Today, another round of technological possibilities are coming to the fro, enabling retailers to make fundamental changes to their operations. A lot of it involves a new approach based on technology
The Indian retail industry has been struggling with a variety of problems. First, there is the challenge of the very high cost of infrastructure. To off set this it is essential to maximise sales for every square foot of space taken and invested in. While malls are getting fancier and more engaging, winning footfalls is not necessarily translating to increasing sales. This is dependent on both engaging the customer, as well as providing a strong value proposition to get customers to buy. We need to have the right products, effectively engage the short attention span of customers, get the pricing just right and have great service. If we step back a little, it is clearly an optimisation problem coupled with a customer engagement.
Globally, the retail industry hit upon a formula in the 1940s. It involved shifting from serving a customer over a counter to a self-service model and providing them with shopping carts. Since then, there has been little change from that winning formula until the era of e-commerce about 15 years ago. India has been rapidly assimilating that model. Today, another round of technological possibilities are coming to the fro, enabling retailers to make fundamental changes to their operations. A lot of it involves a new approach based on technology.
Aren’t people cheaper?
At first, it seems counter intuitive. Do we need to deploy more technology in a country where we have many people looking for jobs? Aren’t salaries low enough to allow retailers in India to work with a more people-intensive model?
A look at manufacturing might explain a different view. In the next five years, the country that will have the largest number of robots in the world is China. The same China that became the manufacturing hub of the world based on low cost labour is rapidly replacing people with robots. This shift is being driven, in part, by an increase in labour costs and a simultaneous drop in the capital cost of robots. Additionally, there is a change in the demand pattern of customers. Customers in developed countries, that form the main market for China, are asking more for customised goods and the demand for mass produced standardised products is starting to shrink. Making customised goods at scale requires automation, where a robot can be programmed to receive the unique specifications and tailor the product exactly as required. It needs no practice nor will it complain.
The situation in Indian retail is not very different. On the one hand, we have a pressure on wages for skilled staff . As the customer evolves, so too must the people who work in the industry. Simply putting warm bodies in stores will not be effective and is, in fact, counter productive. Couple this with dramatic advances in technology and the retail firms that ignore this development will suffer. This shift from a labour intensive model to an automated one is exactly what the Indian IT services industry is grappling with. As competition starts using automated tools to do what Indian companies were accustomed to putting together a team to do, cost structures and performance expectations are shifting business away from India.
In retail, brand and product proliferation are leading to increased complexity. At the same time, the pace of change has also increased and product life cycles are shrinking. Addressing these conditions requires a good mix of technology and people skills. The good news is that much of these are available today. The danger is that companies that are struggling with today’s problems will not evolve fast enough leaving the competitive space open for new entrants.
People don’t optimise well
The retail industry is a bit like the stock market. Retailers make punts on which brands and SKUs will sell when the customer walks in through the door. Retailers neither make nor consume. So, it is essentially a matching of what the consumer wants and is willing to pay for, with what is available and will give a good margin. As mentioned earlier, this is an optimisation problem. Like most other optimisation problems, people don’t do a good job at it. It becomes really difficult when there is an increase in scale or if things are changing fast. At that time, experience and judgement start to fail. Today, retail faces both of these complicating factors. There is an expansion in the number of stores and product proliferation. At the same time, there is a faster pace of change.
Last month, I have already written about the challenge of forecasting and replenishment. These are core operating processes for any retailer. Today there are powerful tools and methods available to support these processes and have been proven to work better than human judgement. Here, we will look at other areas where technology has stepped in to raise the bar and is helping deliver better profits.
In a recent experiment in the US, we had deployed a technology to track shopper movement across aisles in a specific department. The outcome of the study showed that most shoppers were entering the department, but walking through a single aisle and spending less than five minutes in that department. About 24 per cent were walking through two of the aisles and spending about 20 minutes. Less than 10 per cent of the shoppers were walking through three aisles and spending 60 minutes shopping. It also showed that more than 25 per cent of the aisle space was not browsed at all! Much of this information was new to the management. They immediately initiated redesign exercise to engage shoppers more effectively.
The ability to accurately measure what real shoppers were doing allowed for a tight feedback mechanism and makes better use of every square foot of space.
This technology did not require the shoppers to either carry anything or log into any app. All they had to do was to be themselves and shop. Sensing technologies today have become so versatile that it allows for sensing of the movement of people. This allows for more data-driven decisions on store design, assortments and planogram effectiveness. When this is coupled with sales data, we can get a more realistic picture of lost sales.
This data is not just useful for the retailer, but also for the brand. To take a single example, knowing how many people considered a brand and then moved on is extremely useful. Such data is very valuable to brand managers and providing this data could form another potential revenue source for retailers. This data can be provided in near real time and will have a great deal of granular detail on consumer behaviour. This would be especially useful when launching new products or during consumer promotions. As useful as this may be, other technologies allow for potentially even more useful decision making inputs. This time in an area of pricing.
If it is difficult to decide a stocking policy for a new product, it is much more difficult to decide on pricing. Pitching it too high or low can result in no sales to a loss of margin. It is to get a better handle on this that a technology like smart shelves has evolved.
Smart shelves are shelves with a combination of micro display units and sensors. The display units are like tablets that are mounted on the shelf face and communicate brand messages and pricing. The sensors are monitoring the buying behaviour. The smart shelf can make out how many people walked by and how many stopped to look at the display. It can make out whether the person is a male or female or an adult accompanied by a child. Different and appropriate messages to be tested can be displayed. It will have sensors to know if someone seemed interested or not. Did they pick up a product, look at it and put it back? Or did they take the product for check out? A wealth of data can be generated for more effective testing and monitoring.
These are advanced technologies but they are not rare technologies. Most of these technologies are already available in consumer products and are being adapted for use in such studies. The advantage of such off-the-shelf technologies is that they are already made in large volumes and are, therefore, cheaper. Many of the assembled units made today are still expensive, because it is early days. But, even then, compared with manual methods of observation and data collection, they will probably be comparable in cost and much, much more accurate.
Technology is coming our way. Much of it is very exciting. Much of it is also essential for future survival and growth. These technologies help us monitor a fast changing consumer base and adapt to it quickly. Th is could be by designing new products, selecting them or ensuring high levels of availability. As the Chinese manufacturers are probably thinking, we live in interesting times…
