Data-driven human touch
Seattle celebrated April 29th as the “Independent Bookstore Day”. The independent bookstores in the area were trying to fight Amazon’s move to build brick and mortar bookstores. Tweets said, "April 29. Independent Bookstore Day. Why not take a break from the corporate chain retailer today and support a local indy merchant instead?" The bookstores organized events where readers could go visit almost 30 bookstores and hopefully stay on as loyal customers who would shun all deals on Amazon.
It must be hard for the independent bookstores to compete with the behemoth. After all, Amazon is a data company. The brick-and-mortar bookstores are just labs to gather more data and insights about customers.
“Individualization needs data.”
What does that have to do with Human Resources? In the past, HR was all about creating one set of rules then applying those rules to all employees.
Today, employees expect a customized experience from all employers. The process of creating an individualized experience is dependent on the unique identifiers we have for an individual.
While most corporations have still stayed on with gender options being limited to three at best, Facebook offers 71 gender options to UK users; and this allows them to target ads more specifically. Facebook allowed people to type in whatever they wanted to describe their gender, and from that data-set created more categories.
That is just what Amazon is doing at scale. By telling people that there is a set of books that have more than 10,000 reviews on Amazon.com, they are simplifying the decision-making process.
Imagine a company that can put data like this on their website to say “Consistently rated at 4.9 on a 5-point scale on Glassdoor by 2500 employees”.
Amazon constantly gathers data about individual choices — online shopping and browsing histories provides rich data that is hard for any other bookseller to match — and then creates an individual experience or club common choices to create experiences at scale.
Simplifying consumer decision-making adds speed. When combined with individualization, it seems like a winning combination that any other bookstore would find it hard to match. Like the Amazon bookstore — all through the store there are examples of how a company can leverage data to customize experiences, scale up and gather data for the future.
Idea 1: Customize experiences – “If You Like Zero to One”
The Amazon bookstore blurs the line between online and offline shopping experience. I noticed a shelf that stated “If You Like the Book ëZero to Oneí by Peter Thiel. The shelf has several books that give advice to people who hope to start their own venture someday. The books are on a range of topics from lean startups to raising capital.
HR can gather data about training courses that are popular and use that data to customize the experience for individual employees. “Those who liked our course on ëLeading in Growth Marketsí also signed up for the course on ëManaging Talent in Fast-Growing Economiesíî.
Imagine being able to nudge people in the Sales Team to say, “92 percent of the Sales Representatives have completed the course on ‘Selling to Busy Professionals’. Or to capitalize on a trainer’s effectiveness, “95 percent of participants rated the class on ëNegotiation Skillsí by Semira at 4.8 or higher.”
You probably track some of the data today. Get your team to brainstorm what other data points you would need to be able to get these details. It is never too late to start.
Idea 2: Scale-up – Books Kindle Readers Finish in 3 days or less
Most bookstores will have predictable categories like fiction/non-fiction etc.; but Amazon draws on real-time data to classify books in its brick-and-mortar stores. They have categories that are impossible for competitors to replicate:
• Fiction top-sellers in Boston/Chicago (whichever city the store is located in)
• Highly rated fiction on Goodreads
• "Books Kindle readers finish in 3 days or less"
Their recommendations are specific to the city. That enables them to scale-up and capture the market. The travel section has books about Florida, the Caribbean and Midwest states like Ohio and Michigan – the areas Chicagoans like to travel. The store in Chicago has lots of biographies because that is what their data tells them.
Imagine if HR could collect data to serve food in the cafeteria that is specific to the employees in the city. Or for example, an overwhelming majority of employees love watching movies by a certain actor can be used to design everything from the Annual Day to team outings.
Being able to announce at a campus that 83 percent of alumni from a specific college have got promoted to the next level in 18 months can be a great draw. Or to say 84 percent of our most successful leaders have worked in two or more geographies is a great data point to convey. Or that one-third of our supply chain team is made up of ex-servicemen. Or saying that 4 out of 5 managers are now reading XXX book can encourage others to follow suit.
Idea 3: Gather data for the future – “Alexa switch on the light and fan”
The bookstore has a small section where Amazon’s intelligent personal assistant Alexa is available for shoppers to play with. Alexa understands voice commands just the way Apple’s Siri and Google Home do. In the store, Alexa is hooked up to a table lamp and a table fan. Visitors stop by and ask Alexa to play music, read out the news, answer simple questions and switch on the light or fan. Once Alexa does that, the next obvious thing people do is to ask Alexa to switch off the light and fan.
Then some visitor gets creative and says, “Alexa, turn off the light but keep the fan running.” Alexa has difficulty understanding the command. But the command gets stored in the cloud for the researchers in the lab to program Alexa in yet another way. The store serves as a lab to find out the many different ways in which people frame voice commands. And the kind of services they expect. A kid asks, “Alexa, can you do my homework for me?” Another hint for what the Amazon scientists will work on next. The bookstore serves as a lab for ideas that will help grow the business in future.
Imagine having a robot that answers routine questions on HR policies or runs a new hire orientation about the company’s history or publicly available financial data.
When someone asks if they have “Pawternity Leave” (when the pets need you) it could be a great opportunity to see how many people ask for it. That in turn may be a way to delight the employee. Creating a database of questions asked during hiring, it is possible to find out which questions are predictors of competencies needed in the company. Creating a database of responses by candidates can provide great insight if there are common statements that successful candidates have in common.
HR people have often avoided adopting technology by claiming that HR is about high touch. HR in the near future will be all about data-driven human touch. HRD will soon stand for Human Resources Data. Is your organization ready for it?