The Problem with Sales Incentive Management
Background
In my previous article on the problem with HR and People Analytics, I had commented about the sub-optimalities in the design of sales incentive schemes by HR practitioners. In my 6th article of this series, I unpack some key features of sales incentive design to shed light on the poor thinking and poor practice in this domain.
Several years ago, my consulting co-founder (Sally Taher) and I worked on a performance management project involving relationship managers across a national branch network. The brief was simple: is the bank’s performance management and variable sales incentive scheme creating sub-optimal outcomes, and if so, how should it be improved. Of course, if one goes searching for opportunities, one will generally find something. So what would be convincing evidence to suggest that the scheme design was problematic? We found two.
- There was no obvious Pareto effect (i.e. 80/20 rule). We expected 20% of relationship managers to contribute to 80% of target outcomes.
- There was no obvious separation of top and bottom performers. A top performer was someone who significantly exceeded their achievement on almost all of the target outcomes.
Our operating assumption was simple: a well-designed sales incentive programme should allow the “horses to run”. These ‘horses’ were obviously not. We found that the balance scorecard approach that the bank had implemented as part of its sales incentive design was creating unintended conflicting outcomes, forcing the relationship managers to optimise their earnings by making trade-offs. Everyone therefore traded off and walked the ‘middle path’.
I have been involved in the design of sales incentive schemes for most of my approximately 20-year career at Citibank, having been assigned the initial project in Singapore when the bank transitioned from a service to a sales culture in the late 90’s. My learnings have come from multiple trial & error experiences as good research in this area was severely wanting. Even the academic research in the last two decades tend to focus on hard economic modelling which is heavily assumption-based and flawed (in my opinion) when it came to real-life implementations. I experienced first-hand when Citibank forcefully implemented an econometric-based sales incentive scheme across the globe based on the positive outcome from the US pilot that was proposed by an external management consulting firm. I had pointed out then that the existing US sales incentive scheme was so badly designed that any thoughtful and evidence-based methodology would have resulted in a significant lift. The econometric-based model required time-motion data and calculating differential equations. It was over-engineered and complex for the sake of precision. The new scheme took off. It flew for a while. It had some notable hits. And it flatlined. Key lesson: sales people are already suspicious of management and do not believe that they have their (the sales people) economic interest at heart. Any incentive scheme that lacks transparency, any incentive scheme where a sales person is not able to accurately estimate their earnings, is going to fail.
The Flywheel
In my 4th article, I briefly introduced the idea of the metrics continuum:
Input → Activity → Output → Outcome → Impact
I love this simple framework because it can be applied to so many situations. One can think about sales management in very much the same way:
- Input = opportunity
- Activity = customer engagement
- Output = sales counts; sales volume
- Outcome = economic value generated by the sales for the organisation
- Impact = customer share-of-wallet
Building on this approach, I developed a perspective of viewing the design of a sales incentive scheme as a ‘flywheel’ (see diagram below):
Opportunity → Effort → Value Creation → Rewards
Opportunity is defined as the potential for sales which may reside in an assigned customer portfolio or in the broader prospect market. Effort is the time, resource and activities put in by the sales person in moving the opportunity through the sales pipeline (may or may not lead to sales closure). Value Creation is the economic value recognised by the organisation (can be either near-term or longer term). Rewards are the benefits that the sales person receives which would include sales incentives, bonuses, promotions, etc.
Removing friction and increasing alignment of the components in the flywheel is the key to making a sales incentive design work beautifully. To that end, we can begin to shift our perspective to see the following as lubricants to the flywheel:
- Target Setting is about removing friction between Opportunity and Effort.
- Economic Margin removes friction between Effort and Value Creation.
- Payout Rate aligns Value Creation and Rewards.
- Payout Frequency lubricates the loop between Rewards and Opportunity identification / Effort.
Target Setting
There are 2 kinds of target setting in a typical sales incentive design scheme. There is the Payment Target and the Payout Target. The payment target is the threshold at which the incentive payment starts to kick in. The payment target needs to be set at 3 to 5 times the base salary. (If you have monthly sales targets, then you convert your annual base salary into monthly equivalent.) The reason for this simple — a sales person has to earn their keep. A person’s fixed salary is typically one-third to one-fifth of total cost of a full-time headcount, which includes rewards & benefits, premises, IT infrastructure, etc. Based on this defined payment target, you then do the maths to figure out if there is sufficient sales opportunity for the sales person to exceed this target; in the case of a banking relationship manager, it would be driven by the size of their customer portfolio in terms of counts and asset under management (AUM). Payout target and opportunity assignment should be constantly adjusted to allow at least 70% of the sales platform to earn a sales incentive (known as the participation rate) and not more than 90%.
