As shown in Figure 4, 41 percent of the companies surveyed reported that they are using spreadsheets for their S&OP solution. Nearly 30 percent of these companies have enterprise resource planning (ERP) solutions that are capable of doing S&OP demand and supply planning, but these companies have chosen to supplement with spreadsheets for their S&OP process. The main reasons cited by these companies are that their users are more comfortable using spreadsheets and that the ERP technology solution was too complex for them or does not provide adequate capabilities.
Although it is convenient to use spreadsheets, this strategy lends itself to multiple versions of the data and is rarely accurate or effective over the long term. This approach also does not lend itself to executive level inputs.
The vice president of strategic business processes at a leading food processing company talks about their technology architecture prior to implementing a leading S&OP specialist solution. "Our company is 88 years old and we ran our operations for 20 years using spreadsheets. Obviously we were able to sustain our business that way. Key issues that we faced with spreadsheets were:
- The amount of variables being able to take into consideration in the spreadsheet. We could only model a limited number of decision points within our spreadsheet solution. When changes of sales forecast happened, we paid the price on the inventory stock levels, increased production costs, and increased expediting costs.
- Also as global market became more complicated, we could not sustain the spreadsheet based process.
- Another issue was that there were a few gurus who knew how to handle the very complex spreadsheets and knowledge sharing was a problem.
Once technology solutions were put in place these problems got resolved. For example, overtime was reduced from 23 to 10 percent."
Why is Technology Important for Enabling Integrated Business Planning?
Aberdeen research finds that 78 percent of companies say that technology is either critical or very important for their S&OP process. There are several reasons why technology plays a critical role in helping companies achieve better S&OP results and move toward an integrated business planning process.
- Data management. Today's organizations often have myriad sources of data colored by many different perspectives — sales, customers, marketing, suppliers, manufacturing, logistics, and finance. Because this data tends to be present within disparate systems and are complex in nature, data management and integration capabilities are needed to ensure that data inputs are timely, complete, and are incorporated into the S&OP plan in an accurate manner (e.g., adjustments are made for differing units of measure, customer and item master inconsistencies, variable time horizons, and so on).
- Multi-dimensional goals and views. S&OP places the spotlight on different goals — revenues, margins, working capital, forecast accuracy, supply/demand match. Organizations need to look at the data in different ways in terms of aggregation as well as units. For instance, finance and sales typically look at the product family level and in dollar unit sales and manufacturing looks at unit level and end item SKU level. Creating multi-dimensional views of the plan that also support what-if analysis is something beyond the capacity of a spreadsheet process.
- More dynamic business processes. Faster and more frequent S&OP cycles are required to keep pace with shorter product life cycles, compressed order lead time requirements, and more dynamic demand. Technology enables automating these processes as well as decreases the times that S&OP planners spend on manual operations versus doing more productive work. More importantly technology enables the ability to rapidly react when real-life scenarios unfold in real-time like supply shortages, plant breakdowns, etc.
- More decision parameters. Involved in coming with the Integrated Business Plan which cannot be tackled by manual technology. Some critical decision parameters are overall margin, product family level margins, budget (financial plan), inventory, supply capacity, demand accuracy, service level requirements, etc. These decision parameters are often multi-dimensional and often involve attributes that may be different at different levels of aggregation, for example, demand accuracy at a product family level may be measured differently than the demand accuracy at a SKU level. These require support from technology to not only model but also to manage and monitor.