Reliable results thanks to optimal planning

Implementing a Sales and Operations Planning (S&OP) process is a popular approach to solving challenges such as this. It entails a holistic, cross-departmental and networked corporate planning approach that better balances supply and demand, one that focusses on meeting customer needs. To this end, supply chain planning is tightly coordinated with sales, purchasing and production planning, with the Sales, Marketing, Procurement, Manufacturing and Finance & Controlling (FiCo) departments all working closely together.

Having decided to introduce S&OP in collaboration with ROI-EFESO, we assembled a project team. This comprised a project manager and four other consultants for specialist aspects. On the customer side, the core team comprised SCM and supply chain project managers, a SCM analyst and an IT in-house consultant.

The project commenced at the end of 2020 with an initial analysis of the current situation and the creation of a concept solution, as well as a complete dry-run implementation with an individual model, as a proof of concept. The roll-out then took place in two stages: Stage one lasted eight months, during which the first two plants were connected and a 'Basic' S&OP cycle rolled out. In Stage two, the remaining three plants were also fully integrated in order to form a 'Full' S&OP cycle.

The customer's legacy planning process was hampered by having to cope with an enormous number of different part and material numbers as well as a host of technological dependencies between the individual production stages. In the past, these restraints had often led to inaccurate planning results that frequently had to be readjusted. Like many other markets, the furniture industry is highly dependent on other sectors, and customer orders are often placed at very short notice. As a result, rapid fluctuations in demand are sometimes difficult to compensate for which, in turn, can lead to a decrease in contribution margin.

Due to the extreme complexity and effort involved, the company traditionally had only carried out planned exercises once a quarter, and even then purely on the basis of historical data. Freely available market data/reports were not taken into account, even though they would certainly have led to improved forecast quality. Instead, the company simply relied on its own data from the previous year. This meant that for three quarters of the year it effectively was working with outdated planning data.

Even though the quality of its planning was less than optimal, the quarterly frequency undertaken had normally proved adequate. However, the advent of the Corona pandemic, and the related sudden surge in demand for furniture, had underscored the need for a rapid realignment and improvement in its internal planning process.

The project goals were quickly identified and prioritized, namely:

• A reduction in planning effort while increasing the quality of short- and long-term requirement planning, as well as optimized pre-planning for production
• Standardization and automation of the planning process to achieve more flexibility, higher efficiency, better utilization and productivity
• Implementation of a fast, easy-to-use and accurate planning process, one that could be undertaken more frequently in the future
• Achievement of more accurate forecasts by incorporating publicly available market macro data.

An activity structure analysis (TSA) carried out at departmental level identified what work was going into the ACTUAL planning process. This enabled ROI-EFESO‘s consultants to identify the individual levers within an optimized planning process which, in their opinion, would yield the greatest beneficial impact (calculated in FTEs or Full Time Equivalents). Measures to reduce the adverse effects of external variables (e.g., customers, suppliers) and improve internal variables (e.g., better forecasts and projections to help suppliers with their planning; higher frequency planning cycles) were identified and evaluated, using a cost-benefit assessment for prioritization.

Lean, fast and automated: the new production planning process Based on this in-depth analysis, the ROI-EFESO project team developed a concept for the introduction of an integrated S&OP process. Its goals were to improve forecast accuracy and production planning stability as well as to increase efficiency and flexibility. Accordingly, the new end-to-end planning process (encompassing budget, sales, SCM, capacity and procurement) was to be standardized and automated in order to increase the quality of demand planning, optimize the production plan, and reduce manual effort.

Instead of, as was previously the case, receiving a wide variety of Excel lists with individual plans from different departments, planning would in future be carried out once a month in a structured manner using the new S&OP process. Inputs from all relevant parties would be integrated, with a primary focus on the sales organization. Demand, supply and inventory were to be reconciled within the S&OP process. The overall goal was to create a feasible, realistic and consistent plan every month.

The IT solution chosen was SAP Integrated Business Planning (IBP). SAP IBP is a state-of-the-art tool in this area and supports all the necessary components of an integrated S&OP, from demand planning to capacity planning and prioritization of customer orders. This enables capacity supply and demand to be brought in line, customer requirements to be better forecast and production to be more accurately planned.

SAP Integrated Business Planning (IBP) was especially developed for the management of complex product portfolios and allows for longer-term production planning (e.g., in weekly periods). The PP/DS Optimizer add-on for Production Planning and Detailed Scheduling also caters for planning over the shorter term (e.g., down to the day or hour). A particular strength of the solution is that allows planning at any aggregation level, broken down to individual material numbers or aggregated to any other level. For example, one can have a market report flow in at a level where the input data is available and but then display it at the level where the sales person is doing their planning. Only this solution enables a proactive use of statistical market data.

A detailed proof of concept would now show whether the proposed system would meets the customer’s requirements. So ROI-EFESO recommended a comprehensive dry run. Its challenge was to demonstrate all the functions of the future S&OP system in detail, even though the concept had not yet actually been implemented. Therefore, a viable middle ground had to be found that would map the system in an Excel model so that the functionality of the concept could be demonstrated in sufficient detail.

The concept was comprehensively tested over a period of weeks within all the departments involved, right down to the lowest working levels. To this end, (online) workshops were held in which employees were able to provide feedback and ask detailed questions about the impact of the integrated S&OP process changes on their daily work activity, and how it would benefit them on a day to day basis.

A high level of cooperation on the part of the customer, which was fully motivated to solve the challenges it faced, helped ensure the success of the project. The key to achieving the favourable outcome of the first project phase was certainly down to the very detailed nature of the dry run of the concept. This allowed the whole project team to buy into the concept from the beginning and to dispel any concerns about the system’s functionality on a practical, day to day level.

In addition to the complete development of the initial concept, ROI-EFESO also supported its implementation for more than six months, so demonstrating that it actually worked.

Despite the significant improvements already achieved, there are still further options for continuously developing the planning process. In particular, the demand sensing function in SAP IBP could play an important role in the future. Demand sensing is a forecasting method that uses mathematical techniques and near real-time information to create accurate demand forecasts based on current supply chain conditions. This can optimize medium-term planning for the coming months by adding a short-term time horizon of current customer orders. This would enable the company to react even more flexibly to order fluctuations in the future and be better placed to solve quota problems, as discrepancies between planning and actual customer orders would be flagged up more quickly.