The payout target is the median total compensation (base salary + variable sales incentive) that you expect for your sales person. At this level of total compensation, the achievement of the variable sales incentive must correspond to your overall business sales target if the entire sales platform performed at the median level.
Aligning the payment target and payout target is the fixed-to-variable compensation ratio. The simple rule-of-thumb governing this ratio is the length of the sales cycle — we increase the fixed compensation ratio when product sales cycles are long, and we increase the variable compensation ratio when product sales cycles are short. The other factor driving this ratio is the human element — higher fixed compensation ratio provides higher job security and reduces attrition, but can inevitably provide cover for non-performers. In the consumer banking platform, we typically see a fixed-to-variable compensation ratio of 40:60 that works.
Another key consideration in target setting is not to mix different classes of metrics. There is a strong tendency for organisations to mix activity-based, output-based and outcome-based targets into their sales incentive scheme in the hope of achieving a ‘balanced scorecard’; this is simply bad thinking. This mixing introduces unintended multi-collinearity problems which can lead to either gaming behaviours or cancelling effects. For sales, focus on outcome-based metrics (i.e. business revenue) and not activity-based or output-based metrics in your target setting.
Economic Margin
Everything in your sales incentive scheme design should be expressed as a value of economic margin. Revenue is popular candidate. There is obviously a time component to the revenue calculation, and this is the part that requires some financial expertise and finesse. Products with a recurring revenue stream will need to be adjusted to a fixed time period for equitable comparison with products with non-recurring revenue. If your sales targets include acquiring new customers or providing important service levels, these must also be translated into revenue equivalent. If you can’t make a logical translation, it would imply that the activity isn’t really material to your business strategy. You can also dial-up or dial-down the based revenue computation to emphasise or de-emphasise specific sales focus areas without having to continuously re-cast targets.
I’m a big fan of using a product’s revenue margin as it generally already accounts for sales effort — products that are harder to sell typically attract a higher margin. The exception would be the introduction of new products where the demand-supply curves have yet to even out, and this is where a dial-up or dial-down may have to apply depending on the products’ attractiveness.
Payout Rate
There is an academic school of thought that says that there should be a single payout rate in the sales incentive scheme design; to avoid tier payout rates as they distort the econometric balance. I believe this argument is incomplete. Sales opportunities can be classified as either constrained or unconstrained. If you work with an assigned customer portfolio, like a banking relationship manager, then your sales opportunity is constrained by the size and attributes of that customer portfolio. If you work with prospecting the open market, like a used car salesman, your sales opportunity is technically unconstrained. The logic of a single payout rate applies to the unconstrained situation because the incremental effort of the next sales is fixed. However, in the constrained situation, the next incremental sales becomes harder and harder at some point as you exhaust the potential of portfolio. This is where a tiered payout rate is the correct thing to do to improve the alignment between opportunity and effort. There is of course some maths to do to determine the inflection points of the tiered payout rates that you allow the sales person to make the informed choice to push for more sales in the current period or to delay it to the next period.
Payout Frequency
Another important consideration in a sales incentive scheme design is the frequency of the payout. Here is where I see a lot of bad thinking and bad practices. Here is the simple truth — your payout frequency must synchronise with your sales cycle. If your sales cycle is typically in weeks, like in consumer banking, then you should have a monthly payout. I have seen consumer banks having quarterly or even 6-monthly payout because they wanted to conserve their computational resources. The payout frequency represent the direct feedback loop on a sales person’s effort, and the more it’s aligned, the more it creates momentum for the flywheel. The faster you can close the feedback loop, the more efficiency you will derive.
Another bad thinking and bad practice that is I see is the desire to introduce deferred payment. This idea typically comes from HR. The believe is that if you hold back a portion of the incentive payout (e.g. 20%) and release it sometime later, it would reduce attrition and “smooth out” performance. This believe is not supported by evidence. In fact, the evidence shows that deferred payment reduces the trust quotient between management and the sales platform, and leads to a host of undesirable ‘gaming’ behaviour by the sales platform to overcome this perceived sense of being ‘short-changed’. It doesn’t reduce employee attrition.
Conclusion
Sales incentive scheme designing is a fascinating data-driven domain, and one that Sales & Marketing analysts and HR analysts should sink their teeth into. It is essentially an optimisation problem, and leans heavily on both marketing and behaviour sciences. In my experience, it is vital to keep it simple. Never sacrifice simplicity for the sake of economic accuracy. The ease of interpretation is key to its adoption success by the sales platform.
