What is Supply Chain Demand Planning?

by | Mar 2, 2022 | Data Management, Experts, Retailers

Now more than ever, supply chains need to be efficient. In an increasingly competitive global market, supply chains need to prioritize efficiency and speed and minimize disruption.

In addition to everything that supply chain managers and logistics teams must control – like clarity of communication and managing specialist teams to tackle delays quickly – speed and efficiency in supply chains revolve around predicting the unknown.

To reduce delays in supply chains, planning is critical…

Demand Planning Definition

Demand planning is the process of predicting or forecasting the level of stock needed to satisfy customer needs at any given time while limiting excess stock. The result is a more efficient supply chain, increased profitability and reduced waste.

Using past data trends, Supply Chain Planning (SCP) attempts to balance the supply and demand of seasonal goods while being agile enough to adapt to last-minute changes, too.

For example, both bricks and mortar stores and online eCommerce traders rotate stock seasonally and depending on consumer trends. However, sudden changes in product demand can catch retailers unprepared – especially if regional stores or internal departments don’t freely share information, maintain strong communication and keep a finger on the pulse of national and regional news.

Demand Planning vs Forecasting

The differences between demand planning and forecasting are subtle.

Demand forecasting refers simply to projections of what will happen based on historical data and past trends, but demand planning is more complex.

Demand planning considers all parts of the supply chain, including:

  • Logistics and distribution solutions
  • Seasonality of product offerings
  • Unforeseen circumstances (market fluctuations or major global events)
  • Labor management
  • Regional and national fluctuations in consumer demand

Demand Planning Process Flow

For an efficient and effective demand planning system, retailers must have a framework in place to take them from data collection and cleansing to implementing an actionable strategy.

This will typically include:

Data collection – The minimum amount of data needed for effective demand planning is 3 years’ worth of backdated transaction and inventory information. This provides reliable insights into which products remain seasonal or situational and those that represent sporadic or one-off trends. This data can be collected and cleansed using a retail analytics solution.

Demand planning – The next step is analyzing the data. This means assessing everything from historic sales figures and items frequently brought together to seasonal trends and product promotions to forecast stock requirements. Demand planning should also include key external drivers such as price points and even environmental influences like the weather.

Supply planning – Here, the focus is on constructing the supply chain itself – gauging material and logistical requirements, organizing vendors, and setting out a production plan based on data. This is also where financial considerations such as budgets and revenue forecasts should be considered to keep the process sustainable and profitable – as well as testing ‘what-if’ scenarios and putting relevant contingency measures in place.

Executive meeting – Finally, a meeting is needed to approve plans, iron out any potential supplier or logistical issues and review key systems and tools. This is also where retailers should establish KPIs and make sure they are communicated across every step of the chain, so each department owns its objectives.

Demand forecasting Methods

Unfortunately, we can’t predict the future. However, there are solutions retailers can employ to make future projections as accurate as possible.

Depending on budgets and resources, retailers may turn to a combination of solutions to achieve accurate demand forecasting.

Boosting forecast accuracy may include:

Using active and passive demand forecasting – Passive demand forecasting uses past sales data to forecast future demand. While simple, this method is still useful in delivering reliable projections, particularly if the industry is susceptible to consistent seasonal performance.

However, new start-ups or SMEs must be more proactive, lacking a comprehensive sales history strong enough to inform a solid projection.

Active forecasting, however, also considers wider market research, financial goals, and economic trajectory – giving a helping hand to those without a long-standing sales history.

Calculating short- and long-term projections – Managing short- and long-term predictions is a balancing act. Too heavy a focus on one while neglecting the other can lead to supply issues, missed opportunities and waste.

Short-term forecasting requires businesses to evaluate real-time sales data and manage just-in-time supply chains – improving efficiency to meet immediate demand.

However, long-term forecasting methods combine sales data and market research with the business’ own aspirational targets. This way, they can anticipate future demand, prepare for growth and make sure the processes are in place to expand while remaining agile.

