Why our benefits products need to be like the Sainsbury supermarket

Introduction

 I was undertaking my weekly grocery shop in my local Sainsbury supermarket in Brentwood. It struck me that I have always shopped in this place. Why, and what lessons could be learnt that applies to reward offerings? The store gives me good value, consistency and familiarity.

 

Too often employee benefits are seen as an afterthought, an “add-on” to our pay strategy.  We can do much better than that. Employee benefits are an important signpost of both our employee proposition and organisational culture.  

 

Strong branding, good value, consistency

Sainsbury prides itself on its strong branding, good value and consistency. This is exactly what our benefit portfolio should be offering.  Our benefit products should reflect our organisational culture and values. Employee benefits provide a signpost to both employees and external stakeholders of organisational values. 

 

Good value is important. By which I mean the benefit is valued by the employee and drives business value creation by supporting and sustaining value added employee behaviours.  Consistency is also important. Employees should know what they are getting and benefit costs should be stable unless a revision is taking place. Consistency should also extend to culture. Giving a consistent and congruent benefits message supports and sustains our cultural memes

 

Product placement – the irritation factor

If you do your shopping like me, you are on autopilot; you know what you want and where everything is. However, every so often a ball comes from left field. The supermarket has moved my favourite jam. Panic.  I have to look around to see where it has been placed.  More often than not I see something I have not noticed before. Perhaps I will try a new jam? This again is like our benefit offering. On occasion we should move things around, shake them up a bit.  Just to get our employees thinking a little differently. 

 

Big data is watching you

I use a loyalty card at the supermarket. It is not the most streamlined of user processes.  However, it does mean that Sainsbury knows what I buy and when.  It can offer me money off coupons on things I normally buy and even tempt me with offers of things which I have not tried.  It knows what brand of aspirin I take, the stages of my children growing up and even how often I entertain It does not, in my view, make full use of this data; but it will.  These are valuable approaches we can use to enhance the personalisation of our benefit offering.  We can use the HR data to offer changes in risk benefit levels or pension and financial advice. All this is available and value added. It moves employee benefits from something staid to a dynamic, interesting, value added process supporting business success.

 

Visualisation and info graphics

I do not know, but if I was a betting man, I would place a wager that Sainsbury marketers and merchandisers use visualisation and info graphics to better understand the very large amount of data they hold. I can see in my imagination maps of the UK stores, showing geographic variations in value added products, perhaps with an Acorn (consumer classification) overlay. 

 

This is exactly what we should be doing with our employee benefits. Collect the data. Turn it in to meaningful visualisations.  Use these both as analytical tools but also to inspire creativity and innovation.  After all, why not?

 

Conclusion

There is a great deal to be said to applying the Sainsbury or Wal-Mart approach to our benefit products, services, and communication. The supermarkets make a great deal of money out of offering their customers what they want when they want it, at the optimum price. No doubt we can apply some of these lessons to benefits to build value, add credibility and build business success. 

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Pay reviews; the Compa ratio magic. Strong Analytics V

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Introduction

We are, in most organisations, in pay and bonus round season. I have been involved in running pay and bonus rounds for over fifteen years.  One of the most helpful ratios and presentation tools is the compa ratio.  It is an incredibly powerful analytical tool.  At its most simple the compa ratio is the role is the position salary divided by the market salary.  This gives a ratio.  The magic is the amount of information contained in that number.  A compa ratio of 1 indicates that the position is paid at the market rate.  A ratio of less than one show the position is paid at less than the market rate and by what percentage and a ratio of more than one shows the position is over paid against the market and by what percentage.

By building graphs and visualisations of the compa ratios you have a powerful tool to assist management in making decisions on where to spend the limited salary increase resource.  Compa ratios can also be derived from total cash or even total compensation figures; although please see the methodological warning below.

What is it?

Most of us have salary data information from salary surveys.  We use this data to see how various positions sit in our labour market.   If I work in an insurance company I may have the excellent Mercer survey on insurance pay; if I work in banking I may very well use the methodologically sound McLagan survey.  Provided the jobs or roles have been correctly matched we will have a mass of market data on most of the roles in our organisation.  We will also have the average salaries for the same roles in our own organisation.

