CFOs who effectively gather, organize and share increasing volumes of data are better equipped to make decisions than those who don’t – but the gap between those who use technology to harness the power of data, and those that don’t is growing quickly.
Technology is evolving at a dizzying pace, and more and more of what companies do generates data. Even for small businesses, we are constantly told that this data is "gold" or even "the new oil". But the data must first be converted into information that can drive decisions - only then can they really create value for the business.
That task usually falls on the CFO and often comes with some challenges.
In this article we present some of the most common problems with data analytics - and conclude with tips on how they can be resolved.
1. Poor data quality
Data quality problems are nothing new but finance leaders report that data quality can now be considered one of the biggest threats to reputation. According to the IBM 2021 Global C-Suite Study, 70% of leading CFOs say implementing enterprise-wide data standards is a top priority to help their organisations consolidate systems, cut costs, and scale rapidly.
2. Difficulties accessing data
Some IT systems use proprietary data formats or otherwise make it difficult to export data. Skilled consultants can spend hours troubleshooting problems.
3. Data spread across multiple systems
Data is often spread across several systems creating data-silos. As companies add new systems or grow through mergers and acquisitions the problems increases.
4. Too much data
Even if all three prior points are resolved, finance teams can quickly end up in a situation where they have too much data. Ordinary spreadsheets struggle to handle more than about a million lines of data points, and that limit is reached quickly in even smaller companies.
5. Different view of data
Data means different things to different people. Some people will look at the number of units, others are interested in cost per unit. Without the right analytics tools, it takes a lot of time to analyze, calculate and present key figures (KPIs) for various decision-makers.
6. Data visualization
Creating easy-to-understand graphs and charts isn’t as easy as it looks.. The correct view of data can help decision-makers make the right choice, while the wrong view of data can be disastrous.
… And the solution
Data issues can’t be solved overnight, but there are 3 steps to an effective data strategy:
Integrate systems where possible, automate data entry and synch data between systems where possible. Our colleagues at Keyforce integrate CRM and ERP system for example, have years of experience making data flow between systems.
B: Eliminate manual analysis
Spreadsheets have many advantages but also many drawbacks. Where possible, businesses should optimize routines and set up modern systems to organize and report data. This saves finance hours of spreadsheet rustration.
C: Use modern technologies
An effective business intelligence tool gathers financial and non-financial data and automatically organizes it on CFO Dashboards. When business environments are unpredictable, dashboards give finance teams and other key stakeholder live insights into just about any aspect of the businesses. With better visibility, CFOs can better guide their oganisations in both good time and bad.