Say Goodbye to the Bell-Curve
Wee Kwong G.
Learning & Organisation Development | Talent Management | Recreational Author
The bell-curve.
Some old school HR love it. The rest of us loathe it.
I recall a recent chat with a Director in a vibrant startup when we discussed this common performance management tool in-depth, over four-and-a-half hours.
First conceived by French mathematician Abraham de Moivre in 1733 and later popularised by Carl Friedrich Gauss, a German mathematician, the bell-curve (also known as Gaussian distribution), is a topic most of us learnt during our secondary or high school mathematics syllabus.
The bell-curve’s application into performance management was first introduced by General Electric during the 1980s by then CEO, the late Jack Welch. Some forty years later, it has become one of the most popular HR instruments and tool.
The concept is simple.
Put all your employees into a statistical model, then force rank them into four groups:
The distribution is indisputable, and every other company is doing the same thing.
This performance management approach is simple. It however does not work as intended and creates more problems than help.
The bell distribution system works by forcing a company to only recognise a smaller than actual number of best and good performers. The idea was to create an environment where other employees would be able to look up to and be motivated to better their performance so as to enjoy the rewards.
The fixed system also simplifies budgeting by allowing companies to pre-forecast how much it will spend on bonuses, effectively ensuring expenditure on manpower stays within budget.
The bell curve distribution, however, did not consider some important job and performance attributes.
Firstly, present-day job design involves grouping tasks according to their complexity and functional nature. As such, there is a limit to how much more productively an employee can demonstrate at work. Although technological advancement and adoption may help raise the productivity bar, not all jobs and tasks benefit from technology’s un-uniform innovation.
Secondly, the macro and operating environment for each organisation differs greatly in terms of complexity, volatility and the life of the products or services that are being generated by the organisation. A public service organisation such as a government agency may operate within a stable context. In this instance, revenue comes from allotted government budget each year, the function / products / services provided by the agency remains relatively similar and unchanged across an intermediate term i.e. three to five years, and the manpower needs tend to be stable and non-expanding.
In comparison, a commercial start-up operates in the end of a highly volatile environment, with revenue sources uncertain and unstable. Products and services may have very short lifecycles compared to the government agency’s, and manpower needs frequently change according to how well the startup is adapting and surviving. What commercial entities need are workforce with the reverse composition of performers i.e. at least 60% performers, the best of the best in what they do, to help the startup grow.
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Thirdly, and possibly most important, the bell curve system grossly misread the employee psychology. While new, motivated employees are hired into the organisation, they soon learn that their environment is really a giant cage fight. The force rank system means the company recognises only a small and fixed number of performers is, and not all performers.
The base motivation of an employee is to work for a salary to meet living needs, and not to make more friends at the workplace. As such, the employees will learn to view their colleagues as competitors or worse, rivals. Far from encouraging cooperation and collaboration, competition and toxic behaviours are encouraged over collaboration.
The drag on other HR centre of excellence work is real.
Talent Acquisition (TA): All the hard work identifying and recruiting top industry talents gone because the performance management policy only recognizes 10% to 30% of those hired. The other 70% of your best hires from the industry gets an immediate downgrade overnight to ordinary or worse, poor performing employees in your company right after they join you.
Talent Management (TM): Not the optimum groups of employees may be identified as high potentials or leadership succession candidates. (As a L&OD and talent management professional, I can assure you there are a lot more requirements that are needed to identify them.)
Talent and Leadership Development: When less than ideal groups are identified, the outcome from even the best training and development programmes will be less than ideal.
Employee Relations and Retention (ER): Rather than starting with a favorable base with most employees being neutral to motivated, the engagement team faces a horde of un-engaged or bitter employees who turned after repeated rejections to be recognized as a performer by the bell curve performance management system.
Not forgetting the 70% employees who received that immediate downgrade after joining a company, they remain and still are the best in their field of expertise - and they will leave with little hesitation when another company offers them the same or better opportunity.
Organisation Development (OD): The senior management eventually realises there are fires to fight and tasks the OD team to action. While there are solutions available in our OD toolkits, it is such a waste and pity to be always stuck in the repair mode. OD practitioners know what an engaged, motivation workforce can excel and achieve more collectively. We are however, limited by the circumstances and HR policy decisions beyond us.
Are there alternatives to using the bell curve distribution then?
The answer is yes.
General Electric realised the bell curve caused more harm than good. In 2016, it replaced the annual performance review with a more flexible and continuous feedback system called "PD@GE," which emphasises real-time feedback and development conversations.
There are also other improved performance management frameworks and systems which have evolved from the mistakes and lessons from the past. I shared in depth about one such system which suits the business environment and nature of commercial entities and how it works, with the Operations Director peer in our chat.
In conclusion, the bell curve as a performance management tool has come to the end of its line. Organisations which move with time will gain and enjoy benefits that ‘Bell Curvers’ can only imagine in their vision planning.
If your company is still using the bell-curve for performance management, really, it is time to say goodbye to it.
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That sounds like a valuable conversation! It's interesting how discussions around topics like the bell curve can really shape performance management strategies. What insights did you find most impactful?