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How chief financial officers optimize KPIs with data, automation

  • 2 wk ago

Stewardship of fiscal performance has always been a numbers game; now, big data and automation are allowing financial leaders to take their key performance indicators to a new level.

While the data deluge has created ample opportunity to improve financial KPIs, managing that data and transforming it into actionable insights is proving to be a challenge — an issue explored in a panel discussion at  the 19th annual MIT Sloan CFO Summit.

The challenges are especially acute in companies with a data estate that is spread across different systems and is punctuated by silos, data gaps, and inconsistencies in the type and quality of data stored, chief financial officers agreed.

To fully capitalize on data-driven performance, financial organizations need to start back at step one: Getting enterprise data in order to ensure the right data is captured and that data initiatives are aligned with core fiscal strategy and business goals. Key to that effort is a renewed focus on data governance and working through the question of who owns the data model.

“Before we can even think about getting insights and value out of the data, we [need] a good way of getting that data into our systems and a good way of governing it so that it can be usable for us,” said panel moderator Peter Irwin, a partner at KPMG Lighthouse, which specializes in data analytics, automation, and artificial intelligence.

Here are key takeaways from the discussion:

Finance needs an ownership stake in the data model

The data explosion is a doubled-edged sword. There’s so much potential in leveraging data and advanced analytics to boost fiscal performance, yet without a single source of truth, organizations can be stuck in a cycle of never-ending reconciliations and questionable data integrity that diminishes data’s value to the business.

Historically, the information technology department has had sole responsibility for the data model, but without complete understanding of what’s required for fiscal KPIs, that can lead to a lot of redundant and unproductive work. Aligning goals and responsibilities is central to data governance; as part of that process, finance should have some ownership stake in the data model, along with IT.

“Finance has a deep understanding of the calculations, the sources, and the definitions and mapping” of financial data, said Kae Arima, vice president of finance at Workday, which has an ownership stake in the data model at the provider of cloud-based finance and human resources software.

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