Data Analytics could reduce strike threats.

The recent strike and threat of strikes left the whole country in a mess. First, taps ran dry, followed by disrupted airport movements, and the nation waited with bated breath for the hammer to fall with an even larger strike across the public service


For starters, disagreements are a part of life, as are protests and strikes; we are not against employees taking action. We are a nation built on resistance, protests, and demanding what we deserve. We are also a nation searching for solutions, and we can consider using data analytics to maximize employee satisfaction and reduce the likelihood of strikes.


We use the word solutions because data analytics enables problem-solving; it requires people to take action to see the benefits. Consider Amazon, where strikes and protests have become an annual occurrence at one of the most technologically advanced companies that prides itself on being customer-obsessed and innovative. Amazon workers have reported inhospitable working conditions, unrealistic targets, lack of benefits, compensation not tied to changing economic conditions, and even automation affecting job security.


Is it possible Amazon was not fully aware of how bad the situation was or considered the strikes an acceptable downside versus external customer demands, or they thought they had enough leverage over their employees? Whatever the case, public services don’t have the same luxury as a US$1.57 trillion e-commerce company operating in over 12 countries.


Enter data analytics, which can provide the foresight to avoid strikes. Before we get into how to remember this statement, “Employees are customers too.” Let’s start with the purpose; we want to improve employee satisfaction and reduce strike risk. To do so, we need to understand our employees.


The first stage is descriptive analysis; we want to describe the current state of the business, including gathering data on operations, business targets, and of course, feedback from employees. Data collection can use multiple tools, such as polls, interviews, surveys, and newer approaches that utilize chatbots, conversational artificial intelligence (AI) and even games. We’ve had tremendous success with games to fuel employee insights. We recommend using an independent resource periodically to collect employee feedback; employees are usually concerned with human resources or senior leaders targeting them to voice less-than-popular opinions.


When collecting information, you need to ensure your employees can be open and honest or your recommendations won’t be helpful. Also, remember that any employee feedback study aims to find areas of improvement, not to report good-looking metrics to the board of directors. I wonder what the employee satisfaction scores looked like leading up to the recent strikes.


Once you have valuable data, the next step, called diagnostic analysis, focuses on the “why”, understanding your employees and their relationships with the business. The diagnostic analysis uses many approaches to uncover cause and effect relationships, such as statistical analysis. A diagnostic, for instance, can provide evidence that your work-from-home policy increased employee productivity by 5 per cent and reduced resignations by 10 per cent. This looks great so far, but how will it affect productivity in the long term and the chances of a strike?


Enter the third stage, predictive analysis. This stage uses predictive tools, such as machine learning models that learn from data and the insights gained in the diagnostic phase to forecast the future. We ask questions like: How will a strike affect our customers? If we meet the demands of employees, how will this affect our future financial strength? What are the early warning signals of a strike? What is the daily cost of a strike?


In the final stage, prescriptive analysis brings together what you know, what you understand, what could happen, and the company’s objectives to provide practical recommendations and a road map based on data analytics. For example: Can we meet the demands of employees while ensuring our external customers receive the best customer service and our financial obligations are met? The prescriptive analysis will tell us which demands can be met and how they can be done effectively.


We are reminded that employees are customers, too, and data analytics can help employers better communicate and understand them. It’s not about restricting employee strikes. It’s about finding a solution to employee grievances before they escalate to a strike.


Stay innovative, Jamaica!

Source: Jamaica Observer:

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