Here are some examples of comp ratio calculation:

Position salary Market salary Comp ratio
100,000 100,000 1 (Salary at the market position)
100,000  90,000 1.1 (Salary 10% above the market)
100,000 110,000 0.9 (Salary 10% below the market)

By using the simple compa ratio we will be able to see how our roles fit to the market.  Here is an example from a data set:

Role Average of Current Base Salary Average of Salary Compa
Actuary

$370,000

1.03

Management   Team

$370,000

1.03

Analytics analyst

$36,000

1.03

Analytics

$36,000

1.03

Analytics Manager

$100,000

1.01

Analytics

$100,000

1.01

Asst Trader

$47,648

0.94

Commodities

$41,603

0.95

EM

$29,347

0.96

OTC

$57,696

0.93

Special   Sits

$44,335

1.02

Treasury

$31,333

0.63

Here we have roles categorised by department with the compa ratio.  We can immediate see that there is an issue with the Assistant Trader role in Treasury.  At 0.63 we are clearly paying well below the market.  At best this warrants further investigation; at worse we have an immediate problem that should be prioritised in the pay increase distribution.   The concept becomes more powerful when we convert the data in to a graph

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In this example I have produced a graph showing both compa ratio and the attrition rate.  There is a strong negative correlation between compa ratio and attrition rate.

Getting clever

Using compa ratios it is possible to compare departments against one another as well as roles within a department.

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This shows the compa ratio by department; again illustrating where our pay round fire power should be concentrated.

The analysis can be extended to looking at sex discrimination, for example.  In this graph we look at the differences between males and females by compa ratio.

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This chart again gives an indication of areas that will require to be considered when carrying out the pay review.

Making connections

Another very useful application of compa ratios is to compare department compa ratios against a range of business analytics.  So, in the table below I have compared compa ratio with return on risk capital.  The concept is to focus our pay increases on to those areas that give the best return for the business.

Department Average of Salary Compa Average of RORC
Political Risk

0.93

32.00%

M&A Advise

1.00

28.00%

Treasury

0.89

18.00%

EM Debt

0.99

14.00%

Special Sits

1.00

14.00%

Derivatives

0.97

12.20%

Swaps

0.95

8.20%

OTC

0.95

7.40%

FX

0.95

7.23%

EM

0.96

5.50%

Vanilla

0.94

3.50%

Grand Total

0.95

11.60%

This approach shows a low correlation between market position and return on capital of 32%.  Depending on our reward strategy we may wish to focus our pay budget on, for example, Political Risk which has the top return on capital but has a compa ratio below one, showing we are paying, on average, below the rate for the market.

Thinking bigger

A similar approach can be taken when using a compa ratio for “total cash” – that is salary plus annual cash bonus.

A word of warning

I will talk of some of the methodological issues later in the article; but of particular note is that great care must be taken when looking at total cash market survey results.  Survey organisations use different methodologies so be sure you are comparing like with like in terms of cash bonus definition and the timing of the payment of the bonus.

Combining data

One of the most powerful ways to use total cash compa is to compare base salary compa, total cash compa and, for example performance ranking or even better, a business KPI to ensure alignment of bonus payments with outcomes.

A common reward strategy is to place salary at the median of the market place but to pay bonuses at the upper quartile, or better, for upper quartile performance.

He is an example of a table of salary compa ratio, total cash ratio and return of risk capital.

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This is a very powerful analytic graphic.  It shows that there is a major mismatch between the areas achieving the best return on risk capital and the market position for both salary and total cash.  It further shows that two areas with very similar RoRC have different compa ratios for both salary and total cash.

We can carry on with this type of analysis with almost any business metric and any mixture of KPI’s and compa ratios.  It is a really powerful way to think about pay and bonus analysis.

Methodological warning

A major consideration when thinking about this type of analysis is that salary survey data relates to positions, not individuals.  Further, accurate job matching is essential to ensure a good “fit” to the data.  Salary surveys are best viewed as not absolute numbers but as indicating relativities in the marketplace.  It is more important to look at the relative position of a role than the absolute salary level.  This is because roles are different between organisations as are the people who fill them.

