Challenges with Excel When Building a Demand Planning Process

Gartner estimates that by 2020, 60% of revenue in supply chain dependent industries will be driven by digital business. What this essentially denotes is that the congruence of people, business, and process (or things), is ever-looming.

Image by: Arkieva

Okay, let’s be honest. This is not a new concept.

Most businesses today, employ some degree of IT data management or automation to eliminate manual processes and are heavily invested in creating a digital supply chain. For manufacturing businesses, successful companies consistently strike the right balance between customer demand and supply planning through the meticulous implementation of internal and external processes and systems.

They leverage the power of planning, collaboration, communication, market intelligence, decision-making, and risk mitigation. The decision-making and planning without the right technology solutions leaves businesses without the actionable insights needed to stay ahead of the curve.

Irrespective of the scale of business, companies need to regularly review their processes and systems and decide the most suitable tools and applications to cater to their business requirements. Here’s where Excel comes in.

Versatility of Excel in business world applications

Excel spreadsheets have become an integral part of most businesses across the world, irrespective of geographical location or the nature of the business. Most computers and smartphones are pre-loaded with Excel, which makes it one of the most accessible application across the globe. Excel is widely used for data entry, basic calculations, data sorting and analysis, creating forms and questionnaires, presentations, creating graphs and charts, budgeting and accounting, planning and scheduling, etc.

Excel has an excellent user-friendly interface and its basic functions are easy to learn. There is plenty of online and offline self-help material available for learning Excel. Representing data tables in graphs and charts is quick and easy. Advanced users can exploit the higher functionalities of Excel like rule-based formulas, conditional formatting, pivot tables, macros, etc.

Dynamic nature of Demand Planning

Demand Planning process generates demand forecasts based on various historical data and relevant business information. Historical data and statistical analysis are used to develop long-range estimates of expected demand. Demand Planning also analyzes the impact of marketing promotions, new product launches, and other business plans. Pricing discounts, rebates, market intelligence, and product discontinuations are also considered.

In today’s world, demand signals are dynamic and complex in nature due to multiple SKUs, wide distribution networks, multiple point of sales, varying geographical locations, customer demographics and seasonality. Huge amount of diverse and complex data is generated which needs to be effectively and efficiently considered in the Demand Planning process.

Normally, there are multiple Demand Planners that contribute to the Demand Planning process. There are individual Demand Planners for specific product categories, geographical regions and customer segmentation. Different inputs from these Demand Planners contribute to the overall Demand Planning process. This is where Excel starts to become limiting.

Limitations of Excel in Demand Planning Process

Excel is a great productivity tool and an excellent stand-alone business analytics and reporting tool. However, it has its own limitations which impede its effective implementation in the Demand Planning process. Excel is not designed for online collaborative work. A single Excel file can be edited by only one user at a time, which becomes time consuming for inputs by multiple users.

Merging multiple Excel files into a consolidated file is a difficult, time consuming task and is prone to inconsistency, errors and misreporting. The higher the volume of data in an Excel file, the slower the file size will process, leading to more chances for the data to get corrupt. Excel spreadsheets are also prone to human data entry errors and are vulnerable to deliberate manipulations due to inherent lack of controls. Excel is incapable of supporting quick decision making since the data might be outdated and inaccurate. It can also be very time consuming in getting the most up to date information from multiple users and summarizing the information for making business decisions.

Considerations for Demand Planning Managers

While Excel is a good tool for Demand Planning of limited SKUs with fairly steady demand and regional distribution; a Demand Planning Manager needs to evaluate the future business expansion plans, new product launches, new region expansion and marketing plans. In such a scenario, the existing Excel based Demand Planning process might not be able to handle the volume of data, scalability and running what-if scenarios for quick decision making.

Even without the need for flexible demand planning tool, one of the biggest risks that businesses face when managing planning data in Excel is often centered on the inability to transfer knowledge easily. In most business cases, there is often a “power user” who is highly versed on how every cell calculates, and the formulas being used. This type of planning process is often not scalable, leaves many businesses scrambling when their star Excel user is unavailable. In the end, Excel is great tool. In fact, most supply chain planning solutions like Arkieva adopt an Excel look and feel to make user adoption easy. It’s core limitations lie in the inability to the data redundancy, live data integration consistency, sharing and seamless collaboration needed for today’s digital business.

Enjoyed this post? Subscribe or follow Arkieva on Linkedin, Twitter, and Facebook for blog updates