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demand forecasting

Businesses in every industry are facing increasing demand volatility. Additionally, with  rapidly evolving market conditions, it has become vital for businesses to stay prepared and anticipate the future. To cater to these fast-changing market dynamics, the practice of demand forecasting began. Today, several businesses, especially those belonging to the FMCG sector, have sophisticated demand forecasting models in place, which help them stay ahead of the market.

The Need For Demand Forecasting

An area of predictive analytics, demand forecasting takes into account the historical data of a business and uses that to harnesses the demand for their goods and services. This knowledge is crucial, especially in today’s business landscape, as it allows suppliers to estimate and hoard the right amount of stock at their disposal. But having this knowledge isn’t enough. The major challenge is to ensure that the forecast made basis this knowledge is accurate. For instance, if the demand is underestimated, sales can be lost due to the lack of supply of goods – which is referred to as a negative gap. Similarly, if the demand is overestimated, then the supplier is left with a surplus – also referred to as a positive gap – which then becomes a financial drain.

It is important to understand that many business decisions depend on demand, like production, sales, staff requirement, etc. Good forecast helps in appropriate production planning, process selection, capacity planning, inventory management, etc. It also provides reasonable data for the organization’s capital investment and expansion decisions and eases the process of suitable pricing and marketing.

The Science Behind Demand Forecasting

Demand forecasting should be done on a scientific basis, and several facts and events that can have an impact on demand need to be examined, studied and taken into consideration to make an accurate forecast. Traditionally, demand forecasting involved sales managers coming together at the end of every three months to analyze the sales statistics of the bygone business quarter. Basis these discussions and findings, the demand was predicted and a rolling plan was prepared for the upcoming three months.

But, businesses soon began to realise that the traditional methods of manually interpreting data to forecast demand aren’t practical – given that they operate in a market that is characterised by fast-changing customer expectations. They realised that to reduce their margin gap, it was important for them to be agile and adopt a more data-driven approach that can deliver results in real time. That’s when they turned to technology for aid.

Today, several methods involving data science, statistical model, trend line, time-phased analysis, data mining and more are used to predict consumer demand.

Our Take On Accurate Demand Forecasting

At BizAcuity, we enjoy expertise in solving complex analytical problems using data science models, analytics and other sophisticated technological approaches. By working with several clients belonging to diverse backgrounds like gaming, events, manufacturing and more, over the years, we have garnered great insights and developed great proficiency in this domain. This has given us an edge to help businesses devise an efficient solution to forecast demand.

We began with understanding the problem in detail. Soon, we realised that to make a more accurate forecast, it is important to incorporate and take into account more variables into the model. This way, a wide range of data at every level of the supply chain could be captured and taken into consideration.

For example, a regional sales executive may have important inputs and findings pertaining to his market, which when studied and taken into consideration, could prove beneficial in understanding the business dynamics in detail. Such data, when fed into the model for computation, can help in tailoring a more accurate prediction.

Capturing such data today has become easier than ever before, all thanks to digitization. Now more and more factors can be taken into consideration by collecting data at every level, across all markets. It is these small details, which when put together, help in framing a completely different picture of the demand of a particular product or service.

Demand forecasting is a problem that we have studied and understood thoroughly. Our solutions are rooted in technology and can cater to a wide range of businesses. There are things that our solutions bring to the table, which not only improve the margin gap but also enhance the business scenario in general – just what today’s businesses need.

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