The demand planner serves as the unbiased arbiter in the S&OP cycle. This role involves taking a cold hard look at manufacturing, logistics, marketing, sales and finance to paint an objective picture of demand.
A strange blend of cross-departmental cooperation, leadership and statistical analysis, demand planners are the rarest of breeds. This unique combination of analysis, leadership and a can-do attitude is a prized commodity.
The rarity of the skillset means strong demand planners are hard to find, and harder to retain. And that is a major problem, because when demand planners leave they take their knowledge with them, making sustainability of knowledge a critical issue for many forecasting teams.
The chances are that right now, your demand panning team is facing some kind of sustainability gap.
Overcoming Knowledge Gaps at Unilever
My experience at Unilever has taught me that the biggest and most frustrating part of demand planning is when an experienced demand planner leaves. When this happens, the team has to spend time reinterpreting the data that was under the remit of the departed planner, and subsequently turn that data into knowledge that can be acted upon. Long meetings to reestablish the correct range of uplifts or cannibalization of each promotional activity is a common scenario – knowledge that was known that is now lost. This is frustrating not least because it is entirely unnecessary. Learning something that was already known is, after all, absurd. How then do you fill this knowledge gap, ensure continuity and avoid wasting time when a demand planner leaves or moves to other product categories?
The Right Tools to Hold and Share Your Greatest Commodity: Company Knowledge
What you need to mitigate the damage of demand planners leaving and to plug the sustainability gap is a mechanism for sustainability of knowledge. We’re talking about the right tools to collect and store information that can be held centrally and maintained regardless of who comes and goes within your team. Something that would ensure that whichever employee leaves, their knowledge and insight remains easy to access by whomever takes over. What we use at Unilever is a Promotional Library. The Promotional Library is our tool for Knowledge Management (KM). KM is the planning, organizing, and controlling of people, processes, and systems in an organization to ensure that its knowledge-related assets are improved and effectively employed.
KM is nothing new, but remains an under-exploited tool in S&OP. Mature S&OP environments are embracing this kind of tool to maintain company intelligence – but this should be standard operating procedure for all demand planning teams regardless of size or maturity. After all, forecasting is very much a company intelligence process and without stored knowledge accessible to everyone, there is a serious hole in your approach to forecasting.
The Difference Between Data, Information and Knowledge
Data: These are your facts in their simplest, unexploited form, most often relating to sales, invoices, inventory etc. This is the raw data collected from other departments.
Information: This is your findings based on analysis of your data. You turn your facts into something from which inferences can be made. This can be trends of sales or relationships between sales performance and promotions, for example.
Knowledge: This is insight gained from interpreting your information based on a thought process, context and experience. This knowledge forms the basis of an action plan and is the ultimate goal of forecasting: turning data into something actionable and useful that will add value to the company.
Knowledge, or marketing intelligence, is typically retained in the heads of demand planners, or in files on their computer. Rarely is it centrally stored for incoming demand planners. Knowledge is the ‘end product’ of forecasting that allows for strategic decision making. Therefore, it must be treated as a commodity, and not be allowed to disappear when personnel changes are made.
Characteristics of an Effective Promotional Library
It must be enhanced in terms of depth and consumability and made easily transferrable. Even if companies maintain sales data across extended horizons, leading indicators and qualitative data are hard to trace back as they are stored in different locations that get lost through time. The execution of KM then comes in the institutionalization of a promotional library that computes, documents, and secures all the necessary information to accelerate and elevate the standard demand review. This means you can check across categories, activation types, and time horizons with ease – keeping you from extensive meetings and aspirational forecasts.
Practical Benefits of a Promotional Library
Through excellent data-driven MI assumptions, value is added to the business by:
(1) Simplicity and agility of decision-making
Even in the face of new territory, having data (across not only time horizons but also categories) helps in proper benchmarking for better qualifiers than rough guesstimates.
(2) Improving profit margins through healthier inventory levels
Higher forecast accuracy, in principle, leads to improved inventory – translating to better liquidity and higher profit margins.
(3) Improving Customer Service Levels (CSL)
Demand management is an enabler in the goal of every supply chain: bringing to the customer the right product at the right place at right time.
(4) Continuous Improvement in Forecasting Metrics
Data is a double-edged sword. Deeper data can translate to better assumptions, and iterations along the years refine hypotheses about the company and its DNA.
(5) Consistency and Sustainability
Organizational Learning is achieved through maintenance of both tacit and explicit knowledge to avoid disruption caused by knowledge gaps.
Embracing Instinct and Nuance with a Promotional Library
One area that may seem anathema to the cold, hard statistical analysis of demand planning is the nuances of forecasting, developed through personal experience. This personal experience is what drives insight into demand, and enables demand planners to understand the quirks of certain SKUs. It takes time to understand the impact of month to-month business activities and customer specific history. Demand planning teams must strive to retain this insight, as it allows for inferences to be made which is the key differentiator in achieving robust forecasts.
We mustn’t forget that demand, just like human behavior, cannot always be rationalized with statistical models. In that sense, forecasting is an art. Intuition may not come naturally to the quantitively minded, but its value in painting an accurate picture of future demand must not be underestimated.
I’ll be speaking more about how Unilever sustains demand planning & forecasting knowledge at IBF’s Asia S&OP & Forecasting Conference in Singapore this month. I would be happy to further discuss this topic in person.