“The best collaborations create something bigger than the sum
of what each person can create on their own.” – Anonymous
Importance of collaborative Demand Planning in global businesses
Demand Planning is a multi-step and iterative operational Supply Chain Management process, which generates reliable demand forecasts based on historical sales data and relevant business information like – impact of marketing promotions, new product launches and discontinuations, pricing discounts, rebates and market intelligence.
In today’s global business environment, demand signals are dynamic and complex in nature due to multiple SKUs, wide distribution networks, multiple point of sales, varying geographical locations, customer demographics, and seasonality. Huge amount of diverse and complex data is generated which needs to be effectively incorporated in the Demand Planning process.
Normally, there are multiple Demand Planners that contribute to the Demand Planning process. And there are remotely located individual Demand Planners for specific product categories, geographical regions, and customer segmentation. Different inputs from these Demand Planners contribute to the overall Demand Planning process. Hence, for global businesses, it is imperative that their Demand Planning process is fundamentally collaborative.
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Key benefits of building a collaborative Demand Planning process include:
- Increased processing speed and accuracy
- Reduction in forecast errors
- Increase in customer service levels
- Reduction in bull-whip effect across the Supply Chain
- Cost savings
- Increased productivity
- Transparent data sharing for a better decision-making process.
Difference between Demand Planning and Forecasting
Demand Planning and Demand Forecasting are two different terms which are often used interchangeably in the business environment. Demand Forecasting is the process in which only the historical sales data is used to develop an estimate of an expected forecast of customer demand.
Demand Planning is a multi-step operational Supply Chain Management process, which generates reliable demand forecasts, based on historical data and relevant business information.
Demand Planning Tools
There are various manual and automated Demand Planning tools available in the market. Selection of the right tool depends on the scale of business, product range and distribution network. There are mainly three types of Demand Planning tools widely used in the business environment –
- Excel based Demand Planning
- ERP integrated Demand Planning module
- Demand Planning software solution.
Management needs to ensure structured Demand Planning training for all Demand Planners and key stakeholders. New features and functionalities also need to be communicated across the organization and key users need to be trained accordingly. Best-of-breed solution providers such as, Arkieva, provide demand management solutions that allow for Excel and ERP integration without sacrificing the advanced demand planning features needed for a more detailed analysis.
Demand Planning Methods
One of the most important steps of Demand Planning process (DP) is the appropriate selection of a Demand Planning method. Selection of suitable method is dependent on the type of product, type of demand, manufacturing strategies, distribution model, data collection approach, etc.
The following are the popularly used Demand Planning methods:
- Make-to-stock DP
- Make-to-order DP
- Time Series forecasting
- Demand Sensing
- Demand Shaping
- Bottom-up DP Approach
- Top-down DP approach.
Based on the specific requirements of a business or a product category, a customized Demand Planning process model can be developed. Such a model is an extension or combination of specific Demand Planning tool and various Demand Planning methods.
Demand Planning process flow:
Demand Planning software: A robust foundation of collaborative Global Demand Planning
A Demand Planning software refers to a computer-based program which runs on database management system (DBMS) and integrates, automates & drives the Demand Planning process. For successful implementation of collaborative and centralized Demand Planning, higher functionality options like database management system (DBMS) need to be explored. Some of the DBMS examples are Microsoft SQL server, Oracle and DB2. DBMS-based Demand Planning software solution, facilitates an online collaborative working environment with higher speed and accuracy, data consistency, data sharing and reporting. Checks and balances on user inputs and controls and alerts to prohibit fraudulent manipulations can be customized in the software. Collaborative and centralized Demand Planning process can be easily implemented on DBMS platform, with data input standardization, report customization, what-if scenarios capability, scalability, repeatability, accuracy, and security.
Consensus Demand Planning: A trusted driver of collaborative Global Demand Planning
Based on the historical sales data and statistical analysis, Demand Planners develop long-range estimates of expected demand, also known as the Baseline Forecast. Once the Baseline Forecast is generated, the Demand Planners can initiate the collaborative process of taking inputs from various functions, for analyzing the impact of marketing promotions, new product launches, pricing discounts, rebates, market intelligence and product discontinuations. Finally, a formal consensus meeting can be held with Finance, Sales, Marketing, Manufacturing, Purchase, and Logistics for final inputs for releasing the Consensus Demand Plan is released for operational purposes. This formal and structured process of consensus meeting brings early alignment between diverse functions and inculcates a joint sense of ownership of the deliverables.
Encourage and Reward a collaborative Global Demand Planning process through shared KPIs
There is nothing which brings diverse functions and teams together more than a set of common KPIs and a joint performance management system. Organizational KPIs and Functional KPIs can be complemented with shared KPIs for an all-round assessment of an individual’s performance. Some examples of shared KPIs are – Customer service metrics like on-time delivery (OTD), on-time in-full (OTIF), case-fill/fill-rate; Reduction in inventory obsolescence, Reduction in inventory re-positioning costs, etc.
Sufficient weightage need to be provided to the shared KPIs so that due importance and collective proactive action is carried out by teams. Shared KPIs facilitate lowering of communication barriers and functional silos and foster teamwork between competing functions and individuals.