Boosting Competitiveness Through Advanced Production Planning

Accurate planning has never been more important to a company’s ability to quickly react to new scenarios and changing priorities.?With pressure mounting to boost competitiveness, it’s no wonder that manufacturers around the world have looked for additional ways to manage scarce resources, build resilience, and reduce emissions — all without constantly fighting fires and increasing complexity.

Manufacturing and supply chain planning has four distinct process levels: network strategy over the next 6-10 years, capacity planning over the next 3-6 years, sales and operations planning over the next 2-18 months, and production planning on a local level over the next 1 to 8 weeks. (see Exhibit 1).

Advanced production planning offers a new lever companies can pull to generate business impact at this last level. In its most basic form, production planning is the process of deciding what to produce and how to produce it, in line with business objectives and operational constraints. The latest tools and approaches allow companies to automate what is often a manual planning process, using advanced analytical techniques to make plans based on a number of preset criteria and parameters, such as inventory levels, delivery performance, and asset utilization. The system sorts through all the data and future scenarios to systematically find not just the most feasible plan, but also the optimal plan with the best performance according to a company’s objectives.

Incorporating advanced planning techniques into traditional planning methods has the potential to create a step change in performance, significantly reducing costs, increasing profitability, freeing up cash, and managing output much more dynamically. We have seen inventory reductions of 10% to 40% as well as overall equipment effectiveness (OEE) increases of 5 to 15 percentage points. With much greater automation, companies can also achieve a 20% to 25% reduction in the cost of the planning function and free up workers to do higher value-added jobs (see Exhibit 2). In addition to these bottom-line results, the smartest companies are finding new ways to increase top-line revenues from additional services such as expedited orders and faster delivery times.

But to see this kind of boost to competitiveness, a company must fundamentally transform its operations and organization. Those that get this right can unleash a significantly improved value proposition in terms of cost and quality, greater operational resiliency, and higher sustainability as they react to a rapidly changing environment.

Getting the Technology Right

Implementing advanced production planning involves changes that can be unfamiliar to many organizations. The latest mathematical approaches include optimization algorithms that find not just good solutions, but also optimal solutions, using techniques such as branch-and-bound and branch-and-cut algorithms.

Thanks to rapid technological progress and the exponential increase in computing power over the last few years, advanced analytical tools and techniques to quickly optimize production are now within reach of any company. Plans that once took weeks now take hours to produce.

But companies must carefully decide whether to use existing off-the-shelf solutions or invest in a tailor-made solution with custom functionality. Off-the-shelf software offers obvious benefits, such as fast deployment, low implementation risk, and usually lower cost. Examples of off-the-shelf tools include Siemens’ Opcenter APS, OMP’s Operational Planning, and Dassault Systemes’ Delmia Quintiq, along with more sector-specific providers such as BlueYonder for CPG companies and Aspentech in the chemicals industry.

Tailor-made solutions, on the other hand, allow for more complex ways to manage constraints and provide the prioritization logic necessary to consciously balance conflicting objectives like inventory levels, customer satisfaction, and production efficiency. This tailor-made functionality, however, often comes at the price of longer lead times and higher cost.

As a consequence, there is no “one-size-fits-all” technological solution. Manufacturing companies need to carefully define their target picture and requirements to identify the most suitable solution for the business — whether this is an off-the-shelf solution that potentially has some customized elements, or is even a fully bespoke solution, depends on the individual company. A careful consideration of all the options is essential in order to avoid making a costly mistake.

Consider the experience of a European manufacturer of specialty steel products that faced a severe cash crunch. Its high work-in-progress inventories and long, fluctuating cycle times required large amounts of working capital to hold the finished-goods inventories it needed to reliably supply its customers. As part of its transformation, the company embarked on a rigorous redesign of its production planning processes and organization. After a careful analysis of the costs and benefits of off-the-shelf and custom solutions, it decided to build a custom production planning tool in agile sprints, starting with a minimum viable product (MVP) within weeks rather than months, which it continuously evolved over time. After only five months, the company was able to cut its work-in-progress inventories by more than 30% and its lead times by 25% on average, while reducing its considerable variation in lead time by more than 60%. As a result, the manufacturer unleashed large amounts of cash that had been tied up in working capital.

