In part-1 of this series, we discuss why investing in finance talent is critical to drive transformation. Finance leaders must seek to improve their team’s digital literacy of both existing and emerging technologies to optimize processes and data. This may require you to augment your existing finance team with process experts and data scientists.
Data is a crucial component of autonomous finance functions. Hence, improving its quality—completeness, accuracy, consistency, and timeliness—is the next major step in striving toward building an autonomous finance function.
Post finance technology implementations, most CFOs would violently agree on one key challenge – insufficient focus on data. In the middle of a technology deployment, with exuberant monthly burn rates, finance teams find it hard to align on common data governance frameworks and data standards. Subsequently, post go-live, finance teams struggle to democratize access to data under a common framework to enable reliable storytelling and facilitate better, faster decision-making. Agnostic to incremental technology investments, CFOs can allocate time and resources to execute the following steps to improve finance data maturity.
Finance professionals in corporate and local markets need to partner together to prioritize and align on common finance data principles that meet corporate, regional, and local requirements. A common set of principles will enable finance professionals to practice consistency in analyzing and interpreting data at both the summary level and lowest common denominator. A practical data model will reflect the business maturity while providing a pathway to enhance it as the business grows. Even a basic data model can enable finance professionals to shift away from reconciling data among themselves to assessing business options to facilitate decision-making.
Recognizing the alignment to common finance data principles is hard work, especially as it requires stakeholders with different perspectives to come together and agree to a common view. As a result, it is equally important to define and establish a governance framework to maintain the hygiene of the foundational data principles and enable ongoing evolution in a systematic way. The governance frame should establish data owners, decision rights, and data hygiene scorecards to monitor adherence to the principles.
Once the data principles have been agreed upon, it is time to adopt them across the finance function at corporate, regional, and local levels. Don’t underestimate adoption efforts especially if there is a wide gap between the current ways of working and the newly formed data principles. To help ensure each team adheres to common data principles, it is important that key practical activities are prioritized. The successful adoption of foundational data principles is a journey, and data maturity is a multi-year evolution. Don’t forget to celebrate incremental wins.
Read part-3 of this series to know the third element required to build an autonomous finance function.
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