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Advancements in data availability, collection and processing — along with new analytic capabilities — offer first movers in the finance function the power to harness new insights, navigate risk and make informed decisions faster than competitors. This has caused many organizations to overhaul their enterprise resource planning (ERP) and related systems that supply the core data necessary to fuel business insights.
But here’s the catch: ERP transformations are often once-in-a-decade investments that span multiple years, impacting almost everything from customers to closing the books. And, despite significant efforts, the outcome frequently falls short of expectations, leaving organizations disappointed and fatigued.
So, what’s happening? Think about building a new home. Would you lay the foundation without a blueprint for the house it will support? Without a clear vision for downstream performance management capabilities and requirements, teams often default to what they know. This results in either marginal improvements or overengineered solutions due to the lack of clarity in decision-making guardrails that help guide effective design.
To avoid this, you should consider first establishing a common layer that brings together disparate data and cross-functional teams to better manage performance and drive profitability: enterprise performance management (EPM).
Use EPM to define the vision for a strategic finance function that helps drive profitability
Most organizations acknowledge the urgency for change.
In our 27th Annual Global CEO Survey, 97% of executives said they have taken steps in the last five years to change how they create, deliver and capture value, and 76% took at least one action that had a large or very large impact on their company's business model.
The problem is many companies frequently embark on digital transformation journeys without taking a step back to redefine what they need to operate and manage in the future. It’s no surprise, then, that capturing value from digital transformation remains elusive.
Consider a different approach. Start by having finance reimagine their role as a strategic business partner — or performance coach — responsible for curating data to steer decisions that help drive long-term value creation. This requires finance collaborating with cross-functional leaders to answer critical questions:
- Do we have the right accountability model?
- How and where will decisions be made, and what key performance indicators (KPIs) and insights support that?
- What new factors need to be understood as market dynamics shift?
- How will we accelerate and connect planning and forecasting?
- What data will this require, how frequently and where will it be sourced?
This shift in perspective should naturally lead the finance function to focus on EPM solutions. Well-designed EPM solutions provide agile forecasting and scenario modeling, risk mitigation, integration between finance and operations, and better decision-making processes.
How EPM supports a smoother ERP transformation
Here are the specific ways that an “EPM-first” strategy can unlock what an ERP system should do on Day One, supporting a smoother ERP transformation while accelerating the path to unlocking finance as the coach to the business.
Data reporting, quality and analytics
In PwC’s August 2023 Pulse Survey, 43% of finance leaders said establishing finance as a partner to the business is one of the top three priorities for the finance function. Strategic finance teams, or coaches, do more than keep score — they give operations fact-based insights that reveal opportunities to improve performance and drive value in line with the overall enterprise objectives.
For example, finance should be able to quickly identify upstream supply chain disruptions, evaluate the impact and analyze options to help business leaders determine how to appropriately respond. But this requires alignment on the data elements that need to be captured and the enterprise data structures that connect them. Demand plans, pricing and promotions, suppliers, unit costs, lead times, inventory levels, production capacity and working capital — these are just some data points that should be connected and collected.
This calls for a reimagined data and reporting strategy, with cross-functional teams tying together the two major reporting streams — financial and non-financial — that are essential to generate actionable insights. Instead of working in silos, financial systems should be closely integrated with operational data sources to eliminate gaps, confusion and bottlenecks that can delay the transmission of vital insights.
The decisions made during an EPM implementation are crucial in determining investments required in your ERP, resulting in a faster deployment and reducing risk from the entire process. Starting downstream creates a significant pull for data — the ingredients to drive performance — identifying gaps and being clear about what needs to be delivered.
At one multinational company, using EPM to redefine its enterprise data model formed the basis for a new chart of accounts design, as well as enabled it to take advantage of enhanced reporting capabilities earlier. The company was able to test key systems with minimal risk or cost of failure, supporting a smoother transition when the future ERP came online.
