What is Demand Forecasting in Supply Chain Management?

What is Demand Forecasting in Supply Chain Management?

 

Many supply chain managers face the following dilemma: Their warehouse is overloaded with excess stock, which inherently takes up valuable space and drains financial resources. On the flip side, many supply chain managers also deal with the opposite problem: Too much demand from customers, and not enough stock to satisfy it. 

Both of these scenarios are bad, as they directly impact a company’s competitiveness, as well as overall customer satisfaction – two very important factors in a business’s success. The question is, how can you strike a balance and optimize inventory levels, while also ensuring that your supply chain functions smoothly? 

The answer: demand forecasting. Indeed, the best way to find a balance between surplus stock and stockouts is by analyzing historical data and market trends, and accurately predicting the degree of demand that can be expected for a specific product. Cutting-edge algorithms have made demand forecasting more accurate than ever, and it has emerged as an essential business tool for supply chain managers to make insightful decisions, optimize inventory levels, shed unnecessary costs and improve customer retention. 

The Basics of Demand Forecasting

In order to understand how demand forecasting can bolster your supply chain operations, it’s important to first grasp the basics of the concept. Simply put, demand forecasting is a systematic process of predicting future consumer demand for a specific product or service. This process involves several factors and considerations, including analyzing historical data, considering current market trends and examining consumer behavior patterns.

Why demand forecasting matters

There are countless reasons why demand forecasting is worth integrating into your business, not the least of which is that it offers valuable insight into expected demand, which enables businesses to determine optimal inventory levels, and mitigate excessive stock holding and stockouts. A steady stock replenishment system inherently leads to stronger customer satisfaction, and smoother operations on the whole.

Capacity management is another reason to use demand forecasting, as it can help businesses optimize their resources, avoid expensive carrying costs, and ensure their workforce meets the demand. Essentially, demand forecasting can minimize the perils associated with underutilization and overcapacity. 

Leveraging demand forecasting can lead to revenue optimization, since accurate predictions promote effective sales planning and strategic resource allocation – including marketing campaigns. Aligning supply chain operations with customer demand will also help businesses mitigate supply chain risks, and identify potential problems before they arise. By using foresight into future demands, businesses can plan much more proactively. [1]

Importance of Accurate Demand Forecasting

Of course, demand forecasting is only effective if it’s accurate. Precision is paramount in the world of demand forecasting, as the benefits of the process are only experienced if the information it depends on is verified.

That being said, it’s useful for businesses to create multiple forecasts for superior planning and control, based on several different scenarios and time horizons. For instance, short-term forecasts typically cover days to week, and can assist with important near-term operational decisions. Conjuring regular short-term forecasts is useful for avoiding daily operational obstacles, scheduling production and managing inventory. 

Meanwhile, medium-term forecasts, which typically cover months in advance, can assist with resource allocation and longer-term capacity planning. They can help businesses anticipate demand and prevent inventory issues, such as too much or too little stock.

Finally, long-term forecasts go beyond one year, and they are highly effective at helping with serious investment decisions, strategic planning and market positioning. Long-term forecasts enable businesses to pinpoint market trends and gain an understanding of demand patterns, which can help leaders make more complicated, long-term business decisions with ease.

Benefits of Demand Forecasting

On the whole, demand forecasting can offer profound business benefits. By truly understanding consumer habits, you can optimize pricing and promotions, maximize sales, bolster customer satisfaction and retention, enhance planning, allocate resources efficiently and effectively, and reduce unnecessary costs. Not to mention, demand forecasting can completely overhaul a company’s supply infrastructure by optimizing production capacities, streamlining procurement processes and solidifying distribution networks. 

Uncertainty is a fact of life, especially if you’re a business owner, but conducting accurate demand forecasting can remove a great deal of risk and futuristic haziness. It equips companies with highly valuable insight into market dynamics, which allows them to proactively respond to risks and changing conditions. In short, it helps them stay ahead of the game. 

In our eyes, demand forecasting is absolutely crucial for strong supply chain management. 

Factors Influencing Demand Forecasting 

Demand forecasting is influenced by a number of factors, all of which are either internal or external. Collectively, internal and external factors dictate the accuracy and accountability of the forecasting process. By carefully considering both external and external factors, supply chain managers can develop more robust demand forecasts.

Internal Factors

We’ve narrowed down four critical internal factors to consider when conducting demand forecasting, including: 

1.     Marketing and sales strategies: Promotional activities, including marketing campaigns and sales strategies, have a major influence on future demand patterns. It’s important to incorporate information about upcoming price strategies, product launches and other sales initiatives into demand forecasting.

