More Power to HR in 2019
There can be many reasons to feel powerful. HR already has the power to shape rewards and recognitions in the organisation. That is just one source of power. I want to focus on HR drawing power from its expertise at bringing science to the table. It matters most when teams are being formed to execute against projects. A squabbling team is a sure-fire recipe for low morale, project overrun and missed deadlines.
As work starts to rely more on collaboration, HR needs to take the lead in the organisation to build a culture that celebrates cross-functional problem solving. This is actually much tougher than simply creating a team. Building a team is often more about personality factors than just skills. Knowing that the science of personality has an impact on team productivity can help HR create better teams.
“The jobs that follow the ‘faster, higher, stronger’ principle will progressively be taken over by machines. However, jobs that involve dealing with ambiguity, human emotions and changing rules are still best left to humans.”
For instance, a study of 133 factory teams found that higher levels of interpersonal sensitivity, curiosity, and emotional stability resulted in more cohesive teams and increased pro-social behaviour among team members. When the team has people who remain unruffled it improves team effectiveness. Having people who are open to others’ ideas makes a team function more efficiently.
Collaboration is often better with people who are very high on altruism as a motivator. Bringing science into HR is the best way to build credibility.
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Technology will make HR more human
Technology can only perform rule-based jobs that need to be done at scale. Algorithms and programmes can do such jobs better than humans. The jobs that follow the ‘faster, higher, stronger’ principle will progressively be taken over by machines. It is easy to programme robots to do something repetitively and do it blindingly fast. Not only can robots work faster than humans, they are devoid of Monday morning blues! They do not seek vacations nor do they object to working on weekends. They can go through mountains of data in a moment and identify anomalies.
They are already more superior legal assistants than humans, and make better radiologists than humans too. Cars are going driverless. The trend is clear. Any job that is faster for machines to carry out makes it uneconomical to be left to humans. That means, we will have robots replacing humans to carry out many of these jobs.
However, jobs that involve dealing with ambiguity, human emotions and changing rules are still best left to humans. That is what Daniel Pink was referring to in his book A Whole New Mind – Why right brainers will rule the future. Technology may allow more human-ness in the workplace. Leader will required who understand how to motivate people to give their best and feel more engaged and happy at work. The ‘resource’ part of HR will be handled by machines leaving HR to get the best out of the ‘human’.
Application of design thinking to learning
Design thinking principles will identify:
– Why do learners wish to learn? What’s the motivation? What are their apprehensions?
– What do they wish to learn specifically?
– How does the learner learn best?
– What is the best time for learning?
– How do we test for learning?
We can keep formulating questions to see how we can observe the answers to these questions in the behaviour and conversations (without asking the learner directly to answer these questions). Posing questions is often the least effective method. For instance, asking why someone wants to learn something always leads to predictable and cliched responses.
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