Despite an environment of high interest rates, economic uncertainty and continuous geopolitical friction, consumer confidence unexpectedly rose in May after three straight months of decline. This served as another reminder for companies in industries across the board that historical consumer patterns have changed over the past few years, and this change is prompting business leaders, and their demand planning teams, to reassess their strategies aligned to today’s end customers.
As companies navigate these new conditions, implementing advanced demand forecasting capability is more crucial than ever. With so many options available, where a company begins is important and should consider business imperatives and nuances. Data has never been more readily available, but it is useless if it cannot be organized or analyzed and pointed at the pre-defined business problem. There are new and emerging technologies becoming more readily available in the market; all of which have a precursor to success that is defining the business problem.
For companies looking to begin building or improving their demand forecasting, here are three ways to create a competitive advantage and grow closer to the end customer.
Use Your Data as a Compass
Companies that rely solely on their historical data from past demand and orders are quickly realizing that it’s no longer an accurate way to predict future customer demand. This realization has led to an “outside-in” approach to demand forecasting. Fostering a stronger collaboration with the company’s retail network or supply chain trading partners closer to the end customer means access to trends and consumption data that is a leading indicator of upstream impacts to future demand. Finding an efficient way to incorporate this data into planning workstreams as a value-added insight, is a great initial step to better visibility and incorporation of external factors into an organization’s demand plan.
Focusing on the accuracy and consistency of master data and attributes that categorize or group products into meaningful segments is required to take advantage of any of the new technologies and algorithms in the market today. This includes a rigid governance process that ensures the validity and quality of the master data on an on-going basis.
Aside from a company’s supply chain network and partners, there are a few additional ways demand planning teams can look externally to find pertinent data for their organization. Publicly available external data streams such as economic indicators that are drivers or influencers of demand can be incorporated into algorithms that can efficiently identify correlations between sales and the external data set to better predict future sales.
Also, evaluating and investing in risk management platforms can help demand planners prepare accordingly as they can provide alerts about major events like a cyberattack on a supplier’s warehouse. Efficiently incorporating external data can be a powerful way to take demand forecasting strategies to the next level.
Integrate the Right Technology
Only once a company has an organized, wide-ranging master data set can it evaluate the right technology to help its overall business objectives. For companies looking to integrate the latest artificial intelligence or machine learning tools, their leaders must ask, “What’s the business problem right now that cannot be solved with existing technology?” Sometimes, it’s a matter of turning on functions within platforms that have already been purchased. Other times, new technology is needed. During this evaluation, companies will also need to prove they can implement what is needed, while ensuring demand planners will be able to harness whatever new tool or technology is being considered so that it addresses critical business challenges and opportunities. If teams do not understand how to apply a new tool, function, or process, they will not trust it and ultimately, they are not likely to use it.
Invest in Your People
Finally, data will not be optimally incorporated, and technology will not be seamlessly integrated without the support of the right talent. Having a dedicated team that understands the business model and its objectives can be the difference between being self-sufficient in demand planning. For a company to become truly self-sufficient, it requires a long-term investment in bringing in new talent as well as creating strategies to train and retain existing talent. No tool or leading-edge technology will be fully maximized without the business team and their collective ability to understand the technology and its required inputs and apply the use of the tools in a way that is mapped to the business outcome desired. The skills required to achieve this are a blend of technology and business acumen, coupled with applied critical thinking.
After successfully applying these three steps, the sum of all of the benefits is visibility—not just visibility of patterns and trends, but visibility to the entire supply chain including the end customer.
In today’s rapidly evolving environment, gaining a competitive advantage by more accurately forecasting consumer behavior can help most of a company’s downstream decisions, such as how much product to make, how many people to hire, where to take risks on inventory and where to keep it. This will create a better estimation of annual sales. Therefore, no matter how surprising it is when consumer confidence unexpectedly rises or inflation continues to persist, a successful demand forecasting program—fueled by data, driven by the right technology, and led by the right team—will allow a company to know exactly what to do with its supply chain as a response.
