Demand Planning-Tool to Manage Consumer’s Demand

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Demand

In the 21st century of a dynamic market and cutthroat competition, the world has witnessed many inventions and trends which have changed the concept of the market from offline to online. E-commerce, virtual markets and internet have made market from local to global. However, the only thing which has not changed is the driving force of the economy and market – “Demand”.

In simple words, Demand is a consumer’s desire and ability to purchase goods or hire services. Consumer’s “Want” becomes “Demand” when it is backed up purchasing power. For any given product, there may be Independent demand, Dependent demand, Inter/Intra company demand and Service parts demand. Generally, organizations are forecasting independent and sometimes service parts demand, but all types of demand have to be planned for an organization’s supply chain processes to ensure availability when needed.

On one hand “Demand” is the driving force for market and easy to understand, whereas on another hand it is equally difficult to plan production and availability of goods or services in line with demand as it is very volatile and dynamic which keeps changing with product’s characteristics viz. its price, availability of products substitutes and liquidity in the market. Hence, it requires meticulous planning of the organization’s activity to handle the demand variation. It is called “Demand Planning” which means the process of forecasting the demand for a product or service so it can be produced and delivered more efficiently and to the satisfaction of customers. Accurate demand planning ensures timely, efficient and cost-effective operations.

Demand planning is the trade-off between Revenue and Inventory. The optimum balance of both will ensure maximizing of revenues by ensuring product availability in the market with optimum inventory levels. Timely, accurate, useable, qualitative and quantitative information is the base of demand planning decisions. It involves analysis of information from multiple sources like channel sales, customer orders, shipments or market indicators or signals to predict future demand patterns. Effective demand planning may reduce costs, improve inventories and speed up time to reaching to market.

The purpose of demand planning is to prepare a statistical forecast. It requires planning team which includes representatives from the sales, marketing, operations and procurement departments. This team starts reviewing the available information like historical data on sales, market research and surveys, and then agrees on a forecasting model it believes will be most effective at predicting demand. The team can then add new data as it comes in, such as actual sales of a product or competing products, and revise the model and resulting forecasts if necessary.

Why demand planning is important?”  – The simples answer is to handle Demand Volatility and System & Manual Variations in the process.

Demand Volatility: It refers to changes in customer’s demand than forecast has been made by the organization. Further, the proliferation of goods and services in the markets and changing needs of customers make it more critical and difficult to sense, analyse and provide a response through the supply chain. It makes forecasting of products more difficult as data will be more complex and usual responses are less effective. Bullwhip Effect creates demand volatility that becomes amplified as it moves through the supply chain.

Systematic Variation: Inventory is a cost and no organization want to hold it but it is a necessary evil because of variations in demand, lead times, yield (production line reliability), transit times and of course random shocks from weather to other factors that affect raw and finished good availability. Since all these variations are natural in operations and cannot be eliminated at all but can be reduced to a certain level, hence it is called System Variation. Upon optimization of system variation, the overall cost will be reduced and the achievement of targeted sales will be increased with optimum inventory level.

Manual Variation: Another source of variation is due to Internal Errors due to faulty assumptions by team during Demand Planning, Production Planning and Inventory Planning. The communication of those plans to suppliers just passes and amplifies the variation. Inventory inaccuracy is also attributed to this error. This kind of errors can create spikes in inventory that could take months to come to normal level especially if they are over forecasts which result in over procurement of raw materials or overproduction of finished goods.

All above 3 parameters shall be dealt with strong leadership, collaborative approach amongst all functions of the organization and optimum inventory maintenance in the supply chain. Supply chain alone cannot control the same as they have some limitations particularly in forecast accuracy and execution of the plan based on forecast is dependent on Sales team. Further, reduction in Excess and Obsolete (E&O) inventory is possible by extra efforts of the sales team or write off option from Finance team whereas managing Month and quarter end peaking where Sales will be increasing by 50-60% of the entire month or quarter is primarily Sales team function. It can be managed by proper planning, demand shaping and push-based system implementation by the Marketing and Sales team.

Conventional supply chain design is unable to sense the demand and adapt the rising demand volatility. It will respond only based on a defined system. Creating an adaptable system that can sense, respond and better manage volatility, requires a complete shift from conventional approaches. This includes sensing channel demand; using optimization to actively shape demand and applying advanced analytics used to drive an intelligent response. It is a three-step process.

3 Steps to Creating Adaptable Demand Planning System:

  1. Improve mistakes made in past: Organizations have to admit the mistakes of the past related to faulty technology implementation and adoption of wrong practices. Few of them are,
  • One number forecasting which depends on a single parameter whereas demand planning is governed by multiple factors
  • Consensus planning without properly disciplined incentive structure scheme which increases bias and errors
  • Forecasting what is to be manufactured by the production team rather than what is selling in the channel
  • Lack of training to understand and use the forecast signal to decide what is urgent and what is important amongst the signals
  • Adoption of Collaborative Planning Forecasting and Replenishment (CPFR) programme without proper training of retailers who are giving a forecast for demand planning.

