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Freelance Demand Forecast Consultant
M&A Consultant
6 years experience | Associate | San Francisco, CA, USA
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Freelance Demand Forecast Consultant
Corporate Finance Advisor at Real Dairy Australia
12 years experience | Senior | Karachi, Pakistan
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Freelance Demand Forecast Consultant
Senior Investment Banking Analyst
4 years experience | Associate | Cyprus
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Freelance Demand Forecast Consultant
Founder at Walecon
9 years experience | Manager | Vienna, Austria
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Freelance Demand Forecast Consultant
Principal, Corbel Capital Advisory
20 years experience | Manager | Dublin, Ireland
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Freelance Demand Forecast Consultant
Connector, contributor, investor, advisor
8 years experience | Manager | London

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Guide to hiring the right Demand Forecast consultant

What does a Demand Forecast consultant do? And how can you find the right one? Learn more in our hiring guide for Demand Forecast consultants.

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Process of finding a Demand Forecast consultant

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We will shortlist a selection of 3-6 candidates for your project within 48 hours or less.

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You can directly contact your shortlisted candidates, invite them for interviews, and agree on project details.

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Frequently asked questions

Our Demand Forecast consultants work with clients in 40+ countries. Our clients are Corporate Development divisions, Private Equity backed companies, and fast-growing ventures.

Fintalent is not a staffing agency. We are a community of best-in-class Demand Forecast professionals, highly specialized within their domains. We have streamlined the process of engaging the best Demand Forecast talent and are able to provide clients with Demand Forecast professionals within 48 hours of first engaging them. We believe that our platform provides more value for Corporates, Ventures, Private Equity and Venture Capital firms, and Family Offices.

Our Demand Forecast consultants have extensive experience in Demand Forecast. Most of them have buy-side, sell-side M&A, or Private Equity experience.

Fintalent.io is an invite-only platform and we believe in the power of referrals and a closed-loop community. Members of our community are able to invite a small number of professionals onto the platform. In addition, our team actively scouts for the best talent who have experience in investment banking or have worked at a global top management consultancy. All of our community-referred talent and scouted talent are subject to a rigorous screening process. As such, over the last 18 months totaling more than 750 hours of onboarding calls, of which only 40% have received an invite-link after the call.

Our Demand Forecast consultants have experience in leading firms as well as interfacing with clients and wider corporate structures and management. What makes our Demand Forecast talent pool stand out is the fact that they have technical backgrounds in over 2,900 industries.

We operate world-wide and have clients in North America, Europe, APAC, and MENA.

Pricing depends on seniority, location, and project duration. For our pricing structure, please refer to our Pricing page.

Hiring guide to find the perfect Demand Forecast consultant

What is Demand Forecasting?

A demand forecast is an estimate of the demand for a product or service during a given time period. In the world of supply chain management, demand forecasting means trying to figure out, as far in advance as possible, how many products or services will be demanded by customers in future periods (e.g., weeks). It is a very crucial component of supply chain management.

Demand forecasting according to Fintalent’s demand forecasting consultants is not only important to the company’s growth but also to its profitability. For example, demand forecasting can be used in order to manage inventory levels or optimize distribution. Forecasting demand helps the corporation determine how much (and when) they need to produce products and services. The necessary production and/or inventory levels help eliminate waste and save money, while also allowing companies to meet market demands at the best prices.

Demand forecasting tools are very diverse and can include data coming from many different sources, including sales data, cost data, marketing data, etc. Some of these sources include:

The forecasting process can be divided into two main components: demand forecasting and capacity planning. Although demand forecasting is more likely to be seen as the core of the process, capacity planning is necessary in order to make decisions and take action (e.g., production or purchase orders) when demand forecasted happens.

What Can you do with Demand Forecasts?

Executives use demand forecasts for decision-making purposes. For example, companies might use these forecasts for supply chain optimization and strategic planning (e.g., determining how to allocate resources among products). Demand forecasting is also often used for service, marketing, and advertising needs. In marketing and advertising, the demand forecast helps businesses determine if the company should market a certain product or not. For example, let’s say that Bob’s Tacklebox has a 20% chance of making $10 million this year. If they decide to market an item, they would need to know if they’ll make $30 million or less than that because of their 20% chance of success. Without any information about supply, demand forecasting can be difficult to complete effectively since predicting demand is so critical in order for a business to operate efficiently.

Forecasting requires data and analysis to generate the results needed by decision-makers. Many types of data are available to provide these results; the type used depends on the needs of the company. One example is the use of customer demand data to make decisions about products, services, and advertising. The following list is a few types of data and how they can be applied:

The best way for a business to forecast demand is through a demand planning process. Forecasting demand in an organized manner helps businesses create more efficient plans and forecasts to plan for increased demand and supply over time.

Demand forecasting involves predicting future customer behavior, which usually involves an analysis of past behavior or trends along with projection methods such as statistical modeling. One of the best ways to forecast demand is to use data, such as internal and external sales and cost information. Demand can be then forecast over a time period by applying mathematical models and statistical techniques such as linear regression.

Demand forecasting is not only important for growth but also for profitability, so it is often done with tools like budgets or MRP II (Manufacturing Resource Planning II). It helps in deciding where to allocate resources within the company. Forecasting demand can help companies manage inventory levels, optimize distribution or service levels, or plan production levels. Decision-making that involves forecasting demand requires companies to determine how much they need to produce products and services based on past history.

Demand forecasting can be used to plan the production and distribution of goods, as well as to identify the resources required. The results of these forecasts combined with knowledge of costs give a good indication of profit potential. Demand forecasting is also very useful for forecasting gap analysis and what actions need to take place in order to gain or maintain a market position.

