This whitepaper provides an overview of Optilon’s Sales & Operations Planning (S&OP) concept called "Continuous S&OP". As opposed to a monthly S&OP process, Continuous S&OP is defined through its ability to support decision making at any point in time, with up-to-date information always at hand. This requires a holistic architecture to support demand-, supply-, and production planning, as well as review with relevant stakeholders. One such stakeholder group is finance. Despite typical complexities associated with planning, like promotional activities or complex supply structures, this paper will discuss how we can automate underlying processes to a large extent, thereby supporting the notion of ”always up-to-date information”. This has three major benefits: I. faster decisions, II. less manual work, and III. significant operative benefits, such as more informed decisions and improved KPIs.

Purpose

The S&OP process is primarily a decision making process. Traditionally, this has meant that decisions are made once a month, as a part of an ”executive review” or in any of the underlying processes. The infrequent nature of decision making often leads to a gap between the S&OP process and underlying operative processes. The S&OP process starts ”living its own life” while operations struggle with the day-to-day realities of managing demand and supply in an unpredictable environment.

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Do things need to be done in this way? No. With modern technology and a new process design, we can ensure information is always up-to-date, and decisions can be made at any point in time, whenever necessary.

Aligning planning and execution

Automation lies at the core of the Continuous S&OP. Many tasks that were previously done manually, are now supported by automated solutions. Focus is shifted from manual work, such as keying in numbers or trying to assess trade-offs in spreadsheets, to value-adding work. This can involve, for example, what-if planning to understand implications of different courses of action. With automated processes, we are much closer to always up-to-date information, bridging the gap between planning and execution.

This has different implications for different parts of the S&OP process. Below, we look at this from a practical stand-point for demand-, supply-, and production planning. Key decisions in the S&OP process can be made at any time, but at a minimum once per month in the ”executive review”.

Statistical forecasting is the starting point for demand planning. Kronans Apotek, a Swedish pharmacy chain with more than 300 pharmacies, found themselves in a situation where a lot of manual work was needed for managing orders and shelf inventory. Despite the effort, results were not satisfactory. After centralizing supply chain planning, less than 5% of the previous workforce control more then four million item/location combinations, in a process where forecasts, replenishments, and shelf inventories are re-balanced once per day. Product seasonality and campaign effects are accounted for in the statistical forecast. Focus has shifted from manually managing forecasts and orders to

understanding, for example, which campaigns provide the best return on investment. The final commercial forecast is a representation of future demand, including complexities brought about from campaigns and seasonality.

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A key part of the process at Kronans Apotek is to plan product availability and inventory. This is an often overlooked part of demand planning, something we discuss further below in the ”measuring performance” section.

In summary, the Kronans Apotek example shows how a large quantity of stock keeping units with particular demand complexities, such as campaigns, can be managed so that information is always up-to-date. In this set-up, there’s no need to separate ”planning” and ”execution”. Other similar examples, across different industries include Thule for durable consumer goods, SKF in engineering, as well as Findus and Lantmännen in the food and beverage industry. Typical for all of these examples is the ability to cut inventory by 10-15% or more while maintaining or improving service levels.

A key feature in supply planning is to understand alternatives and trade-offs, driving decision making in the Continuous S&OP process. Analyzing trade-offs, such as alternative cost structures, is a daunting task. In an environment with hundreds or thousands of products, many suppliers, and several warehousing and manufacturing alternatives, the number of alternative outcomes is often measured in the hundreds of thousands. While this can often be simplified, true support for decision making frequently relies on disperse spreadsheets and gut feeling. Better support is needed, where the underlying calculation is automated and focus is shifted towards analysis and what-if planning.

Tine, the major Norwegian dairy company had a very practical problem: they are obliged to buy given amounts of milk from their owners, milk farms. Milk is a very versatile raw material, ending in up in products with a diverse set of characteristics such as different shelf life, margins, and production lead-times. Aged cheese is very different from yoghurt, which is different from fresh cream. Accounting for market demand, and the seasonality that also affects supply of milk, what should be produced and where? The solution was to build a virtual model of Tine’s supply chain, including production locations, storage locations, production rules, recipes (Bill-of-Materials), suppliers, and customers. Long-term production plans are re-balanced at least twice per month. The virtual model allows for quick optimization, i.e., finding of the optimal productions set-up under any conditions. There’s a link to financial control as the optimization is cost driven, enabling an optimal set-up to maximize profit or minimize cost. While this provides confidence in terms of day-to-day operations, an even more important feature is the ability to change underlying

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parameters. What if demand increases? What if a production line breaks-down? What is the cost impact of increasing capacity or moving production to account for constraints? This ability for what-if planning is a crucial feature in the Continuous S&OP process. With a virtual supply chain model at hand, this analysis can be performed at any point in time, allowing for decisions to be made when needed. Other similar examples from different industries include TetraPak for manufacturing, Sandvik in engineering, and Ericsson in the high-tech space. Significant savings have been possible through better planning, while at the same time speeding up analysis and enabling what-if planning to drive further savings.

