What do CFOs really care about when they modernize their analytics tech stack? Better decision support. Improving reporting capability is part of that, but the larger goal is to build a data foundation the business can use to surface a steady stream of data insights.
During a recent webinar, Achieving Operational Excellence in Financial Reporting, Stephen Ibach, VP of Financial Service Solutions at Incorta, unpacked the requirements for building such a foundation. He was joined by Melinda Albert, IT Leader of Data Analytics at ASP (Advanced Sterilization Products) — a global leader in infection prevention solutions for healthcare and an Incorta customer — who shared insights from her team’s journey to illustrate what companies can achieve with a modern data foundation.
What does this foundation look like? According to Ibach, there are four key characteristics:
- Real-time reporting: The world changes too quickly to run a business solely on monthly and quarterly reporting. Having the capability to see how the business is trending in near real time is absolutely essential in today’s market.
- Transaction-level detail: Aggregated, big picture reporting is no longer enough. Organizations need to be able to drill down into transactional detail to find the patterns driving the trends, and to move into predictive or prescriptive analytics.
- Unified data: Complexity burdens everyone in finance, regardless of role. They’re working with an alphabet soup of complex, siloed systems (ERP, CRM, EPM, HCM, etc.) that generate an enormous amount of disparate data. Then there are internal processes that generate data finance needs for analysis. Being able to bring all this data together, cleansed and readily available for the end user, is a requirement.
- A trusted environment: “Single source of truth” is an overused term and an oversimplification of the goal. The ultimate goal is to build a shared data environment where users can collaborate around trusted data to power incremental analysis across business lines.
ASP used Incorta to build such a foundation.
The company operates in over 60 different countries with each region generating its own reports according to local reporting rules. Prior to Incorta it was very difficult to consolidate the data globally in order to get a clear picture of the business.
ASP’s initial goal was to build a system to see current performance versus forecasts in real time. Executives and line of business leaders would have access to monthly, quarterly, and year-to-date performance, as well as real-time visibility into all of the company’s bookings — the orders that were pending fulfillment and actual recognized revenue.
It was critical to have a central location where all the different business users could drill down and compare bookings across different forecast dimensions — for example, by region, product hierarchy, and ship to country.
To do it, they needed to bring together data from dozens of sources. Most of the company uses SAP, but some entities were set up differently. They also had financial forecasts that were maintained in Excel in order to be able to track revenue recognition according to the rules of different countries. That data also needed to be incorporated into the reporting.
The IT team wanted to ensure that whatever they built would be scalable. It had to easily accommodate new requirements and become more robust and trusted over time.
In about a month, the ASP IT team was able to set all of this up in Incorta. They used our standard connectors to bring in the data from their source systems. No ETL was required and they were able to do all of the development work in-house.
For the financial forecasts in Excel, they were able to take advantage of Incorta’s data lake connection. Users could pop their Excel file into a Windows server and from there it could be ingested into Incorta. Now they had a consolidated data set in Incorta.
They then created three different schemas to construct their data model:
- The core schema, which contains about 18 million rows of data, is used to perform all of the calculations across the different entities.
- On top of that, they created a summary schema which pulls from the information in the core schema but makes the data set a little bit smaller and easier to report out in summary metrics.
- Finally, they created an alias schema with key tables from the core and summary schemas. This serves as a playground for business users to explore, create more dashboards, and find more insights without impacting the schemas that other people are relying on for data and reporting.
ASP achieved their goal of full visibility to all of their bookings, backlog, and recognized revenue. They were able to compare bookings to all the different dimensions of their financial forecast. Drill down capabilities eliminated a lot of manual work trying to figure out how each region got to their number. Teams were able to reallocate that time to using the data to learn how else to improve the business.
Visibility into the details of their backlog of unfulfilled orders turned out to yield unexpected value. Not only could they track performance to forecast in real time, they could examine detail about backlogged orders to understand why each order was being held back. That helped them create prioritized action plans for the operations and customer service teams to reduce the backlog and help them get closer to their forecast.
Working together on the action plans fostered a lot more collaboration between finance and the commercial and operations teams as well, enabling a much broader path forward than ASP had originally envisioned.
According to Ibach, that’s the very definition of operational excellence in financial reporting — fast, easy, and reliable access to actionable insight for decision making, while also establishing successful cross-departmental collaboration for future innovation.
Watch the webinar on demand to get more details about how ASP achieved and exceeded its operational reporting goals.