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“RETAILERS HAVE COLLECTED MUCH DATA. BUT ONLY MARKET LEADERS ARE ABLE TO WORK WITH THEM ”

In March, the annual Digital Transformation conference was held. Participants shared fresh trends, statistics, and digital transformation experiences.

We recorded a summary of a speech by Alexei Belkin, a partner at McKinsey & Company.
Retail Trends
Retailers have accumulated a huge amount of user data. But only leaders can work with Big Data in retail. In small and medium-sized companies, the basic level of analytics dominates: managers process reports manually.

The result is a subjective approach, fragmentary analysis, errors in decisions.

Automation will help bring retailers to a new level. The main thing is to catch this trend and start changing now.

Partner at McKinsey & Company on how to use advanced analytics in business.

Artificial intelligence makes a decision for a person in the following areas:

Commerce. Automated pricing, assortment matrix management, supplier comparison.

Logistics. Algorithms are responsible for building a warehouse model, order picking, transportation, demand forecasting.

Operating vertical. Artificial intelligence plans processes within stores, draws up work shift schedules, and considers employees time.

Marketing. Attracting and retaining customers, managing loyalty algorithms.

HR It’s possible to select staff, deal with layoffs, and adjust the motivation system without human intervention.

Finance. High technologies are responsible for forecasting revenue, calculating and adjusting the budget, developing and updating business plans.

Analytics is able to predict literally everything – from the demand for certain types of goods to the dismissal of employees. But this does not happen everywhere. Small players lag behind the giants.

To understand how wide the gap is, consider five levels of decision-making automation:

Analysis of facts and trends is a basic level of analytics. Managers in small companies work with her every day.

For example, they analyze business results according to specified parameters.

Dynamic factor analysis is a more “advanced” analytics. Makes in-depth analysis on non-standard data sections and additional metrics.

Often experts call for help to the manager.

Basic forecasting helps to make management decisions. For example, you can predict the rate of outflow of customers or the reaction of consumers to a new share.

Multi-factor forecasting is used only by advanced companies. Often it becomes a competitive advantage of a brand.

Together with a team of analysts, managers create new forecasting tools, such as CDT (decision tree), Marketing ROI (return on investment in marketing), People analytics (employee performance forecast).

Predictive modeling will describe scenarios of development of events, will point out critical factors. These models are based on machine learning algorithms and other Big Data technologies in retail.

Managers often use them to “look into the future.” For example, calculate the likelihood of an employee being laid off and develop retention scenarios.

Small online stores balance at levels 1-3. Levels 4 and 5 are available only to retail leaders.
Key retail trends in Russia and the CIS
Retail income has been growing very slowly over the past 10 years. The trend has been outlined in 2016 and will not change until 2020. Nominal growth – 6% per year.

Actual – only 2%. The exchange rate is unstable, inflation is increasing, and consumers want to save.

The cost of goods is the main criterion for half the inhabitants of the region. At the same time, buyers in the CIS are choosy: they want to buy not cheap stuff, but branded products at a bargain price. The trend is forcing retailers to come up with new discounts and coupons, launch promotions.

Loyalty to retail chains remains low. On the way home from work, the average consumer enters three supermarkets. It is important for people that the point of sale is located nearby, and the goods in it were fresh and inexpensive.

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A completely different situation in Western Europe: customers are so attached to the brand that they refuse to go to other stores.

Foreign experience: For the convenience of regular customers, the Norwegian company Kolonial installed kiosks along the way from the center to remote areas. The buyer can pay for the goods on the site and pick up the products where he wants.

The largest retail chain in Britain Tesco offers to order products on the way from work and promises to deliver them to the client at home right by the time of arrival.

Residents of the CIS often shop for small amounts. Europeans, on the contrary, visit stores less often, but shop thoroughly. By the way, the second approach is recognized as more economical in the long run.

In the coming years, retail will learn to more accurately predict regional demand, market fluctuations, and inflation.

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