External forecasting – This method examines externalities from relevant business sectors – and current trends in the financial market – to inform forecasting decisions.

Businesses need to be aware of what’s going on among their competitors and the wider industry, as well as developments in their own four walls, to remain competitive. External forecasting may include everything from competitor activity to wider influences like domestic and global economic performance and social factors.

Market research – Sometimes, internal data isn’t enough – especially if your business is in its infancy. Getting valuable stakeholder and customer inputs about company offerings helps shape its direction and influences a comprehensive demand forecast.

The ‘Delphi’ method – This method leverages the opinions of business and market experts to provide additional data and insights, helping companies steer their forecasts in a more profitable direction.

A panel of global market experts provides anonymized feedback and works together to reach an agreed consensus on the current product forecast, so retailers can streamline their supply chain for greater efficiency going forward.

Demand Planning Tools

To reap the rewards of accurate demand planning, retailers must be equipped with quantitative and qualitative data and powerful tools that can automate and streamline many of the time-consuming manual tasks that threaten to delay supply chain activity.

Retail Analytics software is key in efficient demand planning – tracking and cleansing all sales data and presenting it in intuitive dashboards. This gives decision-makers the overview of trends and patterns needed to make macro-scale decisions as well as to react to micro-scale trends by store and unexpected challenges.

Assortment tools also consolidate, standardize and validate data, automating previously manual tasks to keep retailers agile to new challenges or market fluctuations. This accurate data not only allows retailers to make forecasting decisions with confidence but also supports their execution. Assortment tools automate the mapping of channels and partners and the sharing of data – keeping the supply chain efficient and maximizing the value of each demand planning decision.

Demand Planning Benefits

Because supply chain efficiency is paramount to retail success, demand planning boasts many benefits.

Demand planning markedly improves a business’ forecasting accuracy – allowing retailers to more efficiently manage their product offering, inventory levels, material waste and logistical solutions, substantially increasing profitability.

Having a comprehensive demand plan in place also helps retailers remain competitive and become more agile to anticipate and capitalize on emerging sales opportunities – also reducing waste by making speedier supplier decisions.

Having greater access to data makes labor management easier to optimize, too. Retailers get a clearer picture of where resources must be allocated and can make adjustments in light of real-time changes.

Demand Planning Best Practices

Demand planning has the potential to drive efficiency in supply chain management and increase retail profitability. To maximize the benefits, retailers are advised to follow demand planning best practices:

Be careful assembling data

Delivering the most accurate demand forecasts requires a vast quantity of data.

This requires retailers to have both the tools in place to collect and cleanse data, as well as the inventory management infrastructure to handle fluctuations and increases in demand.

This also includes using reliable data for ‘demand sensing’ – the forecasting of demand based on external factors like changes to market conditions or consumer sentiment, wider economic factors and even environmental influences.

Coordinate a strategy

The strongest demand plans start with descriptive analytics to get an understanding of where the business currently stands in terms of inventory, supply chain capabilities and capacity and overall resources.

Each department should be managed effectively to ‘own’ their forecasting. This includes data collection and analysis and creating actionable plans based on the findings. However, effective demand planning also requires collaboration from all departments.

Demand shaping

While demand sensing is a key component of planning – allowing retailers to anticipate and brace for increases or decreases in opportunity – this can be combined with demand shaping activities to drive greater profitability.

Demand shaping refers to retail tactics that don’t react to consumer behavior but lead it. For example, by planning marketing campaigns, product promotions and special offers, retailers can dictate when their customers are most likely to buy. This obviously makes demand planning simpler and more effective, as it removes the risk associated with reacting to market changes after they’ve happened.

At SPS Commerce, we know what it takes to organize and manage an effective demand planning strategy – and we can support you in your demand planning journey with a range of data analytics and assortment tools. Find out more about our extensive range of demand planning solutions here.

Nick Schwalbach
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