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Understanding the Precision of Success

Play out the managerial benefits when the work an individual is doing is building his/her confidence and engagement with the company.
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In a world where precision is the prime indicator of success, it’s easy to think only in terms of tooling or machines. But smart companies understand there is a symbiotic relationship between person and production. In an ideal situation, the relationship between machine and operator should function in “flawless anticipation,” where the brains (the operator) can detect and correct issues with the brawn (machine) early. 

This ideal drives bottom-line results because each minute of downtime in either part of this process is costing energy, effort, efficiency and quality, which all boils down to money. 

The good news is that a statistical tool can help you identify the cooperative human factors that help drive organizational, team and shift achievement. Think about the benefits of understanding the key and measurable differentiators between top and bottom performers in any given role. Play out the managerial benefits when the work an individual is doing is building his/her confidence and engagement with the company. 

In our work, we commonly see two primary people-driven problems that shortchange process and production: 1) Wrong people, wrong spots; and 2) Individuals and teams who are quick to blame, slow to change.

Wrong People, Wrong Spots

Hiring and firing tend to be the most costly decisions a company makes. For most companies, it takes an average of 4-6 weeks to fill a spot once a job has been posted. From there, it can be weeks or months before that person is actually helping to drive revenue. Consider the cost to hire, the costs to train and the costs to wait out the learning curve, and many companies will tell you a new hire costs a minimum of $10,000 in hard numbers. If the person doesn’t jive with the culture, or can’t produce as expected, there are soft costs that affect engagement of fellow employees, supervisors and management. Because of the high costs, the ability to identify and benchmark the precise requirements for success in the job becomes imperative. We have successfully seen results using tools like the Predictive Index Performance Requirement Options to help identify and bring alignment to varying roles that have to be accomplished on the shop floor. We then use this benchmark to evaluate both incumbents and new candidates to find that sweet spot where what needs to be done is being accomplished by someone who can really excel at doing it. 

Quick to Blame, Slow to Change

Also, we aren’t identifying and fixing problems fast enough. In many cases, issues are identified, but as one supervisor says, “Everyone seems to know what’s wrong, but no one can put heads together to actually fix it.” 

It has been statistically proven that people require varying amounts of information to make a decision. Meaning, if all the information is defined as ten points of data, some individuals will be able to make decisions with only one or two points while others will need all ten. So what happens when a situation becomes ambiguous and only 25-30 percent of the information is accessible? Those who require more than available may say there’s a problem, but won’t bring any potential solutions to the table. Additionally, many individuals on the floor are inclined to work in jobs that have a clearly defined plan of “what comes next.” When problems occur, the “next step” often disappears from under them, and they stop to figure out what to do. When solving the problem requires a change in the process, it can cause a period of ineffectiveness while he or she learns the new ways of “what’s next.” Work-driven assessment tools can help identify these individual or group information needs, allowing you to build problem solving processes that help keep the information and machinery outputs flowing. 

By understanding the strengths of your people and equipment, you can help to ensure that everyone and everything is working at optimal levels at any given time. 

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