During a [month] in which the most hotly debated news topic has been the quality of decision-making by senior federal government officials, my nominee for the worst decision is VA Secretary Eric Shinseki’s parting gesture not only to cancel performance bonuses for senior VA executives, but to ban patient wait time as a measure used in performance evaluations.
The standard realtor commission structure doesn’t motivate the realtor to do his or her best for you. As you read this post and my suggested improvement, think about how this situation relates to the incentive compensation plans in your own enterprise, and why incentive compensation is such a delicate art.
When I bring up talent management as part of a mobile business intelligence strategy, I’m often met with that “deer caught in the headlights” look. I realize that talent management is typically used in the context of human resources, but I also see it playing an important part in the development of a mobile BI strategy. As with any technology project, in mobile BI we need to effectively manage three basic resources: technology (hardware, software, network), processes (business or technical), and people. Of the three, I believe talent is the most important one that we need to get right the first time.
If you have a reward model in your organization, take a few minutes and evaluate how many of items that it has for evaluation actually helps your customer to succeed? How many of them support you in improving business processes so that they will produce better results? I bet not many… What should those reward models be based on then? Here are few ideas on that:
Workforce planning is all about ensuring that an organization always has the right resources with the right skills in the right job at the right moment in the right quantity in the right place at the right price. That’s a lot of “right” to be responsible for…right?! Workforce planning takes many shapes, from the long-term strategic…
Do you have to move your processes to the cloud today? The answer is you don’t. Do it when you are ready and when you see value for your organization. If, and when you’re ready to start your journey into the cloud, you can go about it piece by piece, and as a hybrid, to minimize risk to your core operations and to get buy-in internally.
Perhaps you could begin with applications that bring tremendous value, yet are non-disruptive such as workforce planning and analytics? Your newspaper, music, pictures and videos are moving into the cloud, your bills and banking are moving to the cloud, you telecommute, and your social is moving into the cloud - it’s inevitable that your business applications, including HR will follow.
In the finance and banking industries, organizations have employed for years mathematicians, statisticians, engineers, physicists, and highly-skilled specialists with super-strong analytical skills. They put these skills to work, sifting through volumes of financial, economic, and social data to identify trends, pick out the “needles in the haystack,” and determine the probability of markets going up or down. Their brain power, combined with machine resources, is focused keenly on exploring and acting on new ideas to increase the return on investments, whether through gaining a sub-second advantage in trading or in long-term ventures.
However, the idea of tapping big data in the context of the workforce, in order to gain a competitive edge, is just beginning to sink in with many HR organizations.
When Peter Drucker published his first major book, The End of Economic Man, in 1939, the median compensation for chief executives of the biggest companies in America stood at about $1 million a year (in today’s dollars).
The median pay was still at roughly $1 million, in inflation-adjusted terms, when Drucker’s 1954 landmark, The Practice of Management, came out. Executive compensation was at the same level when his Managing for Resultsappeared in 1964. Ditto when Drucker’s Management: Tasks, Responsibilities, Practices was released in 1973.
Then things exploded.
For those of us who work in compensation, the “peanut butter” approach to pay-for-performance may not be new.
This approach consists of taking merit increase and variable pay budgets and spreading them thinly and evenly across the employee population. However, thin swipe of peanut butter may not make a very filling sandwich for the high performers who have been working through their lunches and missing dinners with their families.
So how do we use limited compensation dollars to recognize the contributions of our top-performers, while also keeping the rest of the employee population happy?
There are many presentations and discussions about how analytics and “Big Data” can improve decision making—a simple Google search on the terms returns close to 8 million results. Organizations find their workforce analytics especially challenging as human resources (HR) departments attempt to grow beyond creating reports for the sake of reporting. When you think about…