7 Reasons Why Process and Data Science Should Not Be Used to Fire People
/In our last couple of posts, we have touched on some more technical tools such as business process mapping, the empirical rule and the foundations of the business situation in the United States. If we recall our business model, it consists of process, data/systems and people. This post will focus on the people side of things.
Automation and Efficiency Does Not Mean Forgetting People
As the world of machine learning and artificial intelligence grows, it is easy to forget that many times there are people that are affected by algorithms and automation. In the movie Charlie and the Chocolate Factory, I remember Mr. Bucket is laid off from his job of putting caps on toothpaste tubes at the local factory as he is replaced by a machine that is much faster, cheaper and more consistent. Mr. Bucket later gets a better paying job with the factory as a mechanic fixing the very machines that replaced him.
So seems the story with many businesses. They look at automation, efficiency and data/systems as a way to reduce the amount of people they have to pay. Machines can only do so much to replace the ingenuity of people and it will be a long time before a machine can replicate a human mind. If you are not sure about this, then open your Netflix account and put something on you would never watch. Next time you open Netflix, the recommendation engine will provide plenty of recommendations for something you watched a single time. That is because the algorithm is not making an intelligent decision about you, rather it is comparing you to a profile.
Businesses need to remember that at the center of their operations are people. They should be held accountable to ensure they are treating their employees properly. As an efficiency expert / data scientist and having led many efficiency projects, I have seen businesses time and again create the “chop shop” environment and try to use these efforts to lay people off. However, this is the wrong approach, here is why.
Reason Why You Should Not Fire People Using Process and Data
1. Change is Scary Enough
First, people are naturally scared to death of change. That is because they are afraid a company will fire them for becoming more efficient. Any time a process is optimized or improved, it is done with an expectation to help drive change in the way people operate as well. If we make change scary by dangling the unemployment carrot in front of their faces, it is less willing to be accepted or potentially sabotaged.
2. Employees Will Lose Trust In the Organization and Management
When using process or data to terminate part of the workforce, it is not the people that are let go that the organization needs to worry about, it is the people left after the termination. Not providing a workforce with job security is not a good motivator. This could lead to the workforce losing faith in their management to fight for them and help them succeed.
3. Labor Costs Are Not Always the Problem
With most efficiency projects, the savings are not made by reducing headcount. Usually what is gained is the ability to handle increased revenue versus reducing effort to maintain the current revenue. The difference in those statements is one is long term focused while the latter is short term profit focused. An increase in productivity and labor reduction should not lead to right sizing the labor force, but instead challenging the sales force to earn more revenue!
4. The Risk of Termination Hinders Innovation and Creativity
One way to keep a company stagnant is to terminate people. When people are de-motivated, this leads to them being less creative or proposing fewer improvements because they do not see the value. Usually everyone in the company has a lot of ideas about how to make improvements, but they need to be motivated to voice these ideas.
5. Termination Does Not Make Transformation Everyone’s Job
The last of Deming’s 14 points is to make transformation everyone’s job. When using transformation as a personnel reducer, this separates management from employees. The workforce will not feel like it is their job to transform, rather something management is forcing.
6. The Threat of Termination Hinders Productivity
With the workforce worried about their jobs because of some “efficiency expert”, this causes a lack of focus on the job at hand. It leads to more worry, gossiping and disdain. None of which drives the point of productivity. As a manager or business owner, this costs you more money.
7. The Threat of Termination Leads to Unethical Behavior
When people find out terminations were caused by a data analysis, it makes them want to find out what data was used and circumvent it so the situation is not repeated. Essentially, brewing a fear of termination in an organization leads people to find creative ways to justify their jobs. This could lead to such extreme examples such as manipulating data, purposely working slower than normal or not following an efficient process.
Integrating People and Business Transformation
The question then becomes what are ways to transform a business, make it more efficient, implement automation and still respect people?
1. Be fully transparent and provide security
When there is a need for improvement, the improvement should be communicated with the entire workforce, especially those affected. Being open and honest about change will help the workforce understand why teams or managers may be poking around and asking questions. At the communication, everyone’s job should be guaranteed as long as they support the transformation. The message needs to be the initiative is not meant to eliminate jobs, but to improve company performance. A plant manager I used to work with once told me that he never had to fire anyone when implementing change initiatives. He mentioned that natural attrition helps to keep the workforce in balance. This is a view that makes employees feel safe when they do not have to worry about engineering out their own job.
2. Train employees in process and data science techniques
This one is easy, people fear what they do not understand. If an efficiency expert walks in and starts asking questions or forcing change on a workforce, the workforce will resist if they do not understand what is going on. However, investing in the workforce and training them in process and data science techniques will not only improve acceptance of new things, but can also create a more flexible workforce that can be moved into various positions to help support growth. Companies in the US are notorious for not training employees or investing in employee growth.
3. Get all employees involved in a process or data project
When trying to transform your business through automation, process science and data science, you should get everyone involved in the transformation effort. People do not like things forced on them. If they have a hand in creation, they have more of a motivation to see initiatives succeed and more of a chance of meeting the company’s goals.
4. Make idea generation part of everyone’s review
One quick way to get people to voice their opinions is to tie their ideas for improvement to their financial compensation. Start off with requiring two idea submissions a year to improve operations. Then gradually increase this year over year. This will become second nature to your employees who want their problems solved or have good ideas and have an avenue to voice them. Management is also accountable for follow up on the ideas and why they can or cannot be implemented.
5. Use people for their minds, not their hands.
One key aspect of implementing automation is to first try to automate the tasks that are non-value added and add cost. Many companies focus on automating their value add tasks, but these are the tasks that make the company money. First, focus on the tasks that cost you money! Usually these can be eliminated via low cost automation. Respect people by giving them work that matters. Someone screwing caps on a toothpaste tube is not a good use of a human mind.
Conclusion
Corporate layoffs will never fully stop. It is the nature of business and life sometimes. Industries will rise and fall and companies will find themselves letting people go because they failed to stay relevant. This is all due to management not using proper techniques to innovate their company and the workforce suffers. While this may be the case, companies can control reducing staff in times of stability. Using positive things such as process science and data science to cut heads is an approach that costs money in the long run with the loss of potential and revenue. It does not demonstrate the mindset of a growing company.
Our next post will focus on applying the scientific method to business. Stay tuned!
