In our previous blogs, we shed some light on how the standalone ERP systems are not enough to create a robust demand planning solution. In this blog, we will discuss the effects of SKU proliferation and its toll on the triple bottom gains for the organization.

The problem of SKU proliferation

Various research has proved that an organization can raise its overall market share by expanding its product selection and, thereby, appealing to a wider set of customers. The high product variety is said to stimulate sales as the products are matched closely to the needs of the customer. Though the expanded product lines bring additional revenue, it comes with the cost of managing the variety. These costs can be broadly categorized into the following:

• Manpower cost – additional workforce required to manage complex warehouse and supply chain
• Product stockouts – wider product range makes it harder to precisely forecast demand, resulting in mismatches between product supply and demand
• Operational performance – SKU proliferation can compromise operational performance

How should organizations then balance the objectives of capturing the market share by expanding the product lines without hurting the triple benefits?

Attributes based demand planning

Attributes are the unique characteristics of a product, process, service, or resource to highlight value or compliance to a customer’s need. For instance, consider Diamond, where the buying decisions are based on carat, color, clarity, cut. Whether a customer prefers to buy a diamond of high carat or the one with better clarity, one comes up with the best combination which he perceives to provide the best value for money.  From a demand planning perspective, the right combination of the attributes, namely, carat, color, clarity, and cut must be considered and made available at the point of sales. If the right combination is not available, there is a potential risk of losing the revenue owing to no sales!! This is a dynamic, and real-time problem that needs to be addressed in demand planning to prevent the leakage of revenue.

Besides diamonds, other products like electrical properties on high-tech components and chemical properties on specialty chemicals call for a more complex, algorithm-driven demand planning process.

Empowering users through attribute-based planning

A major hindrance in integrating SKU-based demand planning into an overall planning solution is the lack of user control afforded by conventional forecasting methods. In conventional forecasting, data is organized in a strict hierarchy in traditional dimensions, such as region and product, with a fixed sequence of levels.  The forecasts on demand will be limited in view to relatively broad and non-intuitive categories. This creates a forecast that is less accurate and less attuned to a manufacturer’s specific needs and targets.

In attribute-based forecasting, data is grouped based on common characteristics or attributes that are dynamically set by a user. For example, in the automotive industry, customer preference shifting towards SUV-like design or preferring a hybrid engine for better fuel efficiency could be set. When the data is displayed along these lines newer pattern or new sales potential would come up and makes the forecasting more accurate.  This view of customer preferences of attributes enables the decisions on product line expansion, possibilities of new product variations, and higher investments in growing product lines.

Adexa’s Collaborative Demand Planning machine learning capabilities can handle multiple attributes to provide the granularity required to accurately forecast the inventory while considering the traditional attributes like seasonality, trends, and geographical variations in demand. Through Collaborative Demand Planning features, organizations can realize their objective of capturing the market share without hurting the bottom line.

Table 1: Attribute-based planning benefits

Attribute-based planning is a tool that can generate accurate plans without the planner putting in the exact individual product details. A great amount of planning time is cut down by order of magnitude as the number of SKUs is reduced resulting in an executable and accurate plan. In our next blog, we will talk about how digital twins are a handy technology in mitigating supply chain disruptions.

References

Too Much of a Good Thing: The Impact of Product Variety on Operations and Sales Performance Article  in  Journal of Operations Management · May 2012