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How finance leaders are becoming strategic business partners

June 28, 2023
Data literacy
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Using data to increase the speed and the scope of financial decisioning

Nearly 50% of CFOs say that the current financial landscape poses the greatest challenges they have encountered in their careers.

Economic volatility, marked by disruptions in the supply chain and labor shortages, has intensified, placing greater strain on conventional finance processes and teams. These processes are primarily designed for quarterly and annual cycles, rather than addressing real-time challenges. Moreover, the growing volume of business data requires increased reconciliation and consolidation before meaningful insights can be incorporated into budgets, forecasts, and business plans.

Forward-thinking finance teams are leveraging these challenges as catalysts for improvement in their operations and strategic support. They are implementing new technologies and introducing enhanced processes to work more efficiently with increased flexibility. These teams are also reevaluating how they generate business insights and how they communicate them to leadership teams, empowering them to make impactful decisions.

By adopting these advanced practices, finance teams are developing a holistic perspective of the business, with different elements coming together to provide accurate recommendations and helping them become trusted partners to business units.

Making the most of the opportunity to automate

Many finance teams rely on spreadsheets for various processes such as generating reports, owing to their ease of use. However, this approach can make it challenging to provide the latest data, especially considering the exponential growth in business information and the fact that it often sits in siloed systems. In contrast, advanced finance teams have developed customized processes that let them run reports effortlessly, utilizing real-time data and automating the frequency of their generation according to their specific requirements.

In fact, advanced finance teams lean heavily on automation to speed up time-consuming collection of financial data. This means that they are more inclined to integrate siloed financial and nonfinancial data, creating a unified and reliable foundation of information that helps them provide real-time updates to business leaders responsible for driving improvements in key performance indicators.

These teams employ techniques to generate insights as data stories, focusing on the most significant changes within the business. They provide stakeholders with a clear understanding of the underlying causes, predictions, and recommended actions tailored to their specific roles and contexts.

This approach minimizes the risk of misinterpreting financial analysis and ensures that decision-makers have accurate and actionable information at their disposal. The more automated data storytelling is, the less time finance spends building and reconfiguring dashboards.

For instance, advanced finance teams thrive in meetings with executives by swiftly providing answers to new questions that the existing dashboard fails to address. As data aggregation and analysis are automated to a large extent in such teams, they can respond to stakeholder queries within just an hour or two, rather than several days. This high level of agility enables stakeholders to iterate more rapidly, putting their gut instincts to the test.

Providing top-quartile financial planning, budgeting, and analysis

Traditional forecasting, planning and budgeting processes, carried out annually, no longer align with the demands of today's fast-paced environment. Inflexible budgets hinder business leaders from adapting swiftly and seizing opportunities as they emerge.

What’s more, finance professionals often invest several months in the annual planning process. This entails creating and organizing spreadsheets, distributing them to departmental managers, reminding them of the deadlines for budget figures, collecting and consolidating the spreadsheets, copy-pasting data between multiple sheets, verifying the accuracy of aggregated numbers, formatting the spreadsheets for submission to senior management, and repeating some of these tasks for different business scenarios. By the time the annual plan process reaches its conclusion, there are concerns about the validity and relevance of the plan.

The ability to create various versions to test out ‘what if’ scenarios, plugging in multiple variables and assumptions to understand the short and long term impact on business is also limited and cumbersome in spreadsheets.

In the current cost-constrained operating landscape, there is a need for agile and iterative planning approaches.

For the most successful finance teams, this means constantly reassessing and adjusting budgets and forecasts, running multiple scenarios without constraints, and having insights into all possible outcomes and their implications. They do not depend solely on spreadsheets to create budgets and forecasts, recognizing their limitations in capturing real-time data and the time-consuming processes needed for building forecasting models. Instead they turn to platforms that can connect to relevant data from disparate systems such as ERP, CRM, HR and payroll systems. These teams are able to test out their budgets and forecasts against an unlimited number of scenarios with the right technology. Consequently, they tend to have more insight into what may happen down the line, making their budgets and forecasts as well-informed as possible.

They also constantly look to automate as many repetitive, manual parts of the planning process as possible and use interactive dashboards to show stakeholders where the business is headed.

For instance, when confronted with an unplanned request to assess a white-space opportunity, advanced teams showcase their remarkable agility by quickly developing a model that incorporates business input within a matter of hours, instead of weeks. This accelerated pace allows for in-depth analysis of potential funding paths, unveiling alternative investment options without any delays. Moreover, when evaluating capital expenditure (CapEx) business cases, the finance team's ability to conduct rapid pre-audit analysis propels faster insights into factors impacting project performance at maturity. This expedited analytical approach not only enhances the business's comprehension of uncertainties, but also empowers stakeholders to make well-informed decisions much faster.

As demonstrated by the FP&A team at Amazon, these advanced practices pay off. The FP&A team at Amazon employed modeling techniques to evaluate the effectiveness of two potential business levers: offering customers a 10% discount or providing free shipping on purchases. Through their analysis, they discovered that free shipping would have a more significant impact. This pivotal finding paved the way for the creation of Amazon Prime, one of the primary catalysts behind Amazon's extraordinary success.

Such examples abound. At The Economist, the FP&A team used modeling to understand how the magazine could adapt to the increasing popularity of digital readership. At Lego, FP&A calculated how the company could utilize the savings from reduced travel during the pandemic to facilitate productive remote work for employees. Additionally, at Levi's, FP&A showed how the company could stay ahead of changing consumer preferences by preparing for the shift from skinny jeans to baggy jeans.

The path to forward-looking insights

With the right systems and processes, the most successful finance leaders are helping their teams automate time-consuming work, move away from spreadsheets, and carry out advanced analysis. Such finance teams make the most of data and provide much more than accurate financial statements and reports.

Finance teams seeking to get there can start with three changes. The first is increasing the focus on non-financial data and metrics. The second is helping financial analysts gain a deeper understanding of the operations of their business so that their analyses become more relevant. The third is to bring in technology that can help teams automate even further and build more complex models that make their analyses more consequential.

A data analytics platform like KNIME lets finance teams easily access data from any system - whether financial or non-financial. With its low-code, no-code interface, finance teams can immediately start automating repetitive tasks while gradually upskilling to more advanced modeling, without any coding.

As a result, finance starts becoming a function that has expanded its focus beyond basic numbers and provides forward-looking insights that contribute to shaping the business strategy.

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