To use the compa ratio approach well requires a good understanding of the statistical methodology underlying the raw numbers, it advantages and its limitations.  We need to understand both the size of the data population and its stability.  Even quite large populations used for data can cause issues if that population changes year on year.  This applies both to the organisations taking part in the survey as well as the roles and the individuals within the roles.    Survey data is averages of samples; good statistical approaches can ensure that the samples closely resemble the total population; but in many cases there are no more or less than a sub-set.

This applies still further when looking at total cash survey data.  The definition of total cash and the age of the data are essential consideration when manipulating the analytical outputs.

Conclusion

When we are analysing data in preparation for the pay round the compa ratio is a very powerful analytical tool.  Used effectively it can give a great deal of data in a simplified format that is amenable to graphs, diagrams and info graphics.

Used in conjunction with business data it can create meaningful business insights that will shape and direct the nature of the pay and bonus round in your organisation.

If you would like to understand more about data analytics and the pay round please contact me at idavidson@rewardresources.net

Pay round visualisations – Strong analytics III

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Introduction

An important part of any pay review is reviewing pay.  That is looking at pay modelling, outputs and outcomes.  My experience says that the 80/20 rule applies.  80% of the pay round outcomes will be straightforward.  What will be of interest is the 20% of the population that comprises of exceptions and outliers.  So a good analysis will be layered to provide details on the total spend by department or area and the identification of outliers and exceptions.

The most effective way to provide this data is to do so using graphical data and info graphics.  Human beings assimilated graphical data far faster, in most cases, than vast spread sheets of data or even summary data in tabular form.  We like to look for patterns and at pictures when going through the sense making process.

The other very important piece of the presentational jigsaw is to show, wherever possible, the link to business metrics and key process indicators. (KPI’s).  It is very useful to show correlations between our reward outcomes and business metrics.  We must use the data to show our “bang for the buck”.  That we are spending shareholder money to best advantage.  This approach should be supported by reference back of the pay outcomes to our reward strategy.  So if our strategy is to pay our top performers at the upper quartile of our pay market we must show that correlation in our presentations.

Getting pay visualisation right saves time, effort and increases the credibility of the reward team.  It aligns the reward analysis with that of the organisation and its management.  Having a cohesive pay narrative, linked to business outcomes with make the “sell” of the pay round easier and faster.  Anticipating the questions of our stakeholders is both simple and powerful.

Exceptions and outliers

If the pay round is well structured management will have a focus on the exceptions and the outliers.  Identify the top and bottom ten per cent of your pay proposals.  Clearly identify those staff who are being rewarded outside the policy or in a different way to their peer group.  DO NOT provide pages of spread sheets or tabular summary data. (Unless specifically asked for by a stakeholder).  For most managers pages of data are difficult and time consuming to read and difficult to interpret.

This graph shows a correlation between revenue ranking and market position.  It is immediately oblivious that there is an outlier.  The reason for that person’s position on the graph can be explained and a recommendation made as to how to correct the anomaly and increase the correlation between revenue ranking and market position.  (The underlying assumption is that this is part of the pay strategy).
Revenue
 

Develop the pay narrative

As reward professionals, working closely with our HR business partner colleagues, we should have developed a coherent pay narrative.  A story of what our pay round is trying to achieve and what it has actually achieved.  The reason for this is that it makes explanation, presentations and data analysis much easier if we have started off with a basic, clearly expressed set of principles and assumptions.  This may include foreign exchange rate decisions, key metrics including the budgets and a clean set of data as a starting point.  Time spent cleaning pay data is never wasted and can save a vast amount of time and trouble later in the process.  Data is never perfect.  I have frequently come across situations where the headcount I was using for the pay review and the information in the Finance department was different.  Agree and reconcile the approaches and numbers before the pay round starts.

There is never enough time or resources to process a pay round perfectly.  By undertaking the data cleansing, agreeing the pay narrative and assumptions and any reconciliations in advance (and appreciating that is not always possible) will save time and lead to a better pay review process.

