Mastering Your Data

By December 1, 2022No Comments

Data accessibility and availability is at the core of all finance technology transformation.

By Nilly Essaides

Many finance organizations are fast-tracking automation initiatives, aiming to improve process efficiency and build new capabilities to support an increasingly strategic role. The pressure to reduce process cost and head count is intensifying alongside concerns about a global recession.

  • “We are speeding up our digital transformation,” said a member of NeuGroup for Tech Treasurers at the annual meeting at Carmel Valley Ranch. “I just received my budget for treasury for next year, and it’s going to be flat,” she said. “Yet I am expected to do more. That’s speeding up our demand for automation.”
  • “In a tight labor market, automation is going to play a critical role,” said Tom Joyce, head of capital markets strategy at MUFG, which sponsored the meeting. “CapEx is overall going down, but the one place we see it holding up is in R&D and technology.”

Breaking data silos. New technologies can reduce cost and deliver new capabilities. However, absent access to enterprise-wide “blessed” data, they cannot produce the insights companies need to make financial and business decisions.

  • Finance is a huge consumer and producer of data, and even within the function it often stores information in disparate systems.
  • Barriers to the flow of data are even taller as finance increasingly needs insight into operational information. An October NeuGroup survey of 30 FP&A executives showed the majority have either adopted or are planning to adopt integrated business planning practices.
  • Meanwhile, treasury teams are frequently frustrated with the difficulty of pulling AP and AR information, as well as inventory in order to optimize working capital. “Working capital is an end-to-end process, and it makes sense for treasury to orchestrate it, although often it is not the process owner,” said one treasurer.

Building bridges. The good news is that technologies like robotic process automation (RPA) and APIs are facilitating the process of creating a data lake that includes different types of data, e.g., financial, customers, supplier and operational.

  • “What we need is a single source of the truth,” noted a member of NeuGroup for Mega-Cap Heads of FP&A. “Right now, data is dispersed throughout the organization.”
  • Another member said, “As part of our digital transformation project, we are building a data lake that will host enterprise data and support multiple applications.” The source systems feed that data lake via flexible “pipes” that can be easily reconfigured.
  • A third FP&A executive said, “We have over 500 robots that, among other activities, fetch data from different systems and push it into the data lake.” Planning, analytics tools or TMS “sit” above the lake, and pull the information they require.

Data governance. One source of data is only as good as the data within it. While IT has an important role to play, because finance uses and generates critical data, it often owns or influences data definitions and governance.

  • In a survey conducted at the start of 2022, 49% of treasurers reported that finance is piloting master data management (MDM) solutions. Seventeen percent said they have implemented MDM tools at scale. Looking forward 12-24 months, the pilot projects are destined to expand to full-scale adoption.
  • On the path toward a comprehensive view of data, “data governance is an essential step,” one FP&A executive said. A recent NeuGroup survey revealed that FP&A organizations at the highest level of maturity are 27% more likely to own MDM compared to peers.

Filtering out the noise. Having all data in one place can have one potential drawback: data overload. With so much information, how can finance ensure it pulls only relevant data points?

  • “Our company has a data lake,” said the treasurer of a large technology company, “so treasury and other functions can draw on the same data.” Finance relies on machine learning algorithms to curate and digest the information it requires, for example to improve the accuracy of the cash forecast.
  • “You need to understand the data in order to use it to make decisions; otherwise, it can be overwhelming,” said a member of NeuGroup for European Treasury at a recent meeting in Geneva.
Justin Jones

Author Justin Jones

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