The crucial distinguishing factor in near-term production planning is the ability to automatically create an implementable production plan that accounts for constraints and rules in production, as well as material availability. Any orders that cannot be fulfilled are automatically highlighted. This capable-to-promise ability allows for decision making on customer prioritization, if so required. It is also a key input for longer-term supply planning. As with the examples above, automation again allows for an always up-to-date plan. Key customers that make use of these abilities include the engineering companies Sandvik and ABB, the food and beverage company Absolute Vodka, and the durable consumer goods company Thule. Benefits are two-fold, on the one hand side this typically allows for better throughput in production, and on the other hand it enables what-if planning also in the near term production scheduling window.

Supply- and production plans that incorporate the latest market conditions enable decision making at any time, bridging the gap between planning and execution. Supply- and production plans are also a key input for procurement, enabling tight integration of suppliers to the Continuous S&OP process.

Integration between planning engines as well as source systems (e.g., ERP, product data management) is crucial. The Optilon Integration Layer (OIL) is a central information repository,

taking care of integrations towards, and between, different solutions. A key benefit is that user interfaces, visualizations, and reports can

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be created for different stakeholders in the Continuous S&OP process. Another key feature in OIL is the conversion between different data elements. The means ability to work with different timelines (monthly, weekly, daily), on different geographical hierarchies, or on different product levels (such as SKU and product family), and with different units of measure such as financial measures. This puts in place financial control to further support decision making in the Continuous S&OP process. With the Optilon Integration Layer and always up-to-date information, planning and execution is truly bridged. The notion of a ”monthly S&OP” with decision making tied to a calendar then becomes obsolete.

Measuring performance

There are several relevant KPIs for demand, supply-, and production planning, as well as for the S&OP process itself. Rather than focusing on these, an easier approach is to highlight how the Continuous S&OP process is different, and what not to measure: forecast accuracy.

Forecast accuracy has an indirect effect on performance. Poor forecast accuracy has a few possible consequences: either it is compensated for with higher inventory (or, for example, bigger flexibility in production or faster deliveries) or lost sales. These have a direct impact on

performance; there are capital costs tied to inventory, higher costs associated with flexibility in production or faster deliveries, and lost sales means a decrease in revenue and unhappy customers. As such, capital tied to inventory, production costs, and service level are the key KPIs to measure. An increase in forecast accuracy on the other hand, is only visible on the bottom line if it affects any of the other mentioned KPIs (e.g., inventory or service level). The key thing to remember is that an improvement in forecast accuracy does not automatically lead to improvements in, for example, inventory or service level. Other measures are needed to manage this link. Therefore, measure the outcome, not the starting point. More details on the management of availability and inventory in a new way is available at www.optilonsolutions.com.

Perhaps not a KPI in itself, another key feature that needs to be assessed in the S&OP process is the availability of data for decision making. Is the information at hand

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always up-to-date? Are we making decisions based on the latest status? Do we have all the alternatives mapped out?

How do i get started?

Optilon is a developer independent partner for understanding your S&OP requirements. The starting point is to understand your environment and come up with a plan for improvement. This involves understanding and determining roles and responsibilities, and ensuring management buy-in for the new process. At the same time, availability of data is assessed and new processes and tools are put in place to enable the Continuous S&OP. There is an old ”truth" saying that processes should be put in place before tools. This is fine, if the abilities and performance of modern supply chain optimization tools are taken into consideration when designing the process. In other words, don’t start by assuming the text book definition of a monthly S&OP is the only way forward!

For more information, contact:

Henrik Nyman, Country Manager, Optilon Finland

henrik.nyman@optilon.fi

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Optilon AB Hantverkargatan 5F 112 21 Stockholm Sweden www.optilonsolutions.com

About Optilon

Optilon creates business advantage through solutions based on leading supply chain applications. Our passion is to help you ask the right questions on how to improve your supply chain.

We deliver proven results by combining your knowledge with our experience and solutions. That’s why we independently select superior technology that leverages our competence to support you, and provide our services in all Nordic languages. We support companies in both manufacturing and trade.