2. Buy the right demand planning system: Demand planning, ERP (Enterprise Resource Planning) and order management are the most important supply chain technologies based on in-memory processing, cloud-based analytics and deeper optimization. Demand Streams and Demand Drivers are the key factors to choose the right technology for the organization’s operation. i.e. Interconnectivity, seasonality, top-down and bottom-up forecasting, and forecast-value add analysis are essential to the selection of the technology.

3. Careful Implementation: After planning and adopting the best technology also, the final result is depending on the implementation. Companies that are the most successful in demand planning tune the optimization engines through a series of conference room pilots to drive the highest forecast accuracy. The goal here is not to accelerate the speed of project implementation but to establish a well-designed pilot which can identify correct demand drivers and optimizing the technology in line with the same. Further, it requires timely tune-ups by the cleansing of data, alignment of planning master and fine-tuning demand optimization engines. For any goal, a resourceful team with suitable knowledge, experience, training and skills is required. The team shall have the correct mindset for using forecast signals and shall be interested in the reduction in bias and errors by using Forecast Value Add (FVA).

Achieving Demand Planning Excellence: Estimating future demand is one of the most valuable activities in any organisation because its impact is felt throughout the business, from sales and marketing to procurement, manufacturing and distribution.  The right demand plan can balance inventory levels with costs and lead to higher customer service levels and positive cash flow. For achieving Demand planning Excellence following 4 parameters need to be taken care of.

  1. Look forward beyond ERP reports and Spreadsheets – Despite upon accurate demand planning is directly correlated with the profit of an organization, more than 80% of the organizations are still dependent of ERP reports and Spreadsheets. This quantitative forecasting can be used for products which have existing demand history available whereas for newly launched products qualitative models including subjective inputs like product attributes, market knowledge, benchmarking and expert opinions need to be used. Organizations have to identify and implement both quantitative and qualitative attributes for demand planning.
  2. Disaggregate Strategic Demand Forecasts to Operational Levels – Demand Aggregation (From bottom operation level to top strategic level) and Disaggregation (Vice-versa) are keys to reconciling the data at all levels and generating best possible forecasts. Both hierarchies should support demand signals and input from multiple sources, including customer and sales forecasts, management direction as well as external demand signals generated by synchronized data and point-of-sale (POS) information. The hierarchy structure breaks down higher level plans into detailed forecasts and decides “SKUwise quantity” need to be created, stocked, and distributed for multilevel product structures such as accessories, components, consumables and service parts that have time-phased dependent demand. Generally, the most accurate forecasts are achieved by disaggregating higher-level demand forecasts down to tactical levels which reduces the forecast error inherent in the higher tier into smaller inaccuracies at the lower levels of demand planning.
  3. Focus on High-Value Add activities – Supply chain organizations focus on high-value-add activities like avoiding problems, resolving issues and optimisation. A centralised dashboard display and planner-specific real-time alerts (in form of system, email or mobile notifications) call attention to important conditions that have deviated from established targets or expectations. Planners will also need to create custom alerts as needed to support the priorities and business goals of the organisation. As per ABC analysis, most manufacturers’ 20% of SKUs drive 80% of sales while the next 30% of SKUs drives 15% to 19% of sales and the balance generates 5% or fewer Sales. Planner’s main focus is to set alert for high-value products (the “A” items) that contribute the most, whereas the response of “B” items shall be moderate and “C” items can be reviewed as and when basis. Common KPIs which can be included are forecast accuracy, inventory levels, service level, fill rate, and stockout percentage. By managing one integrated set of KPIs across the organisation, from supply-side to demand-side, at every level of forecast aggregation; everyone stays on the same page regarding overall performance against unified customer service metrics.
  4. Collaboration – Getting visibility to what customers, partners and internal stakeholders know can further drive a more accurate demand plan and provide reliable input to the sales and operations planning (S&OP) team. An introduction of Collaborative VMI is a combination of Collaborative Planning, Forecasting and Replenishment (CPFR) and Vendor-Managed Inventory (VMI). In this, the purpose is for trading partners to share information and cooperate to sense demand as early as possible and respond to changes in demand efficiently.

