To steer their companies through today’s volatility and uncertainty, it is imperative that finance functions turbocharge their role as forward-looking, strategic advisors. Two related steering capabilities—dynamic planning and advanced business intelligence—are critical enablers of this enhanced role. Dynamic financial planning provides a driver-based, comprehensive view of potential future performance, accelerating a company’s ability to sense and respond to a changing business landscape. Advanced business intelligence capabilities enable real-time analyses of both historical and future performance.
With greater visibility and better scenario planning, companies can improve their monitoring of operations, markets, and customers and can enable faster and more informed decision making. Companies of any size or industry can quickly deploy proof-of-concept tests of new solutions and capture material value in the near term while building capabilities for the long term.
Several building blocks are required to accomplish this step change in finance function excellence. Companies must create a driver-based business logic that connects strategic, financial, and operational metrics and implement digital tools and visualization engines. Success also requires having shorter planning cycles, a central data platform, and a new talent strategy. Given the scope, it is critical to effectively coordinate a multidisciplinary effort across finance, business, and technology.
Companies need more accurate and agile planning and more actionable business intelligence to weather the challenges of today’s economic environment. They face an unprecedented combination of intense supply chain pressure, high inflation, low unemployment, rising interest rates, and global political conflicts. To guide decision making amid the uncertainty, companies must understand how different scenarios will affect operational and financial performance.
An advanced approach to planning and business intelligence also helps to attract and retain top talent. Finance professionals will feel empowered if they spend more time on value-added analyses and decision support instead of data extraction and manipulation. In addition, more precise and accurate data allows CFOs to be true strategic advisors to the business and be better prepared for investor meetings.
To capture these benefits, finance functions need two types of enhanced capabilities:
These enhanced capabilities make steering better, faster, and more efficient.
The advanced approach allows the finance function to focus on drivers that influence the metrics that matter most to the business, such as growth, margins, and shareholder returns. This improves both the quality and the efficiency of decision making and strengthens the strategic partnership with business leaders.
A major US department store chain implemented dynamic planning and advanced business intelligence to respond to the challenges of the COVID-19 pandemic. The company was able to improve inventory turnover compared with prepandemic levels by 15%, set location-level prices, and rethink how stores measure productivity. It achieved these impacts by:
Producing and updating plans, budgets, and forecasts requires significantly less time and enables agile decision making. The department store company shortened the lead time for producing forecasts to one week from the customary three to four weeks. It now updates performance dashboards in real time and produces full management reports in a few hours, versus two to four weeks in the past.
Finance functions that modernize their planning and business intelligence can often become 15% to 20% more efficient by reducing the amount of time spent extracting, manipulating, and reconciling data. The department store’s finance function decreased the share of its time spent on these low-value tasks from 60% to 80% in the past to less than 20%. This freed up finance professionals to spend more time on business advisory activities.
Implementation of the new capabilities requires establishing five building blocks: driver-based business logic, digital tools, simplified processes, data platforms, and redesigned talent and operating models.
Each company needs a solid understanding of its business logic—that is, the drivers of performance and a structure for analyzing the results. Two capabilities are essential:
A US luxury department store developed driver trees for all key line items in the P&L statement, including sales, merchandise costs, supply chain costs, and SG&A expenses. Exhibit 1 illustrates the driver tree for variable labor in stores and how a company can leverage automatic and manual inputs.
After establishing the business logic, finance functions need to configure digital-planning tools and visualization engines that allow teams to examine what-if scenarios, interpret the results, develop actionable insights, and define plans. Financial-planning tools (such as Anaplan and OneStream) and visualization engines (including Tableau and Power BI) are examples of modern cloud-based tools that are transforming traditional finance processes. Exhibit 2 shows a sample dynamic dashboard that visualizes real-time data and enables analyses by stakeholders across the organization.
Digital tools should provide the following capabilities:
A US retailer created an ML engine to improve its ability to sense demand and respond rapidly to customer needs. The model integrated multiple external data sources to better predict customer buying patterns and to get “smarter” at sensing demand over time. The company integrated the model into regular operational and financial-planning processes, to ensure that its insights inform daily decision making and resource allocation decisions.
To effectively run the digital tools using the new business logic, finance functions need to rethink their processes. They can apply automation to shorten planning, budgeting, and forecasting processes. In addition, frequent forecasting with occasional detailed planning and budgeting allows companies to maximize visibility into, and control over, operations while minimizing the amount of time spent on the annual planning process. Companies can also boost efficiency by improving alignment touch points with senior leadership and breaking down organizational silos to better coordinate financial and operational planning.
To enable the adoption of AI-driven algorithmic forecasts, an automotive manufacturer’s leasing business unit needed to replace its traditional bottom-up forecasting process. The new process included alignment touch points that allowed leaders to adjust the algorithmic forecasts manually by applying their expertise, followed by strategy sessions to simulate the impact of making changes to strategic levers (such as debt ratios). Full adoption of algorithmic forecasting enabled the company to shift from retrospective analysis of past results to proactive identification of actions and their likely bottom-line impact.
To feed digital tools and calculation engines, companies should establish a data repository (for example, a data warehouse and data lake) as the single source of truth. (See Exhibit 3.) To make effective use of the data repository, companies must take the following actions:
Companies need to identify the new competencies required to manage dynamic planning and advanced business intelligence. They must upskill the current workforce (to use new tools and conduct scenario analyses, for example) as well as hire people for new roles (such as data scientists and configuration specialists for finance tools). A center of excellence should oversee any future changes to the new digital tools and ensure that they are being used to their full potential.
Leading organizations are addressing this imperative aggressively; many see it as especially urgent given the intense competition for digitally savvy talent. A global health care company transformed its talent strategy to support changes to its digital tools and operating model. This included upskilling people within the finance organization through formal training in key skills, updating the skills (such as coding and scenario modeling) required for each role, and expanding career paths to prioritize diverse, skill-based experiences. This upgraded approach is driving a greatly enhanced employee value proposition, which helps the company attract and retain the best talent.
Although the concepts behind dynamic planning and advanced business intelligence are not overly complex, many companies struggle to implement them successfully. For organizations to achieve full value, it is crucial that they set appropriately bold ambitions for progressing through the journey and think holistically about the required changes concerning people, processes, and technologies. Companies can use a diagnostic to understand their starting point. For example, BCG’s CFO Excellence Index benchmarks a finance function’s performance along dimensions such as finance IT and systems, planning and forecasting, and business intelligence.
Five success factors are crucial for implementation:
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