Three Ways to Leverage All Data at Your Disposal

October 18, 2018

by Nancy Boas

Shutterstock 336698507

Data is not what it used to be. There was a time when companies of all kinds had a mandate to gather all the data they could in order to get an edge with their customers and to understand their businesses better. Today they have the opposite problem: a data deluge. Most companies have more data at their disposal than they know how to leverage, creating, in many cases, ‘data paralysis.’ Nearly a decade ago, The Economist wrote an insightful article on this, indicating that “the process of learning to cope with the data deluge, and working out how best to tap it, has only just begun,” adding to their argument that only credit card companies were using all data at their disposal, and even predicting the Facebook data breach issues we’ve read about in the past year.

The good news is that innovation has kept pace with the growth of data, and companies can equip themselves to become data-driven in very smart ways, effortlessly, without losing focus of their core businesses. After all, if you’re a retailer or a coffee chain, you should focus on providing amazing experiences, not on running a data operation. This article explores three approaches regarding the data at your disposal – and not only the data your business generates. After all, data is human and you should apply it to delight your customers, engage your employees and improve your business in general.

Use data to forecast demand accurately

The closest equivalent to having a magic ball to predict the future is having access to all relevant data that determines it, and the means to make sense of it. Let’s go back to the coffee chain example. Imagine you’re the manager of one of their stores in Portland, Oregon and you need to forecast demand for every day of next week so that you can staff accordingly. Traditional methods will have you look at past year’s sales for the same week and extrapolate, see growth trends and maybe sales this week. These methods may get you to 60 or 70% accuracy, which means that you will either be understaffed if you under-estimated demand, or you will have idle or unhappy employees whose shifts never happened because you over-estimated it. Both are losing options. They lead to unhappy customers and unhappy employees. Yet you had all the data you needed to predict demand accurately if only you knew where to look.

Enter Artificial Intelligence: hype aside, one of the best uses of AI is to connect seemingly unrelated pieces of data that the human mind is not designed to connect quickly. So, if the manager of that cafe had looked at the weather in the area of the week of last year, rather than just sales, she would have noticed that temperatures were unusually hot (blame climate change), while this year’s winter is already here. This weather translated into people wanting more water and juices than coffee, so if she is looking how to staff the different positions for next week and does not know this central piece of information and just goes with what happened last year, she will not have enough baristas.

This is only one variable. Local events, national sports championships, whether there is a street closure nearby… you name it. AI will find all variables, make the numbers and tell you what sales will be in a matter of seconds.

Use data to engage your people

Forecasting demand is only part of the job when it comes to using all data at your disposal. Your own people generate tons of data that, again, a normal person will have to spend hours to make sense of and match with your business needs. Happily for you, millennials, who have fully entered the labor force and are even reaching management positions by now, generate data 24/7. They were raised with smart phones and with a sense of having their voice heard. Millennials are transforming the workplace (see our article about them here). Your employees can give you enough data through a mobile app for you be able to match their preferences and skills with the demand data you forecasted – using AI and Machine Learning.

Retail for example, is a tough business. When it comes to hourly workers, rotation is huge, and motivation quite low. The main problem seems to be that employees do not feel in control of their workday – they may be called at the last minute, they may be idle on a shop for hours, or they may simply not have the certainty about the hours when you need them so that they can have a second hourly job to make ends meet.

CultureIQ wrote an interesting piece titled “Company Culture and Employee Engagement Statistics,” where they discuss the issues unique to retail and give some tips on easy things to do to keep hourly workers engaged and happy. One of these pieces of advice is respect. They cite Angela Ahrendts, SVP of retail and online stores at Apple, who pointed to treating store employees with respect as the key to retention. “I don’t see them as retail employees. I see them as executives in the company who are touching the customers with the products that…took years to build.” They added that “her approach seems to be working, as Apple’s retail retention rate has gone up under Ahrendts’ leadership.”

Respect comes easy when you use technology to match employee skills and preferences to demand forecasts, and you do so by engaging them with the tool they can’t live without – their mobile. They can tell the system what hours they prefer, or what shifts are a total no, which can then become open to swapping.  They can even swap shifts directly with other employees, without having to go through their manager. All a manager has to do is see a notification and approve it. The days of using Excel or other labor-intensive tools to match demand with labor are over if you use your data and technology to make sense of it.

Do nothing with data

The last approach to data is to keep business as usual and pretend all that data you have at your disposal – POS, foot traffic, employee preferences, events, weather, etc. – is too much and keep overworking managers in hours of forecasting and matching with imperfect data instead of freeing them to actually manage.

We live in a world of data – yet you don’t need to be a data expert to make sense of it: that is the job of technology. Unfortunately, many companies in all industries – especially in brick-and-mortar industries – still need to cross the chasm. That path is simple, just follow these rules:

  • Embrace all data at your disposal
  • Use technology to make sense of it
  • Apply

All in an easy way that does not require you to hire rocket scientists.

Here is an easy choice you can make with Legion.