A picture is worth a thousand words, or ten spread sheets

Producing high quality, clear info graphics and visualisations of reward data is a very efficient use of resources.  Returning to the 80/20 rule it allows management to focus on the 20% of the pay review that is important or of interest to our stakeholders. Graphics such as the one below can be used to answer questions before they are even asked.  Using this approach highlights our exceptions and the extremes of our pay distribution.

The supporting data is of course available behind the graphics.  But, returning to the theme of a good pay narrative, we can illustrate and support both what we are hoping to achieve and what we have actually achieved.  A good graphic is a “smack in the face with the obvious”. A crude but accurate comment on what a good graphic should achieve.

Business metrics and KPI’s

It is no longer enough just to present raw pay data.  We have to put the information in to the business context.  We must illustrate the connections and correlations between our limited pay and bonus budget and business outcomes.  Reward the performers and the revenue generators.  Pay outcomes can be used to give a clear message as to what behaviours and activities will be reward and those which will not.   Many organisations, even those in financial services, are looking carefully at the “how” something is achieved as well as the “what”.  Balanced scorecard approaches are very common; it is still possible to focus on the financial outcomes by giving it a high scorecard weighting; but we can nuance the approach by giving smaller weightings to cultural, behaviour and approach.  A well-constructed balanced score card will be measurable and give another basis for our graphics to show appropriate correlations.
Blog pic 3

In an earlier post (https://iandavidson.me/2013/08/23/pay-round-processes-a-big-data-approach-including-the-add-on-benefits-to-recruitment-training-and-development-and-succession-planning/) I showed how it is possible to run a pay round based almost entirely on those factors that lead to business success.  It is not easy and arguably it removes “discretion” from managers.  But, it is the use of that very discretion that often leads to upset and even legal challenge.  A robust process backed by robust data is the way forward.

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Conclusion

The pay round in the vast majority of organisations is resource and time constrained.  It can be made easier on all stakeholders by presenting a solid reward narrative illustrated and supported by appropriate and timely visualisations.  This allows the focus of the reviewing stakeholders, be they the Remuneration Committee, Executive management or line management, to be on the 20% of the population that requires attention rather than the 80% that does not.

A strong story, answering questions before they are asked and linkage with business metrics will be both appreciated as part of the alignment of HR and business strategy and as an efficient way to manage a pay round.  Providing good graphics saves time and increases focus when resources are, like high pay increases, very rare.

London Callling

 

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Introduction

I was listening to a radio program about the broadcasts to the French resistance during the  Second World War.  Coded messages were sent by the BBC to give instructions to the  resistance.  These included “The blackbirds have arrived.  Aunt Marie wants to visit.  It is going to rain in Paris”.  To those who understood the code it was perfectly clear; but if you did not understand the code the phrases were meaningless.

 

This is very similar to the language we use in executive reward.  We talk about TSR, LTIP’s and ESOPs.  These make perfect sense to those “in the know” but means very little to those not in the profession.  This is a problem.  It is important that there is a wider understanding of how reward metrics are measured and achieved.   Otherwise executive reward will continue to be a black box.  Given the scrutiny by the media and politicians it is important that we make reward as transparent as possible.    

 

Vocabulary  of reward

The language we use in reward is a mixture of finance,, economics and statistics.  To those in the know it makes perfect sense.  But, we are in danger of losing the understanding of an important group of our stakeholders.  Just as the Nazis during the Second World War, did not understand the messages and made incorrect tactical decisions based on their lack of knowledge, so the media and the public make incorrect assumptions  about the reasons and justification for executive reward.

 

The exclusive vocabulary used to serve a purpose.  It stood as a form of professional validation.  If you understood the language you understood the culture – the way we do things in reward.  Due to increased scrutiny of reward by the media and the growth of social media that makes executive pay discussions more easily accessed such exclusivity is no longer appropriate. 

 

Another lesson from the BBC

The BBC used to have its presenters talk in “Received Pronunciation” .  This was a very correct form of English pronunciation.  While it was not spoken by the majority of its listeners, it was clearly understood by most.  Sadly the BBC now encourages presenters with regional accents to promote inclusiveness; some of the presenters cannot be understood by the elderly, those who do not have English as a first language and upsets those who like English to be spoken properly.