Getting the Organization Right

Technology is certainly critical. However, our experience shows that successful production planning projects devote only 10% of the effort to algorithms and 20% to the technology stack. The remaining 70% of the work involves transforming the planning processes and organization as well as building the necessary capabilities to sustain the transformation over time.

Planning organizations often fail to adopt many advanced production planning tools because they attempt to implement advanced planning as an IT automation project. Since these projects touch every aspect of the business, the focus needs to be on organizational transformation, with IT being a key enabler of the transformation.

Algorithms can take over many of the traditional planning tasks that were once manual, including the creation of an initial draft plan and plan adjustments to account for changes. Automation eliminates much of the need for manual data gathering and plan creation. The role of the production planner therefore shifts toward duties like the management and facilitation of the algorithmic planning process. That requires new capabilities, such as much more rigorous mathematical education to ensure a basic understanding of optimization algorithms. Traditionally, production planners have transitioned from more operational roles like production team leaders, so reskilling and upskilling are needed. In addition, in some cases companies will need to complement the team with new hires who have deep mathematical know-how.

Advanced production planning also depends heavily on having accurate inventory, demand, and product-related data, as well as detailed information about asset availability and yield. This can be done by leveraging a control tower to provide that end-to-end visibility of the entire supply chain and also within the 4 walls of plant operations.?Consequently, much stricter data governance capabilities are required.

The latest production planning methods rely on explicit organizational alignment on planning objectives and priorities to shape the data into plans. These guardrails guide the optimization algorithm. Parameters, constraints, and objectives can include inventory targets, on-time delivery priority, and even the capabilities of individual machines. When liquidity is tight, a company might prioritize lowering inventory over delivering every order on time. When output is the priority, inventory constraints can be relaxed.

Much of what goes into the algorithm involves the tacit knowledge that experienced employees often build up over years with a company. It is crucial to codify this kind of implicit knowledge. Objectives must be regularly reviewed and aligned to fit the strategic and tactical goals of the business. Leadership must also clearly communicate strategic goals, think more strategically in setting planning guidance, and stick with the system rather than stepping in to change production plans manually.

A leading global synthetic fiber manufacturer found this out when it implemented a data-driven production planning process. Using optimization algorithms to create short-term production plans for the next 8 weeks for was only the first step. Tools were created to enable planners to inspect and validate the plans with the help of inventory and sales forecasts. Ultimately, front-line managers were trained to use the tools and further develop and roll them out to other plants. As a result of the transformation, the company saw 80% reductions in unfulfilled orders and 50% fewer changeovers.

How to Begin

Manufacturing companies cannot afford to miss out on building modern production planning capabilities. Advanced production planning offers significant potential to improve productivity and efficiency, ?yielding significant profits. With implementation easier than ever before, a quick ROI is possible.

That said, the main sources of value for advanced production planning vary significantly among industries, depending on their asset intensity, so it is critical to make sure a company’s future planning ambition fully taps the profit potential. To ensure companies reap the rewards, we have seen leading manufacturers take the following steps.

Assess the status quo. Companies should conduct a health check to identify potential areas for improvement, taking a hard look at their existing planning processes, governance, systems integration, and level of skills and training. (See Exhibit 3.)

Define the target operating model. Before implementing a technical solution, it’s necessary to establish the business case for change, the organizational structure, processes and roles, and the business requirements.

Select the optimal technologies. Weigh the tradeoffs between off-the-shelf and custom solutions, then adapt the options best-suited to your needs.

Pilot and learn. Implement a pilot to test the new planning approach across a single end-to-end process, and adjust the operating model based on learnings from the pilot.

Transform the organization. Drive planning transformation across the company, including retraining planning staff and the adjacent organization.

Iterate on planning parameters and objectives. Continuously monitor planning quality and update the assumptions that feed the algorithms to improve strategic alignment.

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Production planning is an area that is ripe for transformation. Getting the production-planning technology and organization right is the key to systematically improving the planning process.

Companies that take effective action in this area enjoy substantial competitive advantage over their peers. They also measurably lift performance, as well as improve their value proposition, resilience, and sustainability. There’s little to lose and everything to gain from getting an immediate start.

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By Daniel Küpper, Yohei Kaneko, Stephan Bloempott, Julian Englberger, and Neeru Pandey