“Inaccurate information and planning processes create more inefficiencies, meaning less time is spent on strategic initiatives to win share."
The post How poor planning is costing retailers sales – and profits appeared first on Inside Retail Australia.
Significant market trends are impacting retail businesses today – the migration of consumers online, supply-chain challenges and the cost-of-living crisis to name just a few – but there is a more obvious reason many retailers are struggling.
Working with retailers across Australia and New Zealand, Quantiful CEO Jamie Cormack has identified poor planning outcomes as one of the significant causes forcing retailers to contract and even close stores today.
“Inaccurate information and planning processes create more inefficiencies, meaning less time is spent on strategic initiatives to win share,” Cormack tells Inside Retail.
“When you lose control of your in-store demand, your stock starts to age, and you lose the agility to maximise return on faster-moving products. If you only look at the stock turn, you may be too late to determine the root cause.”
Quantiful has created an analysis titled Why Planning Accuracy is Key to the Future of Retail which uses real-life experiences of Australian and New Zealand retailers to illustrate the challenges they face and the positive impact of grasping accurate, technology and data-backed planning solutions on retailers’ turnover and bottom-line performance.
“It is possible to reverse the trends and fix the problem – but it requires some bold decision-making and execution by company leaders to adopt specialised AI planning tools that have been proven to solve these challenges.”
That’s where Quantiful’s technology comes into play. It leverages cloud-based, AI-driven solutions to combine customer data with external data to tackle upcoming issues before they materialise as aged or out-of-stock problems.
“We never relied more heavily on the fundamentals of planning because it is the perfect complement to our AI solution”, explains Cormack. “It can be immediately implemented to turn some of your key metrics around, and it’s also clear that not deploying these solutions may result in your competitors rolling over the top of you.”
AI plays a critical role in the process. If trained correctly by drawing on data from throughout the retail business and with external sources such as econometrics, search, and social media, AI-driven forecasts can deliver at speed and scale and are best when combined with judgemental forecasts where the business activates promotional or other demand-driving initiatives.
As the report notes, the benefits are more productivity because staff can focus on the priority exceptions and not get buried “in Excel drudgery,” says Cormack.
“All this leads to bottom-line benefits for retailers, and a happy workforce able to work on strategic initiatives to win markets.”
For example, if you ask Quantiful’s AI engine to predict 15 days of demand in 45 days, you can expect a forecast with up to 85 per cent accuracy down to SKU location level.
“This is a ‘magic wand’ that can equalise stock availability with working capital to a high degree of probability,” he says. “Accurate forecasts drive confidence, build trust in automated operational execution and performance to key business metrics.”
There is no practical limit to the number of sales events AI can ingest and process. When combined with external data such as environmental, social, and search information, it makes the forecast more accurate and illustrates a picture of consumer behaviour and company performance.
“The innovation is a demand planning tool that delivers accurate forecasts and illustrates what is driving demand.”
While most retail executives understand the key drivers determining whether their business is turning a profit – factors like sales revenue, inventory turnover and margin management – such information can often be siloed in different company divisions. Cormack explains it is too fraught with bias, and onerous, trying to disaggregate a top-down forecast and reconcile it with actual demand from the market. Good planning tools arrive at consensus forecasts from every area of the business.
For example, an assumption in a planning process may be that people are transacting less. However, consumer demand is stable or growing in many categories despite the challenging economic environment. So consumers are still shopping, albeit differently, making it more important to identify the changes in behaviour. So, where do you determine the changes in shopping behaviour?
“We need to look beyond the store,” he says. “We look to whatever data sources contain signals about that buying behaviour, such as social and search, which are well-known sources of consumer pre-purchasing behaviour.”
The next job is to match our replenishment process with this new consumer demand, and good replenishment tools allow us to manage our working capital availability against stock availability risk.
“The ideal target for stock availability for every retailer is 100 per cent – but the more a retailer focuses on that target, the greater the risk of carrying aged or obsolete stock,” explains Cormack.
“When your demand and supply are equalised, you have a high stock turnover and cash conversion cycle, leading to maximising margin on products early in their life cycle. “Too often, Quantiful is arriving in businesses whose stock is aging. The company has fallen into the trap of high discounting to clear aged stock late in the product lifecycle.”
AI-driven planning technology will minimise stock levels across your distribution network and allow you to dynamically set inventory levels at every point a consumer purchases your product by accurately predicting SKU location and demand plans.
As the report concludes, deteriorating metrics end in lost sales and poor use of cash, but with the right tools, historical lost sales can be measured to ensure they are not repeated in future.
Cormack says the optimal inventory turn rate is around nine times annually – or every 40 days.
“Consumer demand can vary by geography or by a single store. This means that your planning tools must be dynamic enough to understand the demand at each location. You can no longer categorise stores by size or transactional velocity to set product range and depth.”
The post How poor planning is costing retailers sales – and profits appeared first on Inside Retail Australia.