 

In reward we have to develop our own “Received Pronunciation”.  That is a way to communicate the complexities of reward in a way that is clear but also precise.  That allows all our stakeholders to understand (perhaps with a little intellectual effort) the reasons, metrics and outcomes of our executive reward programs.  A better understanding is likely to lead to a higher level of acceptability

 

Conclusion

In reward and benefits we are involved in a struggle to get our sometimes complex messages across to an audience used to “soundbite” explanations.  We must develop the “Received Pronunciation” of our reward vocabulary to better persuade and convince our multitude of stakeholders of the value of our efforts in the complex and ever changing field.  

Pay round processes – a “big data” approach. Including the add-on benefits to recruitment, training and development and succession planning

Introduction

The key to using data intelligently in HR is to start with the business numbers.  This article is about how to structure a pay round driven by business results.  It focusses on data rather than the normal subjective judgements and gaming that goes on in the vast majority of companies at pay increase time.  The objective is to reward what matters to the business.

This is a long post; but it is not going to give the full detail of the approach.  This will differ in each organisation.  It is a new approach in thinking about the pay round process and the article gives the broad concepts and approaches to the subject rather than a detailed “Dummies guide”.  (I can provide one of these for a reasonable fee).

Effective and efficient

This approach is based on good use of data and behavioural psychology.  It generates rewards for behaviour that is important to the business.  By doing this it sends out a clear message both on culture and on what behaviours are rewarded in the workplace.  This creates the “virtuous circle” of reinforcing profitable behaviour leading ultimately to high performing teams.

You should use this approach.  It gives hard statistical evidence as to why pay increases were, or were not given.  It gives a better return on your pay increase investment.  You are rewarding behaviour that benefits the organisation; not a managerial whim or some perception of employee merit based on last week’s conversation.

In the beginning

Like all good science, start with a test group.  Select a discrete group of employees where business and HR data is available.

Key business success metrics

The key business success metrics for this group need to be clearly defined.  As an example, if looking at sales staff then consider sales revenue, the conversion rate of sales calls to sales, repeat sales and so on.  It is advisable to weight these business success metrics from the most important to the least important; always focussing on the bottom line impact of these factors.

Rank the employees

The next step is to rank the employees against the business metrics.  This must be undertaken strictly against the business metrics.  It is difficult, but is an essential part of the process.  It may well be that your “best” employees are not those who score highest on the metrics.  Stick to your original business metrics.  Do not change them because the employees in the list do not fit your perception of “good”.

What makes these employees “good”?

This is the most difficult part of the process, but the most important.  This is where the power of big data starts to prove itself.  Now take the HR data on each of the top employees to see what common factors make these employees perform better against the business metrics than others.  This could include:

  • Time in role
  • Education level
  • Personality profile
  • Supervisor
  • Training courses
  • Previous roles
  • Previous employer(s)
  • Outside interests
  • Social network size
  • Email activity – internal and external
  • Sales calls length and frequency
  • Time and attendance data
  • Daily newspaper and magazine reading
  • Social profiling (you can use postcodes for this)

As long as you have the data and you should have the data, you can include it as a factor.

You will now need some strong statistical knowledge to undertake a regression analysis to identify the common factors for your high-ranking employees.  I am aware there are a number of statistical techniques that can be used at this stage.  You pay your money and you take your choice.

The outputs from this exercise will depend both on the richness of the data you hold on employees, the type and location of your organisation and your company culture.

It is important to note that this technique is not limited to revenue generating activities.  We can build success factors for HR, cost of hire, attrition, benefit spend, payroll costs and so on.  Or much the same in Compliance, for example.  External audits passed, compliance costs, compliance checks carried out – you can fill in the blanks.

Results part one

What you will have, if the process has been carried out correctly, is a list of individual factors that predict behaviour that support business success.  Some of the factors will appear not to be relevant; and I am aware that correlation does not imply causation.  Some of the factors will be surprising, do not rule them out or ignore them.  GO WHERE THE DATA TAKES YOU.  Human beings are programmed to look for patterns where none exist and make choices based on often faulty heuristics.   The data may not always take you in the right direction – but normally it will.

