure that all data types are within reasonable limits, such as: B. Highlighting values ​​less than £ 1 or greater than £ 100,000.

3. Automate the collection, cleaning, and analysis

In smaller companies, CFOs are often CDOs as well. A common mistake is to leave automation as a step in expanding the business. The truth is, the sooner the better – especially when you don’t have people or money to delegate, automating what you can to actually make good business decisions is critical.

This helps you understand data through a number of different mechanisms. You will have more time to actually read and understand the reports rather than compiling them. It also reduces human error. After all, it helps your business grow as the data streams increase.

It is possible to generate automated reports in Excel, but it requires a lot of manpower. When an error occurs, it can be difficult to track down. Instead, it makes sense to invest in an FP&A (Financial Planning & Analysis) provider.

DataRails is a great example of a platform that does this well. It helps CFOs examine the data that automation has collected, cleaned up, and stored. This also gives CFOs the flexibility to answer novel questions rather than relying on pre-existing reports.

Are you presenting your quarterly results to the board of directors and a trusted advisor asks you a question about the impact of a potential pivot? When projection models are based on dynamic figures and sophisticated visualizations, they can be updated in your spreadsheet with just a few clicks. This type of on-the-fly conversation is no longer an obstacle and empowering everyone.

4. Free yourself from the desk

Many data solutions are designed so that they are only visible on a desktop. However, it ignores the fact that CFOs often have to make decisions on the go. When CNN surveyed 35 executives to see how they manage their work-life balance, most admitted they always make sure they are available for urgent work matters, including at home or on vacation.

This aspect is often overlooked, but as the world gets smaller and smaller and CFOs rely more on their cell phones to help them out when they are away from their workplaces, it makes sense to make sure your dashboards are mobile friendly.

Work-life balance is a great goal for all workers, including CFOs. The reality, however, is that there is often a time-sensitive issue a CFO can reach when you’re unable to get to your laptop – on vacation or when you’ve gone home in the evening. If your data can’t be viewed on mobile devices, this is only useful part of the time.

This step can be as simple as downloading the Excel app on your phone or consulting mobile options the next time you invest in a data platform. Even if the answer is no, it is good to know beforehand.

The last thing you want is to believe that you can rely on your mobile phone to see the data and find out in the short term that it will be difficult to analyze and very difficult to make decisions based on hold true.

5. Turn down some data

Most organizations have a real hunger for data, and understandably they do. CFOs enjoy discovering the why behind the trends they see, relying on a mixture of intuition and numbers to do so. Especially in this data-driven age where it is not only possible, but actively encouraged, to save as much data as possible in order to store and analyze it, saying no to data cannot be intuitive.

Too much data can bloat the processes CFOs typically have to understand their data. This requires more cleaning, more automation, more capture, more opportunities for human error and bias. There is also a cost associated with storing data.

Instead, it makes sense to work backwards to create streams of data. First, ask what questions are important, then figure out what numbers you need to answer. In this way, you can create the data streams that are most important and important to your business. For example, starting Monday, the CRM platform will ask users what kind of data they want to manage.

Despite the capacity for several different types, it is more important to look for signals and ignore the noise of too much data.

Take control of your finances

These strategies range from practical considerations such as mobile usage to more advanced technical proposals such as automating data reporting. However, they are all interconnected. Data drives business decisions.

As a CFO, being able to understand the data you are looking at, knowing that you can trust it, and letting them know about the decisions that matter most to your business is imperative.

Sadie Williamson is the founder of Williamson Fintech Consulting.

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