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 of which new product ideas are worthy of investment.
And that’s before you even get to developing new products in emerging categories, where no previous data exists.
So as a switched-on business, how do you build new product use cases that avoid a warehouse of excess stock, or a glut of unhappy customers who missed out?
Businesses generate huge amounts of valuable data every day, and the importance of this should not be overlooked.
It’s imperative that you capture and record pertinent information, wherever possible, for example:
Historical sales data of similar products in your business
Current sales data of similar competitor products
You can then begin to make predictions, based on the likely impact of:
By combining this hard data with educated predictions, you can start to form a picture of what might happen in the initial three months after launch. But with today’s developments in technology, what was once the final step in the new product demand forecasting journey, is now just the beginning.
Innovating in the age of AI
Not-so-fun fact: around 80% of new products fail. But imagine if it was possible to take some of the guesswork out of the equation, so you could stop backing the wrong horse before the race even started. With AI (Artificial Intelligence), ML (Machine Learning) and Big Data in the mix - this is now a reality. Demand forecasting systems that are driven by these technologies have the power to draw on historical performance-based data, and combine this with huge data sets from well-considered, trusted sources across the internet. They can then deliver real-time insights and predictions that can help you to eliminate some of the uncertainties around new product launches.
The right mix of technology acts as a crystal ball, making it easier for businesses to put their time, attention and investment in the right place, at the right time.
With these tools behind strategically-skilled people, it’s now possible for businesses to do what was previously impossible. Meet 100% of demand with zero waste.
QU - a tool for the times
QU is an AI-powered SaaS demand forecasting tool developed to measure, analyse and predict product performance in real-time. Hosted on and supported by AWS, QU uses the latest AI technology, 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 predicts buying behavior and adjusts forecasts of future sales to individual product levels (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…
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 […]
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 […]
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 […]
Demand forecasting is always wrong. Thankfully. 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 […]
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 […]
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 […]
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 […]
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 […]
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.