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It’s Time For CFOs To Get Comfortable With Advanced Data Analytics

Data analytics have long been employed by CFOs and finance organizations to help manage familiar finance and accounting activities. But digital transformation and changing markets, call for new approaches focused on more advanced data analytics.

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Insolvency

Source: Forbes.com / Jim DeLoach

Comment: The role of a CFO has changed dramatically in recent years – it is not just about presenting the Accounts or Numbers. There is a necessity for CFO’s to now be analytical and understand and interpret the numbers even more so than preparing and presenting them.

Data analytics have long been employed by CFOs and finance organizations to help manage familiar finance and accounting activities. But digital transformation and changing markets, together with rising expectations from boards and executive management, call for new approaches focused on more advanced data analytics. And because these approaches may involve CFOs and their finance teams breaking new ground on the data analytics front, it’s also time for them to become comfortable being uncomfortable.

It’s time to embrace advanced data analytics.

The need for and use of advanced data analytics have been gaining traction for a while, though the past year certainly served as an accelerant in their use. CFOs deploying data analytics to fuel their company’s resiliency and superior performance during the Covid-19-driven downturn have demonstrated two distinguishing characteristics.

First, they have an abundance of advanced supply chain analytics on hand—insights that enable their companies to pivot to alternative markets and suppliers in response to sudden business and market shifts. Supply chain leaders continue to seek cost, efficiency and profitability analyses associated with various sourcing scenarios they may need to enact if other potential disruption risks become a reality.

Second, their smart phones and, more important, access to critical data always remain within reach. Regardless of the time of day or their location, these CFOs remain connected to the systems and data they need to keep real-time tabs on invoices, accounts receivable, working capital and other traditional metrics, along with an expanding portfolio of enhanced analytics on products, services, marketplace trends and conditions, and other forward-looking value drivers.

Throughout the historic disruptions of the past year, these CFOs helped their organizations remain in lockstep with suppliers and third-party logistics providers, churn through dozens of alternative-sourcing scenarios, restock depleted store and warehouse shelves, transform production lines to manufacture in-demand goods such as surgical masks and ventilators, reshuffle B2B-to-B2C rations, provide sharp visibility into customer master data, and more.
In recent years, a drumbeat of research has highlighted the need for finance functions to develop and integrate advanced data analytics into their increasingly digital operating models. Without question, the global pandemic delivered unequivocal proof of this need and its many payoffs, accelerating the transition.

Satisfying Internal Customers and Rising Expectations for Real-Time Metrics

Traditionally, the finance function’s data analytics activities have centered on tactical finance and accounting processes. These analyses and metrics tend to focus on the speed, cost and other performance attributes (and opportunities) tied to order-to-cash, procure-to-pay and record-to-report cycles. Finance teams routinely harness these analytics to help accelerate cycle times, lower costs, and improve the performance of finance activities as well as related processes that extend beyond the finance organization.

In addition, most long-established finance analytics are retrospective in that they focus on historical data and past performance. Analyses of time, cost and quality performance metrics on last quarter’s cycles and processes shed light on ways to improve those activities in the future. Now, though, as organizations operate in an increasingly digital manner and as data inside and outside the organization becomes more accessible, boards and CEOs are challenging CFOs to report real-time information. More importantly, finance is being challenged to expand the scope of that timely reporting beyond the boundaries of traditional finance processes to the end-to-end customer value chain, business development, strategic planning and other realms.

The CFO’s reports for the board now require deeper dives into finance data, often at a regional or specific customer segment level. Meeting on-demand drill-down reporting expectations like this requires finance teams to access and examine larger, more varied data sets in real time.

In addition, human resources, sales, supply chain, operating divisions and other longstanding internal customers seek more precise and timely insights from finance leaders. And newer customers within the organization are equally hungry for enhanced finance analytics. Strategy officers, for example, want real-time insights into sales by geography, product type and other cuts—as well as assessments of risks based on external data related to numerous forms of marketplace variability and volatility.

Three Ways to Enhance Analytics

Accessing and analyzing large, expanding sets of internal and external data in an accurate and sufficiently controlled manner is a substantial challenge. This difficulty, combined with the strategic nature of the decision-making processes that the finance organization’s enhanced data analytics support, helps explain why most CFOs prefer to keep this capability in-house and manage it in a centralized manner (e.g., via a center of excellence).

While that structure can lay the groundwork for enhanced analytics success, several other steps can also help CFOs and their finance organizations get a leg up on their advanced analytics efforts. These include:

Get comfortable with data discomfort: CFOs are wired to fulfill the tenet of accurate reporting at the core of their mission. This need tends to nudge finance executives toward using data sets that they know like the back of their hands – and analyses that they have grown comfortable performing over time. But the data sets that produce the advanced analytics more finance customers are requesting represent larger ones by factors of 10, 20 or more that expand continually, thanks to digitalization’s onward march. This data fluidity can be difficult for the control-and-accuracy side of the CFO’s traditional mindset to accept. Fortunately, the reluctance to plunge into larger data lakes can be overcome by bringing into the finance organization and/or center of excellence the right skills, technology tools and governance structures.

Promote and leverage data governance: Effective data governance is an enterprise-level strategy and capability that establishes methods to ensure control and oversight of the use of organizational data. While data governance is not the CFO’s responsibility, the finance group has a stake in helping to ensure a mature data governance program is in place and adheres to applicable data governance policies and processes. In doing so, the CFO and finance organization can trust the data used in its analyses, as well as the controls ensuring the security, quality and integrity of the enterprise’s data usage, storage, sharing and reporting.

Always look to close the skills gap: Although it often feels like a Sisyphean pursuit, CFOs must continue to develop innovative solutions to address the digital skills gaps within their groups and their organization as a whole. This never-ending effort requires consideration of a range of skills-sourcing mechanisms, the funding of retraining and upskilling programs, and the rethinking of hiring profiles and even deployment of a more flexible labour model.

Enhancing the finance organization’s advanced analytics competencies also requires a nuanced understanding of what comprises those skill sets. Inside finance, digital proficiency should focus more on forward-looking perspectives than on historical reporting. This requires a comprehensive understanding of where data sits throughout the organization, which demands deep knowledge of the business and the challenges faced by key internal and external stakeholders, as well as strong coordination with the IT organization. Core financial planning and analysis skills are a must, and they should be paired with fluency in advanced technologies, such as artificial intelligence and automation in all of its forms, along with the ability to continually improve the analytics the finance organization designs and delivers.

CFOs must recognize that continual advancements in their analytics capabilities are now table stakes for the board of directors, CEOs, their executive management peers and the many internal customers within their organizations. Our experience indicates that boards and executive teams are committed to investing significant amounts of money in advanced data analytics, especially now that they are well-equipped with vivid, pandemic-era illustrations of the resiliency and other returns these investments generate. It’s time for CFOs to step up and get comfortable with a new era in finance for advanced data analytics.

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