Written by Dr. Madhav Durbha. This guest post first appeared on Kinaxis’ industry blog, The 21st Century Supply Chain.

I recently came across a Bloomberg article citing how certain functions of the white-collar workforce at Amazon is getting replaced by automation. Employees drawing six-figure salaries to negotiate multi-million dollar deals with major brands on behalf of Amazon are being replaced by software that predicts what shoppers want, when they want, and how much to charge for it.

Typically, vendor negotiation is a high-touch activity with lots give and take. However, it is also a function that results in predictable outcomes. At the end of the negotiation, the buyer places an order for a certain volume of a group of products at a negotiated discount with agreed upon delivery dates and payment terms.

The results are specific and measurable. Order too much and the buying entity ends up with excess inventory that needs to be marked down or written off as obsolete. Order too little and stockouts become an issue causing loss of revenue. As the aforementioned Bloomberg article indicates, in many instances, algorithms performed significantly better than humans in terms of the quality of orders.

Any such elimination of jobs comes with collateral damage. It is not far-fetched to imagine that the channel teams assigned to Amazon from the vendor organizations have to feel the impact. I feel sorry for the human at the other end of the transaction trying to negotiate with an algorithm!

Algorithms drive objective, data-driven decisions given a defined set of goals and rules that go with meeting those goals, as opposed to humans who have to deal with emotional factors. Going back to the buying example, it is not uncommon for the retail team buyers to wait until the end of the quarter and order in bulk from vendors just so they get steep discounts and pocket big commissions.

Vendors partake in the game as they have to meet their quarterly volume targets. This causes end-of-the-quarter hockey stick patterns, which led the CEO of a company that produces diapers to ask why babies were peeing more towards the end of the quarter!

Algorithms do not need to be concerned about their pocketbooks or others’ perceptions of them. Nor must algorithms sit through endless meetings to arrive at decisions that may be dead on arrival. Under the right conditions, they can be superefficient.

To understand the feasibility and the impact of potential jobs loss through the automated machine learning, we need to look no further than what industrial robots did to production line workers. In the not so distant past, lower cost offshoring was a major force in eliminating several white collar jobs in Western societies. The work that got outsourced was, for the most part, towards the low to mid end of the skills spectrum.

Algorithms level the playing field though. They do not discriminate based on geographic location, age, gender, race, or paygrade. To understand how far automation of cognitive tasks have come and what the future holds, I encourage you to watch this demonstration of the Google Duplex AI assistant.

So, does automation spell the death of white collar jobs? Not so fast!

I like to refer to a recent McKinsey article, which in my view, shares a very pragmatic outlook. The article states – “While automation will eliminate very few occupations entirely in the next decade, it will affect portions of almost all jobs to a greater or lesser degree, depending on the type of work they entail.”

I have seen this first hand over the last several years. If you take the role of a demand planner, it has significantly evolved. A lot of the statistical forecasting aspects of demand planning is now fairly automated. Demand planners now have the opportunity to collaborate with the commercial teams and supply planners to ensure promotional forecasts, product phase-in and phase-outs, competitive actions and other causal factors are being adequately represented. This is what makes demand happen, as opposed to simply generating a forecast and throwing it over the fence to supply planners.

More automation is coming their way, which means the role of a demand planner will evolve further. Some of the progressive organizations I work with are looking to bring in further automation  by collapsing the roles of demand and supply planning roles into the role of a “Network Planner.”

This however, calls for significant upskilling.

In a recent blog post, Dr. Jan Fransoo wrote about how a supply chain planning role can be thought of as consisting of two components – informational and interpersonal. An informational role is where planners spend time collecting, verifying, and disseminating information. An interpersonal role is where planners collaborate with others inside and outside of their organization to solve problems and drive decisions.

The blog suggests that several aspects of the informational role offers opportunity for automation. Now, as aspects of informational roles get automated, individuals will need to migrate towards higher levels of thinking and decision-making. Individual motivation will take on a bigger role and significance. It is not an easy transition for all. Some are bound to be impacted by the change needed.

So how do we prepare for a future where parts of white collar jobs get automated?

We can start by accepting that change is the new norm and that we are living in the age of accelerations where the rate of change outstrips any that we experienced to date. We need to embrace automation brought through robotics and intelligent algorithms rather than fight it. Mid-career professionals will need to look for opportunities to expand beyond the core of their job functions and gain broader understanding of the adjacent functions they touch. They can take advantage of various digital learning opportunities such as those offered through MOOCs (Massively Open Online Courses) such as Coursera.

College students in STEM (Science, Technology, Engineering, and Math) tracks should go for some electives in the liberal arts curriculum and even consider doing a double major or a minor in liberal arts when pursuing a major in a technical field, to develop lateral thinking. (Fareed Zakaria makes a very compelling case for the same in his recent book In Defense of a Liberal Education.)

As one of my esteemed colleagues often says, “Automation does not replace the human in the process. It replaces the robot in the human.” So true! Automation takes the drudgery out of our lives so we can be at our creative best.

As I conclude, I will refer to the Bloomberg article cited at the start of this post. Some of the Amazon employees who moved on in the face of the algorithms started their own consulting firms to help brand owners get prominent placement of their products on Amazon.

The takeaway? As parts of our jobs get automated, new opportunities we may not yet be aware of will open as long as we are prepared!