2.     Production and operational capabilities: Of course, supply chain capabilities directly influence a company’s ability to meet customer demand. Capacity, lead times and other operational constraints are essential to incorporate into demand forecasting, in order to recognize what is actually feasible for a given business.

3.     Historical data: Looking into sales data from the past is a great way to predict how certain products might perform in the future. Historical data often reveals consumer behavior patterns, as well as overall demand trends. 

4.     Product lifecycle: It’s always harder to make accurate predictions about products that have only been on the market for a short period of time. Forecasting is generally less accurate for newer products, since demand patterns have yet to stabilize. As a result, it’s important to take a product’s lifecycle into account when forecasting demand.[2]

External Factors

There are four key external factors that have a major impact on demand forecasting. Since they are external in nature, they aren’t possible for a business leader to control: 

1.     Economic conditions: First and foremost, various economic factors will play a direct role in determining the demand for a given product. For instance, GDP growth and inflation rates largely impact consumer purchasing power and overall desire for specific goods and services. It’s important to closely monitor economic indicators and heavily consider them when conducting demand forecasting.

2.     Market trends: Similarly to economic conditions, considering qualitative variables is essential, as market trends will determine how competitive a given product is. Recognizing competitive products will allow for businesses to understand where they stand in the broader market, and what the demand is for their product compared to similar ones. Beyond competition, market trends also indicate consumer interest and spending patterns, which are both important factors to consider upon forecasting future demand. Make sure to read up on industry reports, so that you’re well equipped with valuable insight on the nuances of the field you’re in. 

3.     Regulatory factors: Depending on the product in question, there are certain regulations and legal requirements that can shape demand. For many industries, there are specific regulations – including health and safety protocols – that must be met, and regulatory changes can determine demand.

4.     Seasonality: Certain products are far more in-demand depending on the season. For example, SPF skincare is, naturally, much more coveted in the summer months. As such, the time of year is an essential consideration when forecasting demand for supply chain managers, as there are certain products that are more seasonal than others.[3]

Developing a Robust Demand Forecasting Strategy 

Set clear goals: In order to develop a robust demand forecast strategy, there are several steps involved. For starters, it’s critical to set clear goals and objectives from the get-go, and determine key performance indicators (KPIs) that align with your goals. For example, if your wish is to improve inventory turnover, that goal should be a central part of your demand forecasting strategy. 

Collect accurate data: Collecting accurate data is another important element, as data truly is the foundation for robust demand forecasting. The more information you can collect, the better. That includes historical sales data, customer orders, market trends and competitor sales. When it comes to collecting accurate data, it can be useful to leverage advanced analytics techniques that can help you sift through large datasets with ease.

Use enterprise resource planning (ERP) systems

Speaking of advanced analytics, if you’re in the world of supply chain management, it’s worth utilizing enterprise resource planning (ERP) systems, or other advanced business software, which are directly aimed at improving demand forecasting capabilities. These systems expertly streamline and simplify data collection and analysis, and offer a centralized platform to make accurate predictions. Typically, these systems come with statistical modeling and data visualization capabilities, as well as scenario analysis. 

Machine learning algorithms can offer meaningful insight into demand patterns by conducting time-series analyses, regression analyses and other statistical examinations. We urge you to test out various systems and softwares to determine what suits your business best. 

Encourage collaboration

Additionally, encouraging collaboration between the different facets of your business is a great way to improve demand forecasting. The sales, marketing, operations and finance teams should always be in direct communication in order for the final forecast to incorporate insights from various stakeholders. This allows for a more comprehensive, nuanced and holistic forecast, which will unquestionably contribute to accuracy. 

It’s worth mentioning that demand forecasting is, after all, a forecast – meaning it’s not set in stone. As such, it’s incumbent upon supply chain leaders to be patient with the process, and remain open to learning and improving along the way. Remember, demand is always subject to external factors beyond a business owner’s control. As a result, it’s important to be flexible in your forecasting strategy.[4]

Conclusion

In all, demand forecasting is a stellar supply chain management tool. When conducted properly and accurately, it can offer a slew of new insights that will allow a business to flourish and push its potential. 

By following the aforementioned tips, you can hone a robust demand forecasting strategy that aligns with your business objectives, leverages your available data, considers qualitative variables, and taps into advanced tools and techniques that will bring your business to the next level. 

If your goal is to make informed business decisions, optimize inventory levels, improve customer retention and satisfaction and bolster your business operations, then try demand forecasting. You will not regret it!