In my previous blog I shared some of the typical areas where forecasting improvement opportunities may be found. Before taking a deeper dive into what these are, and what to do about them, it is important to first take a moment to reflect on the purpose of a forecast.
A forecast should never exist simply for the sake of it. There is no need for a forecast if there is certainty about the future. I know Summer follows Spring; I have no purpose for a forecast that confirms it. There is also no purpose to a forecast where I control the outcome. For instance, I have no use in a forecast that tells me how much I will spend in the grocery store, when I decide what goes in the basket. There is only a need for a forecast where there is uncertainty and there is a clear purpose.
Failure to consider the purpose of a forecast is a mistake that is made commonly when thinking about forecast improvement. There is a tendency for practitioners to think in tactical terms – will the initiative improve accuracy or reduce bias? Very rarely is there thought (or it is taken for granted) what the purpose of the forecast is and how it contributes to the delivery of the organization’s overall mission. Typically, organizations have a formal mission statement that describes the core business ideology and its aspirations for the future. Paying attention to these statements is a critical first step in understanding what forecasting improvements need to support.
Once the purpose is established it is then important to consider the characteristics of the organization. What products or services it provides now and expects to provide in the future? Who are the competitors, what is the speed of change in its industry or market, what are the growth prospects?
The size of an organization can often be a very important factor to consider. Typically, the larger an organization the greater likelihood that it suffers from functional silos. These can not only be barriers to the flow of information, but also create misaligned priorities and some organizational politics. It can also result in dueling forecasts, which can not only be an inefficient use of resources but can create confusion and ineffectiveness. Symptoms of this can often be heard in meetings; “that isn’t my forecast” or “I don’t know where those numbers came from”. The size of an organization also can often point to a large and complex product and service portfolio, a broad set of customers and extended value-chain.
If an organization is a global one, with multiple legal entities and business units and operates in countries with different languages and cultures, the challenge becomes even greater. This is amplified where decision rights are decentralized. The overlay of cultural differences and language barriers over functional rivalries requires thoughtful consideration when designing solutions.
For organizations that are interdependent on others, perhaps they are a supplier to another, consideration of factors beyond the organization itself may be required. As an example, an organization supplying ceramic capacitors for use in specific electronic devices should focus improvements efforts broadly and take into consideration the product lifecycles of the items they go into. The same applies in reverse, any organization that is critically dependent on another for raw materials or services must consider them in their plans.
The growth ambition of an organization is a critical factor in how to shape improvement efforts. One experiencing rapid growth is likely to require a different approach to one that is either in decline or focused on defending share. To support an organization that is growing rapidly it may require greater emphasis on improving long-range or strategic forecasting capability. One more focused on retrenchment may get greater benefits from improved short- or mid- term capability.
In many instances an emphasis on growing a business may go hand-in-hand with the delivery of a high-quality service, perhaps at the expense of it being initially cost-optimized. Conversely, a business in a more mature market, where profit margins are tighter because of competition, may require cost leadership. In some instances, a balance of the two may be the preference. In each instance the forecast improvement efforts should reflect these priorities. In an environment where cost leadership is the priority, a focus on automated approaches may be most appropriate. A service leadership priority may lend more importance on higher fidelity work, perhaps with a greater emphasis on data science and analytics with a focus on elimination of even the smallest errors.
In highly competitive markets, it may often be strategically important to retain or grow share through price discounting. The actions of competitors in response can often further complicate matters. External factors can clearly impact the effectiveness of forecasting processes. If an organization has relied on time-series forecasting methods in the past to create forecasts, but now is experiencing competition, focus on regression-based methods and collaboration with sales and marketing might be a response.
Organization characteristics and sample forecast responses:
The final considerations that are also sometimes overlooked is the need to define what success looks like and whether an initiative is a quick fix or long-term solution. One significant trap is to automatically assume that the goal is to be “best-in-class” or “great” and start a costly and over-engineered improvement initiative. It is sometimes ok to be “good”. That may better support the overall organization objective. Additionally, it should be perfectly acceptable to look for “quick and dirty” solutions. Not all initiatives have to be perfectly designed and built to last forever.
Crimson & Co is a global management consultancy that specializes in operations transformation with specific competency in forecasting and supply chain planning. For more information on how we can help you with your transformation journey, please contact me at firstname.lastname@example.org.
To see Simon’s first post in this series, Forecasting: future imperfect. Why forecasting is crucial and what we can do to improve
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