- Point of view
Integrating plan-to-cash in consumer goods
A choreographed approach to driving enterprise value
Integrating plan-to-cash operations is a tough transition, but the payoffs can be significant. Genpact estimates demand forecasts will offer 15–25% more accuracy, a 1–2% increase in revenue, and a 3–5% improvement in EBIT if implemented successfully.
Getting the right product to the right place at the right time and at the right price. That's the fundamental formula that drives profitability for consumer goods companies.
Of course, it's not quite that simple. Success is rooted in a carefully crafted operational plan that accurately forecasts demand, orchestrates a complex supply chain, and controls costs.
Did we mention that it also needs to be agile enough to turn on a dime?
In today's world, the operational planning equation is increasingly difficult to solve. The consumer goods industry is competitive, complex, and shifting rapidly. Changing consumer buying and channel preferences, more volatile demand, and shorter product lifecycles mean planning cycles are shorter and need to have agility at their core.
Internal challenges are just as tough. Effective operational planning requires detailed inputs from across the organization – finance, supply chain, sales, and marketing. But too often there's no systematic way to capture and connect them all. Highly manual, fragmented processes inhibit most organizations' ability to analyze and respond to growth opportunities and potential risks. And internal functions are rarely working from the same set of data.
Everyone involved wants the business to succeed. But in many consumer goods organizations, one of the unintended consequences of these challenges is an operational plan that's more focused on meeting the goals of functional silos rather than driving company-wide benefits. To do this, planning and operations must start with the consumer and work backward across plan, execute, deliver, and collect.
To address these problems head-on, consumer goods companies need to tackle three major challenges that are hindering their ability to optimize the end-to-end process of demand planning through to cash collection.
Closer functional alignment
Business functions frequently have competing or misaligned goals and incentives. Consider the sales and production groups in a diversified food manufacturer. The sales team is less worried about the mix of goods it must sell to reach its $100 million revenue target. But for the production team, the process of producing bottled water is vastly different from that of producing ice cream.
The pain may not be obvious during the normal course of business. But any kind of shock to the system – say, a natural disaster that creates a surge in demand for that bottled water – will stress test the operational plan and expose any weaknesses.
Now multiply this scenario over thousands of SKUs. Add the impact of trade promotions, regional variations in consumer demand, and channel structures. It's no wonder there's a level of mistrust – or at least misunderstanding – between functions. This often leads to subpar outcomes in operational planning, with inconsistent participation and a focus on reporting rather than action-oriented problem-solving.
Aiming for perfect alignment is not the goal here – nor is it a realistic expectation. However, it's possible to strike an effective balance by establishing an integrated plan-to-cash process with a framework of guardrails that allows functions to exercise some degree of autonomy within predetermined limits. In doing so, the chaos of operational planning can be better controlled.
Visibility – and ownership – of demand drivers
In most organizations, planners have limited visibility into what actually drives the business forecast and the flow of information across silos is inefficient. As a result, they're unable to connect demand forecasts back to cross-functional inputs – making it virtually impossible to pivot quickly if those inputs and assumptions change. This challenge is only compounded by the fact that the number of variables is constantly shifting, without any systematic way to capture them and orchestrate an effective operational plan.
Internal functions must strive to build a connected forecast that ties outputs to inputs. They must establish clear business rules for incorporating near-real-time data that enables agile and rapid decision-making when disruptions occur or new information becomes available. Everyone needs to understand and follow this framework and use a system of record to track drivers and assumptions.
Guardrails are also critical here. It's essential that each driver has an assigned owner for end-to-end accountability when one function makes a decision that impacts the overall plan. If this impact is above predefined limits, it's flagged straight away.
By implementing a consistent framework of business drivers – and holding functions responsible – businesses can propel a more cohesive plan-to-cash process to achieve enterprise-level goals while also having the flexibility to address emerging opportunities or risks. This also helps to move conversations away from discussing numbers and instead puts the spotlight firmly on making the right decisions to succeed in a dynamic market.
Automation with a human touch
Even in today's digital world, many organizations rely on manual forecasting processes. Employees spend an inordinate amount of time reconciling numbers and manipulating data to extract some degree of useful insight from them.
A lack of automation necessitates this manual work, but it's ultimately of little value and misses the opportunity to perform useful analysis, identify opportunities, and craft strategic responses. It's also unrewarding for the employees themselves.
Companies need to shift from focusing on data collection and manipulation to making smart decisions. This means providing real-time data for an accurate view of performance so they can make quick and decisive course corrections when opportunities or challenges arise. Applying advanced scenario analysis capabilities – powered by artificial intelligence and machine learning – adds greater speed and agility in responding to these kinds of changes.
When the enterprise digitizes the labor-intensive tasks of data collection, it can capitalize on the power of augmented intelligence, by which humans and machines work together. Employees are then free to access reliable, real-time data and apply their experience and judgment to what they do best and enjoy most: making critical business decisions. The enterprise must reimagine the organizational model to actively build augmented intelligence into the plan-to-cash process, rethinking not only organizational structures, but also the skills employees need to ensure they're effective in their new roles.
Reaching this promised land requires a new target operating model (TOM) – one that addresses every step, from operational planning through to cash collection. Only then can organizations translate the strategic ideals of operational planning to the realities of execution.
This requires an all-in approach. It's not just about processes. It's not just about analytics and technology. And it's about more than breaking down organizational silos. Existing processes that take an organization from operational planning through cash collection are usually a set of solo performances. What's really needed is a choreographed approach.
Designing the new TOM begins by identifying gaps and inefficiencies in an organization's current processes compared to leading practices. At Genpact, we've analyzed thousands of business processes and millions of transactions to map end-to-end processes at a granular level, creating a Smart Enterprise Process framework. Applying this insight to the plan-to-cash process can help organizations compare their performance levels to best-in-class benchmarks, target areas for improvement, and assess their readiness for change.
Next comes defining the future state for operational planning that aligns people, processes, technology, and governance. This has three key components:
This is where the guardrail framework really comes into play. It gives functions a degree of autonomy to make their own decisions. But the moment those decisions reach a threshold level of impact on business outcomes or another function's operations, they're subject to review.
For example, a production team may have a frozen, four-week horizon for manufacturing a certain product. If the sales team asks them to speed up production to fulfill demand from their biggest customer, should that change be approved? The guardrails are in place so operational plans can change when they're well-informed and follow the correct decision-making framework, and the implications are understandable and acceptable.
The journey to achieving this ambitious TOM will be different for every consumer goods company. Some will be more prepared to make this leap than others, and where a company is on the maturity model and existing levels of digitization, automation, and process standardization will influence its success.
But wherever they sit on the readiness curve, the approach requires new levels of alignment among internal departments and a common language that the entire business can understand. It demands collaboration with customers, suppliers, distributors, and service providers to drive end-to-end optimization. It requires support by a digital ecosystem that combines reliable data, analytics, and artificial intelligence to help humans make smart operational decisions.
This kind of change is rarely easy. As expected, there will be hurdles to clear. What's important is to develop a plan that recognizes the organization's readiness for change. For some, this may allow for a complete overhaul of the plan-to-cash process. For others, it will make sense to tackle the initiative step by step. Either way, the route taken will require executive support, a clear understanding of roles and responsibilities, and open communication from everyone involved.