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So, what makes effective data management so critical to a high-functioning finance department? It all comes down to time. And time is money.
When they take a closer look, finance departments are often alarmed to learn they spend a majority of their day managing data.
According to APQC data, more than half of the staff at a typical accounting shop are transactional positions, like accounts payable or accounts receivable. These are data professionals — that becomes obvious when observing their activities and tasks.
Further benchmark data shows companies boasting the best finance teams can be staffed at 20-40% of the bottom performers. These disparities indicate that some finance and accounting departments have figured out how to be good at data.
Besides the obvious cost benefit from data management excellence, any CFO or Controller will point to other key benefits including more time to provide actionable insights and the ability to focus on key initiatives like sustainable working capital reduction.
What is data management?
When the range of data management tasks are listed out, it’s easy to see why they require so much time. From requesting and extracting to interpreting and follow-up, managing your data effectively is a big responsibility.
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What a technology-based solution for data management looks like
There’s good news: A holistic, well-designed and effectively implemented technology solution and system architecture can dramatically improve the effort level, quality and cycle time of any finance team’s data management work. It starts with a commitment from the top to standardize policies and processes where possible. And it includes an organizational commitment to a formal continuous improvement program.
Since finance departments are so data-heavy, their organizational structure often reflects these data management needs. Team members with strong Excel skills are prevalent. They often become the stars, become critical and hold a lot of leverage which can create employee flight risk and drive up labor costs. Many accounts receivable departments are organized by customers because each customer provides unique data structures and challenges. It is not uncommon to see very elaborate spreadsheets built by an individual teammate over many years to deal with unique customer data. These scenarios are not efficient, scalable and are often risky.
There is a preferred order to an impactful data management technology solution:
First, integrate systems where possible to enable the native movement of data. Systems can be integrated through custom coding or prewired solutions such as API’s (Application Programming Interface), web-services or third-party software. Custom interfaces can be cumbersome, fraught with error and difficult to maintain. The mappings are custom alphanumeric data strings sometimes thousands of characters long that won’t work if not perfect. Pre-configured solutions should be considered first.
Next, ETL (Extract, Transform, Load) technology should be considered to map data wherever there are static source and target data files. This technology can also house very detailed, custom data validation rules designed to achieve maximum data integrity.
Then, fully use your ERP (Enterprise Resource Planning) system’s business rules and workflow functionality to handle how data is automatically reviewed for completeness and quality before moving to the next role/user in the process.
Additionally, where double input of data is involved, it may make sense to employ self-serve functionality to eliminate the second input. Supplier invoices are a good example.
Suppliers first input data to create an invoice. They then lock that data in the form of a PDF, send to an accounts payable department that then must reinput the same data. An alternative approach: Have the supplier enter the invoice data into a secure supplier portal and eliminate the need for the second input.
With the proper technology architecture in place, a significant amount of data movement and management should be touch-free. However, it’s inevitable that finance personnel will need to navigate from system to system to grab, request, validate, and input or upload data. A good process automation strategy, complete with high-impact use cases and a suite of automation technology tools centered around RPA (i.e., Robotics Process Automation) can help automate another significant group of data management tasks.
Supplier invoice input, customer invoice creation, and customer receipt applications are common areas that can achieve high levels of data automation but require an automation suite to supplement a proper architecture.
Performance KPI’s, dashboards and a dedicated continuous improvement team are critical to achieving maximized results.
Technology drives a successful process automation campaign. Cognitive OCR helps automate the unlocking, mapping and inputting of locked documents such as PDF’s. RPA mimics the input and systems navigation of a human’s repeatable steps. Historical data stored in a database can be tapped and used by ML (machine learning) and AI (artificial intelligence) to predict outcomes.
The illustration below shows a fully functioning process automation technology suite.
Get started
As with any improvement initiative, getting started and achieving some quick wins are the most important steps. Getting executive support and identifying the highest impact areas with the most chance for success is a logical approach. Alight, along with a suite of Workday Financial Management solutions, can arm you with the tools you need for both short and long-term sustainable success with data management.
