Demand Planning : Your Guide to Demand Planning & Process
Whether you are manufacturing electronics or garments, or whether you are providing financial services or catering services. The starting point for all business is market demand – how many people will buy my products/service in the coming period?
Demand planning is the science of determining how much goods should an organization manufacture given the market demand, available inventory, and the production capacity such that no buyer goes unsold and they are left with minimum or nil inventory on hand. Fluctuating demand, supplier bandwidth, and production constraints- the three core factors that determine how much will be delivered to the customer by when. Demand planning is a system which brings together these 3 elements in a collaborative and transparent manner, overlays it by advancements in predictive modelling to improve their demand accuracy on an ongoing basis.
What Is Demand Planning & Its Importance?
If one does not do demand planning, there are two consequences – either they manufacture less and lose potential business or they manufacture more and are left with excess inventory. Both are not the outcomes any organization would want. While it’s not possible to be 100% accurate, the goal of demand planning is to come as close as possible to the market condition based on customer demand, market dynamics, historical data, stock in hand, and manufacturing constraints. So while the sales teams will be close to the customer and provide their view of how much they expect their customers to buy, Demand Planning role takes a deeper view of the expected demand and adjusts it for the factors mentioned above and develop the final plan. This final plan becomes the basis for supply-chain and production plan.
Demand planning sits in between sales and supply planning and plays a key role in ensuring organization is balancing its objectives between meeting demand and minimizing inventory.
Benefits of implementing demand planning in your business
Demand planning is probably the most challenging business objective to meet. But when done right it provides the best leverage an organization can have. The direct benefits include - Revenues or no business loss, and lower inventory holding costs. You are producing exactly what the market wants, nothing less .. nothing more. Indirect benefits include – customer satisfaction and repeat business. Because you are able to provide the customers what they want, and when they want it they will be satisfied and happy. This will lead to more repeat business which is generally serviced at a lower operational cost. Plus new business with other customers. Downstream impact - improved cash flow, reduced working capital requirement, and better utilization of plant capacity.
Conversely, if you are running your planning on spread sheets today, chances are that the demand planning team is wasting 60-75% of their time in activities such as data collation, version synchronization, macro manipulation, scenario creation, and cross-functional follow-ups. Impact - lengthy cycles, plan errors, static plans and most importantly stale analysis. Not to mention long working hours. Demand planning systems take away these mundane tasks and enable accelerated planning cycles, instantaneous P&Ls, reduced forecast errors, real-time visibility, and multi-dimensional analysis. And more.
Components, Steps, Common Challenges in demand planning
To accurately predict the demand for the forthcoming period – this is the objective of the demand planning team. And a complex one. To begin with, there are at least 4-5 different functions involved in this process – sales, demand plannings, supply planning, production, and delivery. Imagine if sales teams promise deliveries without knowing the stock and order status. Or the demand team creating the plan without knowledge of upcoming orders. Or the manufacturing team producing based on their available capacity alone. All the above scenarios will lead to unintended consequences – non-availability of goods for sale or over production of stocks not in demand.
Thus the planning process entails all the relevant teams collaborating to come up with a consensus plan. The process starts with the sales teams providing their sales forecasts for their territory/ customer. However they may not be able to give it at the grain and accuracy that is required. Plus they may not have knowledge about other factors which matter e.g. historical trend, seasonality, current inventory, and production schedule. E.g. salesperson A has the habit on over-estimating, territory-B is always shows slower offtake in Q2, or RM101 has a lead time of 6 weeks which will impact 8 SKUs. The demand planning team will look at these and many such variables in detail to come up with their demand plan.
A key component is the ability to develop multiple “what-if” scenarios in order to arrive at the final plan e.g. what if we increase the demand for SKU-145 by 1.5%, how will it impact other SKUs. Or what if we reduce the available capacity by 5%, how will it impact the quantities for other customers. Demand planning systems make this super easy for demand planners to visualize multiple scenarios and their impact on other parameters in order to arrive at the best decision.
