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More Meaningful Employee-Employer Relationships through AI

For many, AI invokes images, hopes and anxieties of robots, autonomous vehicles and lost jobs. For Aaron Zuccolin, Managing Director of Traction University, AI is about driving more meaningful conversations and interactions between people. Companies that leverage AI to automate the impersonal and augment the personal will be able to drive deeper, longer-term relationships with their employees. Through automation, companies can provide employees more meaningful types of work, helping that employee feel more fulfilled while increasing productivity.

Moving Beyond Short-Term Work Engagements

In today’s competitive marketplace, it’s becoming increasingly rare that an employee remains with the same organization for more than a few years. This can be costly for both the employer and the employee. Investing in talent for two to three years and then restarting with a new employee is an unsustainable hiring model. Employees, on the other hand, are looking for meaningful career development paths that may not be available at their current company. However, jumping from firm to firm may not yield the development opportunities and career arc that they’re looking for. Leveraging AI can help ensure that win-win opportunities are flagged for discussion.

Aaron Zuccolin, Managing Director of Traction University

If you understand an individual’s skill set then you can match them with the right kind of work and also search for whitespace in their career development path. For example, soft skill development may help someone in delivery transition to a role in pre-sales. If you have the right performance management data about job skills, soft skills and past experience and training, AI can suggest additional training and content specific to each individual, whether they learn best through videos or experiential training. AI can even suggest a time, location and appropriate instructor, going as far as setting up an online meeting if all attendees work in different locations. In practice, AI doesn’t replace human interaction, it simply augments that interaction with meaningful data and helps organizations reduce manual admin work.

“As humans, we tend to rely on anecdotes and AI helps drive the right questions based on real data,” says Aaron. “The human conversation is informed by the data and AI-driven suggestions help guide that interaction.”

A Scientific Approach is Needed

“The key to success with AI and predictive analytics is to understand the question that you’re trying to answer. Often, organizations start by visualizing their data in an analytics solution and immediately go on to make in inference. That’s problematic because that data may contain significant bias. It might not actually be statistically valid. Figure that out first and if there’s an issue, rethink your approach. Retest your hypothesis and perhaps change the way that you’re collecting data,” Aaron suggests.

Ask good questions about your data:

  • Do I have a good data set that will drive an outcome?
  • Do I have outliers? If so, what do they mean and should they be excluded?
  • Is there something worthwhile that I can prove scientifically? If not, what do I need to do to change the data that I’m collecting?

Companies looking to leverage AI need to be very clear about the outcome they’re trying to drive and seek out the biases they’re already making about what the machine will learn or predict. They need to understand human bias by role alongside the different personality types within their company and ensure that their data collection is all clearly thought out.

Empowered Employee, Enabled Company

Companies also need to ensure that the way they’re using AI and their data aligns with the positive outcomes that they’re looking to drive. Are they trying to create win-win scenarios that foster company growth as well as career growth for their employees?

“Let’s say a company is opening up a new line of business and out of five candidates, Lisa has the best alignment in terms of skills and interests, but her current role would not make her the obvious choice. If the company is able to draw from their data and recognize that Lisa has the best chance of success, they might identify her as a fit to take over that line of business and provide her the training that she needs to make that transition,” says Aaron. “If they don’t, Lisa is going to move on somewhere else and the company will need to start all over again.”

What today’s AI allows us to do is launch investigations into new roles, new types of work and new methods of communication. AI has the potential to be a force for good, creating opportunities that drive employee engagement and better productivity for companies. At Traction, for example, we’ve leveraged our Pulse application to understand that a lot of our employees love working with non-profit clients, and have undertaken efforts to find more non-profit projects to help maintain strong engagement. Pulse leverages the Salesforce platform alongside Einstein Analytics, Salesforce’s powerful AI product to process data and provide meaningful insights.

“To generate positive outcomes we need to ask the right questions,” says Aaron. “How can AI make human lives easier, but also higher quality? Can we actually improve quality of life by creating careers that leave people feeling more fulfilled? Can that actually become an advantage for the company?”

Join the Conversation

On June 21, we’ll be hosting our annual conference in Vancouver, TractionForce 2018. The discussion will dig into some of the most relevant themes in today’s business world. By asking the right questions, we’ll be driving more meaningful conversations and we want to hear your thoughts about topics like AI and the empowered employee. Register here for free and join in the conversation.

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