A Collaborative VMI process is based on shared planning calendar and proactive meetings that allow trading partners to integrate and view point-of-sale data, promotional schedules, buyer and seller inventories, replenishment forecasts, new product introductions, and more. The planning function moves beyond a focus on orders only and gets closer to actual consumer behaviour. It requires formalised processes to accurately anticipate time-phased inventory and customer replenishment needs. S&OP brings together marketing, sales, manufacturing, finance, sourcing, and more on a regular basis to make fully informed decisions and create one collaborative plan that best drives the organisation toward its business goals. In fact, S&OP is probably the most vital collaborative activity in the organisation with frequency of weekly/fortnightly or monthly basis as per business requirement.

Role of Demand Planning in Supply Chain:

The success of a supply chain is linked to its efficiency, which can be traced back to the ability of managers to conduct accurate forecasting when it comes to revenue and inventory. It is possible through Demand planning which uses analytics that examines historical sales data, customer orders, shipments, current sales, and market indicators to better predict demand patterns based on market changes, enabling firms to make smart decisions about inventory and production levels.

Demand planning is a strategic function in the organisation’s supply chain is essential to coordinate and ensure the production alignment to meet demand, and plays a key role in influencing production flows and incoming sales. In the manufacturing industry, the demand planning function is responsible for managing the product demand and determining the resource availability like raw, packaging and other goods required along with required manpower which influences the procurement process.

Demand planning is usually managed through a suitable management system such as MRP (Material Resource Planning). Demand planning needs a consensus to take place regarding forecasts and it acts as both the gatekeeper since data needs to be approved before entering the MRP system and the arbitrator (since the information is required for fine-tuning forecasts). i.e. SAP Hana, SAP’s APO and MRP module, Microsoft’s Dynamics 365 for Operations etc.

Once the data has been entered into the system, and the forecast is not met then the demand planning function reacts accordingly, under appropriate controls, to tune the demand signal. This function has the benefit of providing constant monitoring and reviewing, which can be accessed by management to assist with any issues and determine future business trends. Software systems can assist with effective demand planning and support processes like capacity management and stores requisition management.

This way departments such as operations and financials can communicate and collaborate to ensure production meets the needs of demanding customers.

Good demand planning is highly accurate, based on data and enhances profitability. But the process can be tedious, time-consuming and easy to mess up. One area of a supply chain, such as procurement, may improve its ability to forecast future demand, but logistics and manufacturing may lag behind, leading to higher levels of inventory and escalating costs.

Thumb Rules for Right Demand Planning:

  • Right plan design – Demand planning is integrated business planning activity and must be designed in integration with other business function to drive profitability meeting customer demand.
  • Unique level of planning – Demand planning shall be done at the right level which is unique to business requirement i.e. product family, customer or geographic level
  • Collaborative Approach – It is a collaborative approach and not a single level statistical algorithm testing. If planned in a collaborative way then it helps to get closure to true demand signal.
  • Not just the forecasting – Forecast is a component of demand planning and relates to the best estimate of future demand. Best-in-class companies will influence demand through marketing events and promotions to bring forecast in line with the business plan.
  • Control what you can measure – Put the right set of linked key performance indicators in place and measure and control regularly against these.
  • Educate people before training – Demand planning is a cross-functional process and right education and training are most important to make them realize the importance of their contribution.
  • Data Cleansing – Demand planning deals with the huge quantum of data and a robust system is required to keep it cleansed for better forecast accuracy.
  • Trust the numbers and manage by exceptions – 80% of sales can be achieved by reviewing 20% of the items.
  • A positive error in the forecast – A good statistical forecast will have an appropriate error which drives an appropriate safety stock target. This leads to good inventory management and delivers higher service with a lower total inventory.
  • Deploy a proven best in class solution – A recent Aberdeen study shows that companies that excel in demand management — reporting higher forecast accuracies and lower inventories — are two-and-a-half times as likely to have implemented a best-in-class demand planning system.

At the concluding note, the world of demand planning has changed. The business requirements have escalated and it matters more than ever. To move forward, companies have to admit the mistakes of the past, implement continuous improvement programs to drive discipline, and carefully re-implement demand planning technologies to sense and shape demand.

The evolution to demand excellence needs to be built on a program of continuous improvement focused on forecast-value added techniques to reduce bias and error. Effective demand planning doesn’t just happen, it requires work. It is contingent on the ability to build the right teams and bring a new level of excitement and open-mindedness to driving a demand signal. Those that do it best are comfortable in global market which offers a new opportunity and where demand holds value.

In line with the demand, Supply chains have to adapt to demand changes proactively rather than being reactive and address the demand volatility which is getting increased due to Consumers’ wants and needs shift faster in the modern marketplace. Successful supply chains are able to adapt by eliminating bias and building systems that can sense and respond to demand volatility. Such a system needs to be designed from the outside-in and includes sensing channel demand, using optimization to actively shape demand and applying advanced analytics to drive an intelligent response.

Find the PDF file here for future reference. Your comments and feedback are most welcome.

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