Site icon Wonderful Engineering

Robotization in Retail: Latest Trends And Their Implementation In Business Processes

In nearly every industry sector, there are repetitive tasks that can and need to be automated. That is also true for retail. The brands that fail to keep pace with the rapid changes in customer demand, growing supply chains, and the latest trends in e-Commerce can’t survive on the market. What technology do retailers benefit from even today? Find the answers below.

Potential for automation

By process automation, we mean software that performs actions through the user interface, imitating the work of a human in various computer programs. Such systems leverage RPA tools, Artificial Intelligence, Machine Learning, IoT, etc. This technology helps businesses to increase productivity and reduce errors in performance. 

In 2017, the McKinsey Global Institute published research on business process automation across different industries. The center evaluated their ability to apply currently-known technologies. The results depended on the potential of individual activities in the sectors to be automated. The authors of the report also considered such factors as implementation cost, the regulatory requirements, evolvement of the labor market, and economic benefits.

According to the research, 53% of all retail operations can be automated. That means software can perform more than half of the tedious tasks that were previously the responsibility of humans. Such activities as data collection, data processing, and predictable physical work have the highest probability to be delegated to the computers.

In particular, RPA tools are effective in 86% of accounting and auditing operations against 47% of the activities in sales. This difference is related to the fact that some areas in retail still require human logic and social abilities. For example, the customers value personalized advice on what clothes suit them best or what product tastes more delicious.  

Which operations to automate

We recommend that the retailers consider robotizing the following processes using existing IT solutions:

According to Gartner, by 2022, 70% of all communications with customers will be carried out by chatbots, Machine Learning, Natural Language Processing, etc. Consumers consult these systems to receive information about a product, track their order, or obtain assistance on solving technical issues. The services rendered by such technology are available 24/7 and save time for both customers and salespersons.

Organizations can find it hard to structure product data from various vendors that follow different standards. 

In 2017, the Everest Group published a report that, among other things, described the transition of one company to an automated solution to harmonize its product categorization. The company had products in several markets with different Stock Keeping Unit systems. The technology allowed it to structure data in diverse formats (images and text) and from multiple sources. As a result, about two-thirds of the entire process was automated, which led to 98.5% accuracy in product classification.

Monitoring and controlling goods and stock are much more effective with the use of automation solutions. They include, among other things, reporting and real-time data exchange between different systems. The latter allows retailers to expedite order processing. Predictive analytics helps the companies to anticipate customer demand and thus, to eliminate product losses.

About one-third of the efforts of employees across all industries in the United States are focused on collecting and processing data. Organizations can significantly reduce costs by using robots for these purposes. For example, there is software that processes information in Excel spreadsheets. That allows employees to save time on preparing reports, for instance, in accounting or sales.

The latest trends in process robotization

There are two promising trends in retail automation worth mentioning.

  1. Predictive analytics 

It is this software that leverages both statistical data and Machine Learning to make forecasts of customer demand. This tool processes large amounts of structured and unstructured data that belongs to the company. For example, it has access to the clients’ data from CRM. The system also analyses external information such as laws, economic situations, and even weather forecasts.

Then the software proposes different types of estimates depending on the raw data and the expected result. The program calculates numbers or assumes if a person or an event belongs to one or another category. For instance, such a platform can estimate customer lifetime value or predict if a site visitor is going to make a purchase. In the latter case, the system gives the result as 0 or 1. The lower number means that the event is not going to happen.

With the help of PA, the retailers can make short and medium-term forecasts. They anticipate demand for seasonal goods and new products without a long-standing sales history. This tool tells the firms when to raise or lower prices and how to manage inventory. Personalized customer interactions enable companies to build brand loyalty and achieve better KPIs in marketing and sales.

Such a system is indispensable in large retail chains. Imagine that you have a thousand stores of various formats and fifty thousand item names. PA tools help you calculate exactly where to stock more rice and where to bring in pasta. What is more, the software takes into account not only the purchase history but also some specific information. For example, the average age of consumers or the location of the store in a wealthy or poor neighborhood matters as well.

  1. Automated ordering 

Manual stock replenishment proves itself to be inefficient. When doing it manually, people rely on historical data and personal experience. But the latter may turn out to be wrong. It leads to out-of-stocks and product losses.

Order management software does the processing and structuring of historical data. The system divides the information into blocks and analyzes it using AI and ML algorithms. Then the technology calculates the best product distribution scenario and completes orders automatically.

The basis for such a solution is micro forecasting or calculations for individual units of goods. At the same time, the software takes into account information about promotions, product seasonality, and price fluctuations. The system also makes adjustments to the ordering process during holidays. For example, it knows how many bottles of champagne to distribute to each store for the New Year.

Among the well-known retailers using this technology is dm-drogerie markt. This large retail chain has almost completely automated its orders. Now its customers in more than a thousand stores across Europe have access to the right goods at the right time.

How to implement automation in retail

To introduce new solutions into their processes, the companies should perform analyses of their current state. That will help them to decide which operations to automate. We recommend starting with business processes that correspond to at least one of the following criteria:

Enterprises should start using new technology gradually, proceeding from simple processes to complex ones. The introduction of advanced solutions will inevitably show the difference between the ideal procedures and the existing state. That’s why, even after the companies train their staff on the new approaches, they require an adjustment period. Therefore, we advise retailers to be patient and measure results in phases.

Conclusion

According to the Worldwide Artificial Intelligence Spending Guide published by the International Data Corporation, the use of cognitive and AI systems in various industries will continue to grow rapidly. Global enterprise investment in these technologies is expected to reach $77.6 billion by 2022.

The breakthrough solutions are fundamentally changing the way the markets operate, giving their users remarkable advantages.

Robotization in the retail industry benefits both businesses and customers. Such systems are capable of operating round-the-clock, without days off or vacations. They are reliable and don’t make mistakes, performing the same kind of job hundreds of times. Robots adapt to changes, such as increased sales. It is often easier for companies to reconfigure the system than to retrain a specialist.

The performance of a robot is higher than that of a human. That means one computer successfully replaces several employees. All this leads to lower costs for organizations. Finally, the machines record all of their actions, so the experts can easily track every single operation.

Exit mobile version