The ranking

This is the easier part.  You rank the employees by the factors.  This process is already part carried out by the earlier steps.  The exact nature of the ranking will depend on the analysis.  One approach may be to rank the employees by the factors with the highest correlations to business metrics success.

The pay increase allocation process

In an ideal world you would allocate 80% of your budgeted increase to the top 20% of employees.  That is because it is statistically likely that 80% of your revenue comes from this top 20% of employees.

This process largely removes the subjective elements and gaming that goes on around pay allocation in most organisations.  Decisions can be justified and supported by the data.  A clear signal is sent out to employees as to what is being rewarded.

Extra benefits to recruitment, training and development and succession planning

By having identified the factors that are correlated to business success (provided you have chosen the business metrics correctly) you have a powerful dataset to aid recruitment, training and succession planning.

Recruitment

You have a list of factors that predict business success and effective employees.  Using these factors a template can be developed to quickly and factually identify those applicants who are most likely to do well in your organisation.  It may not be the only measure; but it will provide an excellent screening tool.

Training and development

The factors that lead to success have been identified; thus you can train and develop employees based on those success factors.  A provable bigger bang for the training buck.

Succession planning

From the analytical process you will have identified both the success factors and those supervisors who have the most successful teams.  A variant on this exercise can be used to identify what factors make up the most successful supervisors and managers and build your succession plans accordingly.

Power of big data

The above discussion shows how HR data can be used to drive business success.  One of the tenants of big data is to automate the analysis of the data.  With a little work it is easy to automate the data scrapping processes to allow the identified factors to be ranked against employees and allocate the pay increases once the basic rules have been formulated.  Having the data available and categorised allows for very powerful management information reports and data visualizations.

Warnings and alternatives

The above process is, for the majority of organisations, new and perhaps frightening.  It will not work the first or second attempts.  However, the very process of data scraping and analysis will yield a honey store of good things.  The process can be changed and refined to fit the organisation.

This is different HR.

It is data driven and business focused.  Some will argue it takes HR away from its traditional routes; why not?  HR has not yet earned a full place at the board table with its current approach.  Finance, IT and other support functions have a greater claim, because they have the data and facts to support cost activity.

Conclusion

This concept is fairly new for most organisations and will take:

  • A change in mind-set
  • A robust data store of employee and business data
  • A strong understanding of the underlying statistical processes to carry out the appropriate analysis
  • HR working with Finance, IT and data professionals, statisticians and the business to get the clear benefits from the approach.

When this approach is fully working it provides a rich and effective way of spending the salary budget as well as providing a firm “big data” base for HR strong analytics.

Working this way gives credibility to HR and builds up a subjective data bank of HR information with which to support business decision-making.  Implemented appropriately it is a win win for all parties in the annual pay round process as well as for the wider HR community.

Employee benefits – cultural mood-music

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Employee benefits are often overlooked when thinking about organisational culture. Yet they are a powerful framing or reframing mechanism for amplifying the message in our organisation of “the way we do things around here”. Like a good base guitarist they can provide the rhythm underscoring the melody of our set piece riff.

Messages – explicit and implicit
There are a number of signpost continuums that are reflected in our benefit offerings;

  • Traditional to playful (think pensions vs bike to work)
  • Collective to individualistic (Set menu vs flex)
  • Paternalistic to intelligent consumer
  • Slow moving to early adaptor (Notice board vs Twitter)
  • Tea dance to Lo-fi (Think tea trolley to “Sushi made at your desk” (Hey, is that a new benefits concept?))

You get the idea. The what and the how of benefits delivery as well as the communication sets the mood music for how our organisation is perceived by employees and the wider world.

Conclusion
Benefits are not something that should just happen. They are an important rhythm to the music of our organisational culture. Not up there with the lead guitar perhaps; but an essential, if overlooked nuance and shading of the message of who we are and who we want to be.

A time travelled reward strategy; Who?

