Data management has become a major pain point for organizations around the globe. In financial planning & analysis (FP&A), a sector dominated by numerous regulations, the stakes are even higher. Privacy and security need to be balanced against the quality of the insights derived from the data. Digital tools need to be balanced against the willingness of the staff to engage. To master best practices, you need to go a step beyond the standard advice.
Take Stock
The first best practice starts with an accurate assessment of your current data management strategies:
- What data are you collecting?
- How are you organizing data?
- Who has access to the information?
- What are your top goals?
- How secure is your most sensitive data?
- Does your staff know how to read the data?
- Do you trust what the data tells you?
- How well do you utilize your current data management tools?
These aren’t necessarily straightforward questions, and they certainly don’t yield straightforward answers. If you want to make changes, you need to first prioritize your goals. While the answers vary from company to company, most FP&A leaders want to leverage data management to improve the quality of their rolling forecasts. If your data integrity and reliability are strong enough, it’s easier to keep up with fluctuating markets.
Standardize Data Management
If your data is currently stored across multiple spreadsheets, programs, hard drives, and folders, it’s time to standardize its management. This is the time to address inconsistencies, standardize formatting, and define ownership. There should also be a monitoring system in place that can catch issues before they spiral out of control.
As you run through the process, now is the time to consider whether the staff understands the policies. Data literacy has different definitions depending on the individual’s position, but everyone should have a solid idea of how data quality principles govern the process. You should ideally be consulting with other departments to see how their processes either help or hurt data management.
Investigate the Tools
Investing in data management tools is a huge decision for any company. It impacts not just how data is managed but how the staff relates to it (and sometimes even to one another). There are numerous options on the market, all of which seem to promise impenetrable security and endless functionality.
For instance, if you want to improve an analytical model, you can test the scenario before making a blanket change. If you need to aggregate your data, integration tools can pull from marketing platforms, ERPs, etc., so everything can be scrubbed and organized in one place. If you want to improve forecasting, there’s endless prediction software on the market.
Of course, the reality is more complicated than that. Not all data management tools are created equal, to say nothing of a staff’s reluctance to change their routines for the sake of new technology that may or may not go the distance. Doing your homework doesn’t mean testing every last product and feature, but it may mean putting in more time at the beginning so there’s less hassle on the other side. You need to consider not just how different software performs during a demo but also how it will mesh with your company’s needs both now and down the line.
If you’re wondering where exactly artificial intelligence and automation fit into the latest technology, the answer depends on what you need from your data management. As a general rule, though, automation can eliminate not just rote tasks but also the errors and inconsistencies that stem from some of the more mundane responsibilities of the team. AI and intelligent automation can be used to alert a team member when human intervention is needed.
AI also has the ability to make suggestions, whether that’s how to organize data or how to improve your predictions. While some industries, especially insurance, are still leery of the accuracy of these insights, there are few decision-makers who aren’t at least testing the water with what artificial intelligence can do for them.
Prioritize Ongoing Improvements
Technology, regulations, and hackers alike are all evolving. Every time there’s something new on the horizon, whether it’s a bug in a software program or a government decree, data management policies may need to shift alongside the headlines. If you don’t have someone keeping up with it all, odds are you’ll run into a problem (and not necessarily during an internal audit).
To reduce the onus on your end, the right software provider can help you keep pace with changes in data management. A reputable company can update its software to meet or exceed the latest laws. Even when the language is vague, you can rest assured that your data is under proverbial lock and key. However, it’s important not to become too dependent on technology. You’ll still need employees to oversee the performance of your tools and make adjustments as needed.
Stretch Your Analytics
Data management and analytics are strongly linked, but unfortunately, that connection isn’t always clear to everyone. The drivers behind the KPIs, whether that’s revenue growth, cash conversion, or customer acquisition cost, maybe more obvious to an FP&A team than it is to the rest of the organization.
Once your data management policies have a clear focus, consider how self-service analytics tools can empower other departments to study what’s behind the success (or failure) of different initiatives. For instance, a marketing executive may be able to spot a few holes in the analysis, which can lead to better data models for the FP&A team.
The best practices for data management can be adapted to you and your team. However, whether you’re collecting megabytes or terabytes, the reality is that the habits of everyone do matter to your bottom line. If you want to implement a better culture, it usually starts with asking yourself some very basic questions and really going into detail on the answers. From there, you can start to unravel what you need and who to partner with.