The key challenges in this process are lack of visibility and collaboration across different stake holders, unavailability of timely historical data, and the time wasted by the demand planning team in collating the required data for analysis. Many a time the plan takes weeks to be frozen across teams, leading to poorer planning and forecast plans.
Apart from predicting the demand at the SKU level, the demand planning team is also the custodian of 3 other KPIs viz. SMS (slow moving stock), DND (detention and demurrage), and last CDI (customer delivery index). They need to balance the demand plan with these 3 objectives i.e. minimize SMS, DND and maximize CDI.
Tools and Software for Demand Planning
Understandably, spreadsheets are the first tools anyone uses for demand planning. While they support the early days, spreadsheets are not designed to handle the complexity, scale, collaboration and analytical capabilities required by the demand planning teams.
Demand planning needs to be executed in sync with the other related planning processes e.g. sales forecast, supply-chain plan, and production plan. Thus the planning solution should be able to support multiple use cases for the organization to be able to have all of their plans connected to one another.
Because Demand planning is essentially a prediction function the system should provide various forecasting models such as linear regression, additive decomposition, triple exponential smoothing, etc. It should have the ability to suggest the best fit model and provide sales forecast prediction. The system should have the ability to do forecast at aggregation level and then disaggregating at SKU level.
Apart from this the common expected capabilities include features such as spread sheet interface, multi-dimensional engine, analytics & dashboarding, and collaboration.
Best practices for demand planning
While the demand planning objectives remain consistent across organizations, they vary based on whether you are in B2B or B2C, whether you are in a MTO or MTS business. Some of the best practices include:
- A defined and accepted process – Well understood roles and responsibilities, a shared consensus about the role and importance of the demand planning process, having a clear monthly schedule for all the teams to provide their respective rolling forecast numbers, a consistent template which all the stake holders can adhere to,
- SKU/ account level planning – As they say the devil is in the detail. It’s always possible to get summary data from the detailed data but not the other way round. So wherever possible do the demand planning at a SKU/account level. At least of major products/customers. This will enable to organization to decipher the trends better and reason the factors attributing to the demand.
- 3 demand plans – While this may seem a lot of effort a practice of developing multiple scenarios is easily enabled by a planning tool. One could be your best-case plan, second one as the more realistic case, and the third one as the worst-case plan. All together culminating into an overall agreed consensus plan.
- Cross-functional collaboration – This is key to a successful plan. Every department will have its priorities and constrains – the sales team wants to sale more, the production teams wants to utilize its capacity to the fullest and the finance team wants to ensure that the organization is not missing its financial KPIs. When you offer visibility into the assumptions and drivers to everyone concerned there is a likely output which is in the best interest of the organization., and lastly bring together all the stakeholder and jointly develop the final consensus plan.
What is your monthly demand forecast accuracy? If you are able to answer this question and monitor it month-on-month you will be able to find newer ways of improving it. Every single percentage point improvement can mean a revenue impact of millions. A Demand planning solution will ensure that you are capturing more market share and optimizing your costs and inventory.
Ans. Imagine a customer walks into your store but you do not have what he wants OR you have lots of quantities of another product which no one is asking for. Demand planning helps you solve this problem and that’s why its so crucial to any business.
Ans. Sales forecast, current inventory, production capacity, seasonality, and historical trends are some of the components that go into making the demand plan.
Ans. Capturing the sales forecast, normalizing it using past data and predictive techniques, comparing with trends/seasonality, and considering inventory and production capacity are the key steps involved in demand planning.
Ans. Sales forecasting is done by the sales team listing the orders they expect from their customers in the coming months. The demand planning team will use the sales forecast as a starting point for their process and develop the final demand plan taking into account other factors such as trends, seasonality, inventory, capacity, etc.
Ans. Liner regression, triple exponential smoothing, additive decomposition, and winter’s multiplicative are some of the statistical techniques used for forecasting.
Ans. Not having proper sales forecasts, inability to analyze past data, inability to bring together all the data required for planning purposes, providing trustworthy visibility to relevant stake holders are some of the challenges in the demand planning process.
Ans. Doing demand planning without software tools is akin to traveling to a destination without using navigation maps – you will get to your destination but it will cost you more time and money.