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Introduction

I was listening to the excellent “Dr Who at the Proms” on the radio.  The music was evocative of different times and alien terrains.   A thought struck me; what would the reward landscape look like in ten years’ time? Two alternative possibilities collided in my mind: a sort of Matrix like choice of different futures, a red pill or a blue pill? These were:

  • A continuation of what had gone before with ever increasing inequality between high and low paid
  • A more equal, transparent approach with some convergence between the levels.

This article will be looking at the outcomes of these two scenarios and the different pressures that may lead to one or the other becoming the new reward reality.

Continuation of the status quo

A troika of forces support the status quo.

  • The self-interest and power of those who benefit from the current system
  • A lack of political will to make changes; perhaps connected to first point.
  • As the economy improves the supply and demand equation will reassert itself.

There is a large amount of vested interest in the status quo.  This is not only from the direct beneficiaries of high pay; but also from those who benefit indirectly.  The barrier between board rooms and politicians together with senior public servants has always been porous.   Politicians and public servants often move in to corporate board rooms following retirement from “public service”.  It may be argued that waiting for those who currently hold the levers of power to reduce their future earnings potential in the private sector is like turkeys voting for Christmas; unlikely to happen.

Although outside the parameters of this article there is some interesting research to be undertaken on the issues of power and ideology as they relate to the economics of reward.

Even when the global economy is in recession it is difficult to attract the right calibre of staff in to executive management positions.  Or, if we look at the highest paying sector (putting aside football players and those in the entertainment industry), in to investment banking.   Getting the right people in role can make a great difference to organisational and financial success. When Stephen Hester was unexpectedly removed as CEO of RBS, its share price fell by about 7%.   At the top levels it is a seller’s market, with, arguably, an increasing international dimension.  There is anecdotal evidence that top mangers’ prefer moving in to private equity where rewards are higher but less transparent.  Likewise the increasing, and in my view, mistaken, prescriptive approach by the USA, EU and regulators on financial services pay, has the potential to lead to a flight of talent to less regulated shores; much the same as we have seen in the past with corporate tax planning.  This means a race to the top for the best talent with organisations worried about falling behind their competitors; the stairway is to heaven for the high paid.

There are considerable forces of inertia to be overcome before we can travel to a more progressive pay landscape.

What will the status quo pay landscape look like?  I used some data from the excellent MM&K survey of executive pay to develop a model.  The current position in the UK FTSE 100 (the UK top 100 companies by capitalisation) is:

  • Average FTSE 100 CEO remuneration:       £4,516,474
  • Average FTSE employee pay:                       £        33,957
  • Ratio of employee to CEO pay                                    133

If we look at the last ten years, the average increase in CEO remuneration has been 5.8% and 3.9% for employees.  I build a Monte Carlo simulation (with a heroic assumption that the increases were normally distributed and appreciating that ten data points is not a good sample) that showed there was a 50% probability that the following would occur;

  • In 2022 average FTSE 100 CEO remuneration:        £7,972,054
  • In 2022 average FRSE employee pay:                       £      49,668
  • 2022 ratio of employee to CED    pay                                       161

So inequality between those at the top of the pay scale and those on the average wage would get progressively worse.  A “Hunger Games” scenario with a large population of lower paid supporting a small population of very high paid.

There is a counter argument to this approach.  As the Institute of Fiscal Studies reports:

“Income inequality in the UK fell sharply in 2010–11. The widely-used Gini coefficient fell from 0.36

to 0.34. This is the largest one-year fall since at least 1962, returning the Gini coefficient to below

its level in 1997–98. Although this reverses the increase in this measure of income inequality that

occurred under the previous Labour government, it still leaves it much higher than before the

substantial increases that occurred during the 1980s”.

Thus, income inequality is a moveable feast with volatility making it difficult to confirm a consistent trend given the constant transformations of the tax and social security structures.

A more equal, transparent approach with some convergence between the levels.

