If demand forecasting was a precise science, we would be out of business. Organisations would apply their tried and tested formulas, and would emerge from their endeavours armed with 100% accurate predictions to take into their next phase of demand planning. Their wash-ups would show an exact correlation between their assumptions and commercial reality. Nothing would ever run out of stock and the world would have a far less alarming waste problem.
Sound familiar? Anyone…?
We know that contemporary markets are more volatile than ever before. Predicting demand according to what has gone before gives us some idea of what we might expect, with actual sales then providing metrics to test those assumptions against. But by that point, it’s too late. When businesses over or under order according to inaccurate forecasts, the results can be catastrophic for their bottom line.
Many wrongs often make a right
High error demand forecasts are actually very useful, it’s just a question of being able to learn from them on the fly. Historical business data and seasonal marketing activity can help businesses set some assumptions, but changes in the market along with macro and local events and supply chain disruptions can all impact consumer purchasing behaviour. With the right technology in place, businesses can see how these volatilities affect their assumptions in real time, identifying exceptions before they make firm decisions and place orders.
Demand sensing - good enough for Ikea
With recent developments in Machine Learning, businesses can make timely, accurate predictions about changes in consumer demand. Clever algorithms can automatically recognise patterns, navigate complex relationships in enormous data sets and flag the possibility of deviation from forecasts.
Retail giants like Ikea are realising the benefits of enhancing their demand planning with AI-driven forecasting, developing a proprietary system to give themselves a competitive edge. With 450 Ikea stores and e-commerce across 54 markets, even the slightest error margin can create significant commercial disruption. This is why the company has invested heavily in more intelligent “demand sensing” systems that can react and respond to anomalies in real time, rather than having to solve issues after they have occurred. The company’s lower error margins have reduced its carbon emissions (due to decreased movement of excess stock), lowered waste levels associated with obsolescence, raised profits and increased customer satisfaction.
QU - a tool for the times
QU is an AI powered SaaS demand forecasting tool that has been developed to measure, analyse and predict product performance in real time. Using the latest AI technology along with proprietary ML algorithms and innovative design, QU draws on millions of data points from hundreds of sources. It presents powerful insights in an easily-digestible and customisable dashboard that not only predicts buying behaviour, but adjusts forecasts of future sales right down to individual product level (SKU).
QU is a tool that is designed to empower people, giving them the insight and control they need to do better business.
So if your business is ready to start freeing up resource and firing up profitability…
Understanding demand patterns in the Data Age Demand pattern analysis is becoming increasingly valuable in business, as a way of predicting and preparing for future fluctuations in market demand. The problem is that the “best-practice” models that are still taught and employed today rely solely on historical patterns to make predictions. In reality, looking backwards […]
Forecast. To predict or estimate a future event or trend. Let’s start with a forecast we’re all very familiar with as an example - the weather. Once upon a time, forecasts were based on historical data captured around certain dates. Then, with the invention of telegraph networks, weather conditions could be observed and shared across […]
Not all SKUs were created equal Many businesses are so focused on building revenue, their profit suffers as a result. Organisations worth their salt know that selling at all costs doesn’t make good business sense. A more sophisticated way to measure and drive success is ROI (Return On Investment). What is the business cost of […]
A formula for accurate demand planning at store level (Hint: it doesn’t start with “=”) Technology is the biggest enabler of people in the digital age. Yet arguably, it’s also the biggest threat to the modern day workforce. When it comes to using technology to enhance demand planning in business, harnessing digital tools in a […]
Inject the smarts into your new product planning Consumers now have more choice than ever before - of what to buy, and where to buy it. The explosion of e-commerce has driven product and competitor proliferation to all-new levels, so what worked before (i.e. analysing previous product performance) no longer serves as an accurate indicator […]
The not-so-basics of Demand Planning At its simplest, effective Demand Planning means reducing the gap between held inventory and actual sales. It’s about meeting demand in the most efficient way possible to help retail organisations avoid stock-outs at one end of the scale, and wastage at the other. Yet this vital role is often drowned […]
Top-down or bottom-up? How to approach forecasting in a data-driven world. The role of any good Supply Chain Manager is to ensure regular reporting of the variances between top-down executive targets, and the bottom-up demand of the market. Effectively, this is the budgeting process, and achieving a balance between demand and supply is the best […]
Demand planning + supply planning = integrated business planning If demand planning is forecasting customer demand, while supply planning is managing supply according to these forecasts, you’d be forgiven for thinking that these functions went hand-in-hand. All too often though, demand planning and supply planning departments work to different agendas. One driven by ensuring sufficient […]
To provide the best experiences, we use technologies like cookies to store and/or access device information. Consenting to these technologies will allow us to process data such as browsing behavior or unique IDs on this site. Not consenting or withdrawing consent, may adversely affect certain features and functions.
The technical storage or access is strictly necessary for the legitimate purpose of enabling the use of a specific service explicitly requested by the subscriber or user, or for the sole purpose of carrying out the transmission of a communication over an electronic communications network.
The technical storage or access is necessary for the legitimate purpose of storing preferences that are not requested by the subscriber or user.
The technical storage or access that is used exclusively for statistical purposes.The technical storage or access that is used exclusively for anonymous statistical purposes. Without a subpoena, voluntary compliance on the part of your Internet Service Provider, or additional records from a third party, information stored or retrieved for this purpose alone cannot usually be used to identify you.
The technical storage or access is required to create user profiles to send advertising, or to track the user on a website or across several websites for similar marketing purposes.