I started ForHumanity, partly as a response to thoughts I had about my children who are 8 and 6 today as I write this. If you had asked me 18 months ago, “what skills should my children make sure that they have to be successful when they matriculate from University?”. I would have answered, quite assuredly, “They need to make sure they can code and program,”. Many of you probably still think this is important, but I’m here to tell you, those skills are already being replaced by machines. Machines are beginning to code and reprogram machines far more efficiently than we can. So what should I teach my children? That challenge is what started me down this path…
Data Science has become my poster child today for the challenge. Two years ago, Data Science was the hottest major at Stanford. Here’s a recent article from LinkedIn.
This article argues that data science is dead — ALREADY. You can picture the undergrad thinking, “Now let’s get this straight, I might have signed up for the most relevant, hottest degree at Stanford, dedicated two years of my life already to it and even before I graduate, my degree is useless?”
Now of course it isn’t that simple and Data Science degrees and knowledge will be highly valuable for years to come, but the point shouldn’t be lost. The degree and the subsequent job that might have been expected 4 years hence has already shifted. The knowledge required to be successful with that degree has already changed. Data Science degrees are the poster child for a symptom of this technology age. It is moving so quickly, that we have to change the way we approach learning to remain competitive with the machines. We need to shift to a model of LIFETIME LEARNING
Now the concept of lifetime learning isn’t exactly new. Some will argue that we are always learning and there is truth to that. Still others have pursued the constant student approach, racking up years of study for post graduate degrees and of course the PhD is effectively a mandate on lifetime study in your field. But I am talking about changing a basic paradigm that at least those in the West have followed. LEARN for a while then WORK for awhile and then RETIRE. I won’t tackle the RETIRE concept as that’s a big blog piece onto itself. But let’s focus on that first transition. LEARN then WORK.
Of course there is some learning that goes on at work. There are training programs, there are executive MBAs and occasionally a foresighted leadership team will ask their key staff or high fliers to get a little extra education to stimulate their culture or tackle an industry-wide challenge. But again, I want to approach this differently. It is time for work and learning to merge. For Work to recognize that they will have better employees if they are in a process of LIFETIME LEARNING.
For two decades, executive MBA’s have been this give and take between employee and company. The company values the employee and wants a smarter, more educated employee, but they also recognize that the employee will be more valuable to others with that degree. So deals are struck, you can get this MBA, but mostly on your own time (weekends and days off, mostly). The company will pay for it, but only if you remain with the company for a period of time afterwards. This is a deal done to retain the employee, not necessarily to advance the employee and their ability to function inside the company at their current job. The company had no say in the study. They couldn’t tailor the program to meet their needs as employers, as a function of their industry.
So here is what I suggest. Companies need to either develop an internal skill or engage an external service to create an ongoing learning process for all employees. Not just leadership, not just high fliers, but all employees. It is the only way to keep a company and it’s culture on the cutting edge of technology and all the change that is occurring. These changes effect each department differently. The type of knowledge that each group needs is different, so this isn’t a one size fits all approach. To be most effective, courses and knowledge may need to be tailored. Even the time and method of delivery needs to be tailored. Some course work lends itself to online study, other work is lab based, still other work might involve specific classroom time. The point is that the most effective programs will be those that are tailored to the current needs of the employees or the department. Here’s an example, for decades a lab had used trial and error to test the formulations for their new drugs under trials. This process is labor intensive. Recent developments have brought machine learning, artificial intelligence and automation to the process so that thousands and millions of tests can now be done in the time that it took to do hundreds and thousands previously. However, the output of this automation is statistical. The entire department needs to become more fluent in the language of statistics. Is statistics, the language of these scientist, No. Do they need a Masters in Stats, probably not. Do they need a couple of bachelors level course in stats to simply make their entire department cutting edge, YES. This example can be repeated over and over again, on a department by department basis to identify the latest skills/knowledge and challenges facing each group.
What I advocate is that companies change their culture further. Not only, to allow for constant education for the entire company, but also to build the learning into their current hourly commitments. Allow for an hour or two per week of study during job hours. Encourage it, rather than the world we currently live in where, everyone thinks they need to work 40–60 hrs per week just to survive their existing duties. I argue that your employees will be fresher, creative problem solvers who are working with increased efficiency under this climate. They will feel invested in, by their company and it will relieve some of the growing stress that employees feel about their job security to both machines and to younger generations with more current knowledge. But this sort of culture shift will increase the ability of your teams to collaborate as members will be more fluent in the new languages of technologies.
I believe this culture change, to a constant learning model, embraced by companies, individuals and society at-large will create a more dynamic workforce and will help to smooth the transition for employees and employers as technological unemployment increases its grasp on the future of work. Companies that don’t embrace a constant learning model will find sets of employees who are simply out-dated, and uncompetitive vis a vis machines. Those companies will also find themselves struggling to find good new employees versus their competitors who do embrace the constantly learning model. Finally, companies that fail to embrace this model will also find themselves lagging their competitors where it matters, on the bottom line.
Constant learn is a huge value proposition for both employer and employee and I hope that we can see smart companies move in this direction while intelligent, progressive universities move to meet this new and dynamic demand.