Agility and predictive ability
According to the 2023 PwC Global Advisory Survey, the top 20% of companies capture more than 13 times the performance premium of their industry peers. These top performers make more frequent and significant capital reallocations, more quickly identify and act on risks and opportunities, and drive mutually reinforcing investments. One common thread across these companies is the ability to look ahead and remain agile while connecting the necessary levers to take advantage of multiplier effects.
Additionally, there’s more urgency among executives to reconsider their business model. PwC’s June 2024 Pulse Survey found that 34% of CEOs believe their average competitor will be out of business within three years if they don’t adjust their business model. If you don’t improve your organizational agility with better forward-looking insights and decision-making processes before rebuilding core data platforms, it may be too late.
Instead of waiting 18 months or longer for an ERP implementation, companies can start to capture value from EPM in as little as three months. Bringing together disparate data sets into a cohesive and integrated data model — with improved forecasting and analytics — will allow businesses to more quickly and effectively make capital allocation decisions, respond to market shifts and understand cross-functional impacts on performance. It also can identify roadblocks such as weak data streams, convoluted processes and workforce gaps, which may need to be addressed before or during an ERP implementation.
An opening to AI and machine learning via EPM
As finance leaders explore generative AI (GenAI) and machine learning (ML) capabilities to modernize the planning and analysis value chain, EPM can be a powerful test case. Many applications of AI, such as forecasting and scenario modeling, already sit within financial planning and analysis teams — hence why machine learning features have been embedded in the majority of leading EPM solutions providing a low-cost, high-value entry point to drive value with AI.
With a more urgent need for precise and predictable forecasts related to revenue, earnings before interest, taxes, depreciation, and amortization (EBITDA), free cash flow and other key operational metrics, the ability to rapidly and accurately model future outcomes in a way that considers financial, operational and external factors can be a strategic differentiator. However, this often results in more data being consumed, a lot of which is unstructured and sits outside a company’s standard data model. Leveraging the AI capabilities within leading EPM and hyperscaler solutions can help integrate planning models with a wider amount of data, often from various internal and external sources, leading to a competitive advantage for companies.
One global technology company unlocked more than $250 million of working capital because of more accurate rebate forecasts, which allowed them to greatly reduce accrual levels. It applied ML to granular customer and payments data, among other items. Separately, a large healthcare organization implemented an enterprise reporting strategy after facing challenges during their ERP journey, which highlighted the need for leaders to access cross-functional data from various systems. By using next-generation cloud data platforms with embedded AI, the organization enable self-service access to predictive analytics for volume trend analysis and target monitoring. Both of these examples were deployed within six months.
This underscores the value opportunity while also addressing a common misconception among companies hesitant to start their AI journey. The idea of “perfect” data is often an illusion. An EPM-first approach allows finance to be a first mover in the AI space for organizations, implementing predictive forecasting and analytical capabilities that draw on robust data sets that a thoughtfully redesigned ERP can eventually better satisfy.
How to get started
Leading with EPM offers opportunities to accelerate value, clarify future ERP requirements and reduce risk in the entire digital transformation. Consider these questions as you determine if an EPM-first strategy could work for your organization:
- Do we have a clear vision for the specific capabilities, processes and operating model that will enable finance as a business partner?
- Does our current data model support the necessary insights we need to be successful as the industry and business model evolves?
- What is our future reporting strategy, and do we have a clear vision for the role of EPM, ERP, operational systems and enterprise data platforms in supporting it?
- Have we evaluated whether there are untapped opportunities to streamline insights or apply AI to drive immediate value within our current ecosystem?
- Have we aligned with cross-functional teams on the changes required to accelerate and advance forecasting processes in support of more agile, effective decision-making?
Answering these questions can help you begin to formulate what path makes more sense for your organization — leading with an EPM implementation and seeing more immediate value or starting with an ERP implementation and adding EPM capabilities down the road.
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