When Metsä Tissue started the implementation of a common tactical demand and supply planning process in September 2003 it was facing a situation in which the results of sub-optimal planning and insufficient resource utilization had become obvious. Some effects could be felt directly by the customers, for example insufficient delivery accuracy in growth markets, limited ability to increase the sales volume, and the need to turn down local deals due to local capacity bottlenecks. This was even worse since excess capacity existed at global level which resulted from low capacity utilization at other locations within the Metsä Tissue supply network.
The reasons for these inefficiencies could largely be attributed to the internal situation. On the one hand, Metsä Tissue was lacking common planning processes at corporate level. The local units optimized planning and production based on their own needs – local thinking was the rule rather than the exception. On the other hand, Metsä Tissue was lacking a planning system with the ability to consolidate information from the different ERP systems that were in use.
Metsä Tissue brought Capgemini on board to help to design and implement an integrated solution for the supply chain processes including demand planning and capacity planning. With its SCM project the enterprise wanted to support sales growth, sustain delivery accuracy, improve demand planning forecast accuracy, and decrease supply chain costs.
Eliminating local thinking
Sales growth for example could be improved by shifting the focus from tactical planning at mill level to corporate group level and by balancing production between plants. In order to enable this, clear rules and a framework for planning optimization had to be created. However, such a change first of all required a solid business case to explain the benefit to all stakeholders. Besides that, a number of change management measures had to be defined to involve key people in all regions and all markets at an early stage, create roles and responsibilities in a global, dynamic network, and anchor decisions in a democratic way. A strong sponsorship at top management level was also a must.
Apart from the people side, the new solution had to be able to integrate a selected platform for Enterprise Application Integration using information from SAP R/3 and non-SAP ERP and reporting systems. However, technical functionality was just one dimension of the decision. The competitive position of SAP in the SCM market was also carefully assessed – with the result that the track record of SAP in the consumer goods industry was seen as convincing and SAP was recognized as a viable independent vendor with a very strong SAP partner network. Last but not least, an assessment of the total costs of ownership resulted in a positive decision to go with SAP once more, after the positive experience Metsä Tissue had already had with SAP R/3 in its German subsidiary which also allowed the company to leverage on the existing license agreement.
Get the process started
Processes were developed for tactical demand planning and supply planning with most process steps being based on mySAP Supply Chain Management. Specific process steps that were supported by the Demand Planning tool within SAP Advanced Planning and Optimization (SAP APO) included statistical forecasting and campaign planning as well as the handling of assortment changes. However, the most value in SAP APO Demand Planning was seen in the consolidated view in interactive planning, which offers a lot of flexibility in viewing data at various levels, units, and time buckets. For Supply Planning, the main process steps that were deployed and supported by SAP APO Supply Network Planning were the multilevel heuristic to calculate production requirements besides capacity leveling for converting lines and base paper machines to perform capacity planning. Capacity planning is based on a multi-step process to generate a feasible plan including evaluation of capacity at country level with subsequent adjustments of production location, capacity (for example additional shifts), and production portfolio (for example introduction of “balance products” which can be produced in more than one location to improve capacity utilization). Metsä Tissue also wanted to base decisions on costs for which a specific cost report was created. This will also prove helpful for a possible future extension using the SNP optimizer, one of the planning tools within SAP APO Supply Network Planning.
To support tactical demand planning and supply planning a comprehensive matrix was created in which the exact roles and responsibilities were defined for every process step. In order to measure the process, KPIs were designed, the most important of which are related to forecast and delivery accuracy and plan versus actual comparisons. Specific “planning documents” were created to ensure that people get all the support they need when running their part of the process (“checklists”) and to ensure efficient communication and decision making with documents describing the results of planning (“reports”). An example of this is the report used to support the corporate supply planning meeting which includes all important data on capacity utilization and production mix from the last month up until three months in the future to control the local planning process at corporate level.
Different implementation approaches
The implementation project was planned and started in September 2003 with a pilot phase followed by the rollout. The design of the common template process covered 95 percent of business requirements of the Consumer & Away-from-Home business units and about 70 percent of requirements of Baking & Cooking and Table Top business units. With the extended pilot phase, Metsä Tissue first wanted to test all the interfaces, and second ensure the acceptance of future users. Therefore, during the pilot phase tests, the data volume had to be representative of a real go-live and full integration had to be demonstrated. During this four-month period the tactical demand and supply chain process was mapped, and deliverables such as roles and responsibilities, KPIs, and a change management plan were designed.
Metsä Tissue chose a number of different approaches for the subsequent rollouts. For example, in the Consumer & Away-from-Home business units, the new SCM template was rolled out country by country. With this procedure, Metsä Tissue split the workload for user training, tests, and data migration from various ERP solutions into easily manageable work packages. For each rollout, SAP APO Demand Planning and SAP APO Supply Network Planning were implemented at in parallel to keep the momentum of the pilot project going and achieve quicker time-to-benefit. The global rollout for the Baking & Cooking business unit happened in parallel to the Finnish rollout of the Consumer & Away-from-Home business units and was preceded by an extended preparation phase to capture and address specific requirements which were not included in the pilot phase.
Firstly, it was a good idea to start up the planning process, i.e., the communication, meetings, thinking, as well as people assuming their roles even without the system being in place. Therefore, Metsä Tissue had a head start after go-live. Secondly, it is of enormous importance to have high quality data to feed the demand and supply planning process – especially if mySAP SCM uses input from different ERP instances which have not been linked systematically before. For this reason, a complete and early assessment to standardize master data is strongly recommended. Even though Metsä Tissue knew this, many of the problems that occurred in the project were related to poor master data quality in the ERP systems. Last but not least, Metsä Tissue had to find the right balance between automation and manual effort in the planning process. For example, when trying to increase the forecast accuracy of new products, it became clear that the interplay of the product change management process and the operative planning process had to be improved.
Now that process and system have been live for a year, Metsä Tissue profits from a delivery accuracy of at least 98.5 percent, especially in the growth markets. The enterprise actively bids in more deals. The demand planning forecast accuracy was improved to more than 80 percent. Utilizing the paper mills by 100 percent supports Metsä Tissue’s sales growth. The SCM solution decreases supply chain costs by reducing stock to less than 14 days of inventory. The increased visibility of a common set of key performance indicators focuses on improvement areas and facilitates analysis and benchmarking. With mySAP SCM Metsä Tissue established a tactical planning network for the whole company. Decisions that were big and complex before are now solved by a planning group with clear goals, roles, and responsibilities. What was previously a planning process with a cycle time of more than one month has been shortened to 13 working days.