The demand forecast, along with the supply forecast, is one of the most important components for effective business planning and decision-making for both small and large companies. It helps anticipate customer needs (including expected growth) and helps determine what products will be in demand at what prices. This information has huge implications on profitability, asset utilization, and the risk management strategy of an organization.

Although the methods and tools used in forecasting demand are diverse, many share some basic techniques. Forecasting techniques generally fall into two categories: qualitative or quantitative. Qualitative techniques involve the generalization of past observations or anecdotal evidence; whereas quantitative techniques use statistical analysis to build models and make predictions. The main methodologies used in demand forecasting include:

Inventory planning is concerned with determining the optimal inventory level of a product or product group to fulfill customer orders. If a company finds itself with excess inventories that are not yet needed, it may need to be sold off at a loss, which negatively affects company profits, even if it still holds residual value. Similarly, if it fails to move inventory or sell it at a profit, it may find itself with unsold goods that are now left in the warehouse, increasing costs and decreasing profits. This can cause irreversible damage to the company’s cash flow and account balance.

Supply chain management is the process of managing the production (manufacturing) and distribution (sales) of goods. It involves forecasting demand by anticipating future customer needs and taking actions to meet those needs as accurately as possible, so as to minimize losses from over-production of products or from unsold goods in inventory. Supply chain planning also involves forecasting demand for each stage of the production process.

Demand forecasting is a major element in many different disciplines within the supply chain management arena. In fact, the correct planning and implementation of demand forecasting can have significant positive impacts on overall supply chain performance. Demand forecasting is an important part of growth management, which encompasses many different functions including:

While supply chain management has become increasingly important for companies over recent years, demand forecasting also plays an important role in this process. The role of demand forecast resolution and optimization in the planning process of supply chain management has been discussed by Sandy Flynn (2003). This article is a review on the theoretical and practical aspects of demand resolution and optimization in supply chain management.

Demand forecasting is different from forecasting demand for inventory, which also involves predicting future customer behavior. Intuitively, we can see that from the supply side, one could correct for any errors in demand forecasting by adjusting inventory quantity to match forecast demand. On the other hand, some companies may not want to adjust their forecast at all; emphasizing an economic value judgment of whether or not it would be best to sell an item at a lower price (and lose money) if it is unneeded at that time. The company may consider factors such as customer service satisfaction and improved reputation by keeping unsold products out of inventory.

Another possible approach is to have demand forecasts match inventory forecast. This assumes that demand forecasting is more accurate than inventory forecasting, and it would be best to hold equal quantities of product in both inventory and on the shelves. However because of the need for economic flexibility in the throughput of goods, one could also choose to adjust the quantity of goods sold according to differences between the two forecast.

Demand Forecasting Forecasts are important in supply chain management as well as sales forecasting and marketing management processes. They are used as one of the key indicators in strategic planning, aiding organizations in assessing the current and future needs of its customers.
In marketing management, demand forecasting is used to predict the level of sales within a particular market. Demand Forecasting has been defined as a “process that involves making predictions about future sales by studying current sales and considering various factors such as market share, prices, promotion and distribution”. The other definition for demand forecasting is “the prediction of buyer behavior based on historical data gathered over time” which will help an organization to determine what product lines need to be changed in order to meet demand or produce more competitive products.

Quality forecasting is a process to forecast quality at various stages of the production or distribution process. The different types of demand forecasting tools are often available for a standard set of predetermined data sets. Demand Forecasting tools help organizations in determining how well they are doing in certain business areas, such as marketing and sales, in the short term and long term by analyzing demand patterns within the different market sectors.

In addition to forecasting revenue, demand forecasting also can look into sales potential, delivery schedules, production times and inventory levels. The information gained from demand forecasting can greatly impact various processes within an organization as it can help determine necessary capacity and processing requirements. This can help to increase production efficiency and enhance product quality.

Forecasting the sales potential for a product allows the company to determine what it is capable of selling. This lays the groundwork for its planning future activities, such as inventory required, sales promotion strategies and marketing campaigns. When companies are able to estimate their sales ability, they can better plan when and how much resources to commit in order to maximize their profitability.

Demand forecasting also helps an organization determine what types of promotional strategies they should promote in order to reach its maximum sales potential. Forecasting demand helps an organization refine its approach in promoting a product or service based on anticipated demand levels. When it comes to determining production needs, demand forecasting can help an organization determine how much inventory should be made available for sale. It also helps with determining delivery schedule and backup inventory levels.

Demand forecasting is a very important tool in the supply chain as it helps to yield control over the various activities within each process. The demand forecast will also determine how quickly a company must supply to its customers with products or services such as:

Demand forecasting plays an important part in the sales function of organizations and is considered a “driver” for long term growth and profitability. Demand forecasting aids organizations by providing them with information that allows them to make better decisions on their operations, e.g., sales force size, inventory levels, and production capacity utilization. There are a number of economic, technical and psychological factors that affect demand forecasting.

Demand forecasting is generally more accurate for large order size items. For example, disposable razors have a higher prediction error than toothbrushes. This is primarily because of the more complex purchasing decision involved in the use of disposable razors. Technological advances also significantly impact demand forecasting accuracy. The faster sales cycle time, the better the forecasting accuracy will be.

Adaptive demand forecasting processes are predicted as the most accurate. Adaptive demand forecasting is based on mathematical equations incorporating historical data to forecast future demand. How well an adaptive demand forecasting process does depends on how well it matches real world data.

Demand Forecasting helps companies to gain a better understanding of their customers’ needs and the products that can satisfy those needs efficiently and effectively. While there may be many ways to approach a specific business, an organization should be aware of all their options if it wants to achieve maximum efficiency and profitability from their supply chain process.

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