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Crystal Ball

Manufacturers’ Forecasts Are Always Wrong, But There’s a Better Way

July 12, 2021
The new era of materials resource planning removes manufacturers’ reliance on chronically incorrect forecasts.

Looking for a snapshot of the state of manufacturing today? Spend a day shadowing the supply chain planning managers within most any manufacturing organization. By and large, you’ll experience stress, chaos and desperate attempts to address the crises of the moment.

The good news is that the pandemic accelerated supply chain modernization efforts that forward-thinking manufacturers were already embracing, but industry-wide were not getting nearly enough traction. A sudden global disruption, like the onset of a pandemic, will always be a challenge for even the best supply chain management approaches. However, the pandemic clarified the need for manufacturers to apply new planning methodologies to increase resiliency.

So, how did we get here?

Today, most manufacturers base their organization’s operations on materials requirement planning (MRP). MRP was developed and launched in the 1950s, a post-war era driven by paper-based processes and relatively homogenous demand. In that era, forecasting was less necessary as manufacturers had a full book of orders and customers willing to wait.

Years later, the business environment and customer expectations changed radically—variety and fast delivery became paramount. Introduced in the late 1970s, MRPII became the glue of enterprise resource planning (ERP) by linking MRP to all the other financial and operational aspects of the supply chain.

However, MRP-driven systems consume forecasts. Because the era of order certainty was gone, forecasts were used to fill the information gap and ultimately became the engine driving the entire enterprise.

The Problem is Forecasts are Always Wrong

Forecasts, no matter how sophisticated, are always wrong. Many manufacturing professionals would likely push back on this sentiment, believing that the next technology step-change or more robust data will deliver the accuracy they need. The most sophisticated assembly of forecasting technology and expertise in the world—National Oceanic and Atmospheric Administration (NOAA)—tells a different story.

NOAA utilizes more than 100 years of historical data, supercomputers, AI and satellites, along with wildly talented analytical and scientific minds. Still, beyond ten days, their forecasts are only 50% accurate. If this is the best NOAA can do with all the resources at its disposal, how can a manufacturer possibly effectively forecast?

Forecasting certainly has its place, but running day-to-day operations this way is not effective. Confirming this inefficiency, return on assets within the US economy was 4.1% in 1965, but by 2012 had fallen to 0.9% (according to a Deloitte report). Unfortunately, this scenario has not improved.

The Impacts of Reliance on Inaccurate Forecasts

There is no coherent tactical plan for running the supply chain using MRP-based planning. Lead time and batch size impacts are not understood; planners know their data is wrong and intervene daily. The system positions manufacturers in a chronically reactive and imbalanced posture, leading to way too much of some inventory in some places and not nearly enough in others.

Worse, the lack of a plan and hiding real supply chain cost drivers, like lead time, result in poor decisions. The only lever to reduce cost is unit cost. So in chasing the reduction of unit cost production, supply chains have become more global, longer and rigid. The problem is getting bigger, not smaller. Unit cost may come down, but agility, competitive advantage and total cost are all impacted negatively—not including the considerable expense of advanced planning systems trying to hold things together.

Every player within today’s supply chain utilizes their own ERP system for the vast majority of organizations, driven by MRPII. Organizations worldwide are all operating based on inaccurate forecasts amplifying variability and transferring the increased problems throughout the supply chain faster.

“As volatility and portfolio complexity continue increasing, we learned that progress improving our forecasting efforts tended to plateau,” shared Jean Paul Popesco, global planning and logistics excellence manager with Shell Lubricants, a global lubricants supplier. “Moreover, using MRP as a planning methodology tends to propagate large bullwhips throughout the supply chain, resulting in reacting rather than planning. To maintain consistent customer service levels while optimizing cash, adopting the demand-driven methodology meant addressing our challenges by driving a more mature dialogue on a larger scale and bringing transparency to decision-making.”

A New Paradigm for Manufacturers

To increase both effectiveness and efficiency, manufacturers require a tactical supply chain plan that links the organization’s strategic direction and the long-term forecast with the organization’s operations.

Chad Smith and Carol Ptak, founders of the Demand Driven Institute, developed and ushered in Demand Driven Material Requirements Planning (DDMRP) to incorporate multiple planning methods and promote relevant information flow through the supply chain.

While extremely helpful, DDMRP is a methodology paving the way for DDMRPII, a vehicle for broader supply chain planning, tactical decision-making, supply chain setup planning, visibility and execution. DDMRPII is driven by market service strategy, accepts that there is a need for push- and pull-based supply chain approaches, and links them all to operations. Variability in demand is accepted and understood. Key setup decisions are based on capacity, and a segmented market strategy support decisions on enabling the supply chain to scale up and down.

DDMPRII couples long-term strategic direction, market offer and operational capacity. Marrying these factors generates a tactical plan tailored to accomplish defined business objectives.

The secret to DDMRPII’s effectiveness is the midterm tactical engine, called conditioning in DDMRPII terminology. Conditioning decisions such as product segmentation policies, plant capacity, resource planning, operational parameters, inventory buffer distribution, service level policies, and many other parameters facilitate automated decision-making in the short term, with the long-term and operational capabilities fully considered using multiple planning methods.

Grundfos is a global leader in the supply of pumps and associated parts that play critical roles in the proper functioning of much of the world’s water supply. “Our spare part supply chain function has been in a continuous state of change and development. Using a demand-driven methodology, we have been able to successfully scale up our worldwide operations while keeping our stock turnover and service performance levels healthy,” said Anand Mishra, the company’s global spare part planning manager, Grundfos. “By running various inventory simulations, we have been able to fine-tune our supply planning activities systematically to suit different business requirements and material classification criteria.”

In the end, DDMRPII positions material availability, production capacity and inventory in the supply chain, allowing manufacturers to achieve defined business objectives. By reducing short-term inefficiencies, operational teams gain the bandwidth and the information to focus on overall improvement.

Shell Lubricants migrated from an MRP approach to DDMRPII, with the challenge of managing more than 10,000 SKUs. “A diverse portfolio is quite difficult to forecast, and the orthodox methods that relied heavily on forecast were under significant pressure. With a smart set of simulations testing that diversity, I could see that a demand-driven approach would dramatically reduce the variation and noise compared to the forecast-driven approach,” shared Nick Lynch, former global planning excellence manager, Shell Lubricants (and now a partner at SmartChain).

“The potential was obvious, but it forced me to think differently about how we handled inventory, planning signals and execution. Base oils, additives, components and finished goods all had specific requirements that had to be met. I wanted a solution that could handle all those real-world scenarios to avoid the need for multiple solutions or planners using even more Excel sheets. With the end-to-end functionality and capabilities of DDMRPII, Shell Lubricants could build a much more cost-effective, resilient supply chain that increases competitiveness in the market. Seeing just how much the forecast function was disrupted in 2020, I am even more convinced now that it was the right move.”

In short, harried and stressed supply planning managers are the “canaries in the coalmine”—visible manifestations of a broken manufacturing supply chain. With ever-increasing supply chain complexity, demanding customers, and no end to market volatility, manufacturers need a better supply chain management approach. By facilitating the planning method that is most appropriate for specific products or sets of products, DDMRPII allows manufacturers to focus on long-term optimization by reducing short-term crises. This state is one that supply planning managers and the entire manufacturing industry can get behind.  

Phil Ribbins is co-founder and CEO of O8 Supply Chain, a provider of supply chain planning software.

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