Product Excellence Through Modern PLM in Fast-Paced Markets
Modern PLM systems empower businesses to achieve product excellence in fast-paced markets by enhancing collaboration, agility and innovation.
Sales & Operations Planning (S&OP) and Integrated Business Planning (IBP) have become common best practices across all industries to cover the mid-term supply chain planning horizon. However, both have weaknesses in terms of effectiveness, efficiency, effort, and IT solution coverage. This paper addresses the need to transform current S&OP/IBP approaches to a truly information-based management process without temporal, organizational, and technical integration barriers.
No doubt, a company cannot prevail without anticipating the future development of its business and commercial environment. That is why mid-term planning spanning a horizon of, for instance, 2-5 years is a key prerequisite to timely make both reactive and proactive decisions to steer corporate development and to meet business objectives.
Consequently, regular cross-functional IBP/S&OP planning cycles evolved over the last decade as the most appropriate approach to derive mid-term plans: Depending on the business model and company size, the planning cycles, which are generated on a weekly, monthly, or quarterly basis, generally consist of a sequence of planning and decision steps like product review, demand review, and supply review, followed by internal reconciliation and a final business review. Though the naming of the reviews may differ, S&OP as well as IBP are decision-oriented and gap-closing processes that include all concerned business functions to meet business objectives and to result in a one-number plan.
In fact, all clients I know either run a variant of S&OP/IBP or plan to establish a company-specific Integrated Business Planning (IBP) process. No surprise that all advanced IT solution providers offer respective capabilities to process required planning and forecasting data.
Cross-functional cyclic integrated business or sales & operations planning has become the standard approach for mid-term planning, as key performance indicators, from forecast accuracy over production plan adherence to OTIF can be, for most business models, significantly improved. Nevertheless, despite its general success, this planning approach and the supporting advanced planning solutions come with some substantial weaknesses negatively affecting both the daily planning operations as well as the process and solution implementation:
The first major downside many companies are reporting is the high planning effort. This is not only causing substantial costs, but also, and even more critical in times of personnel shortage and war for talent, absorbing a significant number of planners and human resources, respectively.
In fact, this planning effort is, to a large extent, due to complexity, information loss, and the artificial breakdown of the planning continuum into different planning horizons, i.e., short-term/operational, mid-term/tactical, and long-term/strategic temporal segments.
IBP/S&OP review cycles appear to be simple and easy to apply. However, for many globally operating business models, reviews and the ‘feeding’ demand, supply, and production planning runs are being applied on local, regional, and global level. Moreover, if a company runs independently operating business units, the review cycles are applied to each unit. These kinds of multipliers are a major cause for the high (regular) effort organizations must take to achieve good planning results.
A significant risk of information loss comes from the fact that most IBP/S&OP planning processes are supported by time-series-based* data models of limited temporal granularity. The common reasoning for this simple and intuitive ‘how-much-do-I-sell-or-supply-in-which-time-bucket’ is that a data model with a weekly or, widely used, monthly bucket is anyway sufficient as forecasting cannot be more precise in the mid-term horizon. But this may not be correct for the entire mid-term planning horizon:
Many enterprises, applying for instance a planning horizon of 1 – 5 years, need to enrich the rolling forecast data of a specific product-customer/location combination on a more detailed level over time. While monthly granularity may be sufficient in the far future (e. g., years 4-5), the information on a weekly or even daily bucket in the nearer future is required to ensure timely management of capacities, sourcing, and supply, and to mitigate bottleneck situations.
Consequently, if low granularity, for instance by monthly buckets, spans the entire mid-term horizon, information cannot be adequately ‘attached’ to the plan. Sometimes it feels like a time-series-based data model is a relic from times when computing power did not allow high granularity and/or the application of an order-based* approach over a long period of time.
* For more information on order- versus time-series-based planning, please have a look at this article: IBP Time Series, IBP Order-Based? What is this?! – CAMELOT Blog (camelot-group.com)
Business information is largely not based on a pre-defined data model but rather on unstructured textual information like reasonings, rationales, and understanding of business and forecast development. This unstructured information is essential to capture risks, opportunities, assumptions, and reasons, and it makes S&OP and IBP truly decision-oriented, gap-closing processes. However, it cannot be adequately captured by time-series as well as order-based data models.
If unstructured information refers to one bucket, it can be attached, e. g. as a comment. However, as soon as this information explains business events and developments on an aggregated level, and moreover, as soon as unstructured information must be aggregated, most data models can no longer support. Consequently, numerous companies running IBP or S&OP capture information aside from the advanced planning solution, many are still and for good reason using Power Point, Word, or Excel applications.
S&OP and IBP are certainly proven planning approaches based on best practices across all industries. Nevertheless, there is room to improve both the mid-term planning itself as well as the way the entire business and operations planning horizon is structured and managed.
I conclude that future operations and business planning approaches and their IT solution coverage should be based on one temporal planning continuum serving all short, mid and long-term planning needs. They will therefore be based on one data and process model avoiding bucket-induced information loss and supporting the processing of unstructured management information across all functions and across the entire planning horizon.
Assurance: This paper is solely based on own experience and has been created without any support of KI tools like ChatGPT.
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