There are a number of important pressures that indicate that this is the more likely outcome; albeit occurring over a long period.  As Jon Terry of PwC, a globally recognised FS reward expert, notes they can be broken down in to three broad areas:

  • External pressures
    • Pressure from shareholders
    • Pressure from the regulators
    • Economics
    • Cultural pressures

External pressures

I had a very interesting conversation with Cliff Weight, another internationally recognised reward expert, from MM&K.  This was on the subject of the balance of power between shareholders and executive management.  It is my view that in the past shareholders were more relaxed about the quantum of pay. This is because they were making a good return on their equity.  That situation has now changed.  Return on equity has, in many sectors, reduced considerably.  At the same time the percentage being spent on executive remuneration has risen.  Shareholders are now taking a much more detailed interest in the balance between what they earn and what the “talent” gets paid as a percentage of revenue.

It is also worth mentioning the role, particularly in the US but increasingly in other countries, of the activities of shareholder advocacy groups such as Institutional Shareholder Services (ISS).  I am not a fan of their somewhat tick box approach; but I fully appreciate that they do an important job in highlighting what may be seen by some, as poor pay practice.  Institutional shareholders are increasingly (although perhaps wrongly) relying on the advice given by these organisations.  The pressure on pay is always downwards.

A similar downward pressure is beginning to be exerted by the regulators; albeit often accompanied by prescriptive, counterintuitive and sometimes downright stupid regulations. There is a good summary of the latest UK regime on remuneration reporting here.  A downward pressure on remuneration by regulators is a clear and present danger to the maintenance of the status quo.  Linked to this are the regulatory requirements, initially in financial services, but likely to move to other industries, to hold sufficient risk based capital to support operations in the event of black swans, unlikely but catastrophic events.   This reduces the risk capital that can be invested in higher risk; higher return activities, so, picking up the issue in the paragraph above, reducing the potential returns to shareholders.

Economics

There are two opposing economic pressures affecting this debate.  Shareholder returns are dropping, as discussed above.  There are structural changes taking place that indicate that we may never see a return to the fifteen per cent plus returns before the financial crisis.  If that is the case there is going to be considerable downward pressure on remuneration in order to ensure a more “equitable” division of return between capital providers and employees.  The counter argument is that if there is a return to high inflation (and that has a high possibility in my view) and good economic growth, there is the likelihood of higher relative returns, while the scramble for labour intensifies and earnings at the top of the ladder explode.

Currently the balance appears to be in favour of the economic constraints on equity return leading to downward pressure.  But, as previous booms and busts have shown little is impossible, even if very improbable.

Cultural pressures

This is the most interesting of the downward pressures on pay.  I discussed this issue extensively with Cliff and Jon.  There is a clear consensus between the three of us that there are strong undercurrents of social pressure to increase transparency and have a more equitable distribution of pay.

These pressures are coming from all levels and in some cases some unexpected directions.  We are currently seeing the senior executives of some large organisations preaching pay restraint and greater responsibility.  Although, as the recent CIPD report on “Rebuilding trust in the City” (of London) shows there is a long way to go and some leaders still work on the basis of do not do what I do, do as I say.  But, this apparent change by the changing leadership of some large organisations is an interesting trend.

It can also be argued that those currently coming in to the system or beginning the climb up the greasy pole of corporate life have a different approach to reward, work and life balance.  Perhaps there is something less of a drive for personal gain and more a realisation of the importance of social contribution; we can but hope.

I am unsure that issues of high pay have yet entered the popular consciousness; a bit like the zombies in “World War Z”; we know they are bad but we are not going to come across one in real life.  Very few people have even indirect experience of high pay either in an absolute or relative sense.  Thus, while there is a broad sense of moral outrage driven by an often misinformed media; there is a limited popular demand for restraint on high pay and even less of an understanding of labour market economics or the complex nature of senior reward.

Having said that, social pressures are leading to what Jon Terry described as a “noticeable shift” in attitude by those both at the top of the tree and those who are working their way up the branches.  It is not yet revolution but is most certainly evolution.

What is clear is that social pressure is building up a head of steam and will have, perhaps, a defining effect on the reward landscape a decade hence.

Conclusion

My travel in to the future of reward is complete.  The evidence supports the scenario that in ten years’ time we will have a more transparent, more equal, reward landscape.  It is also likely to be an extremely regulated environment, particularly for high pay.  The issue is that state intervention starts to look like pay policy and pay policy, as history has shown, seldom works and discourages an open market in reward with frequent unintended consequences.

Executive Directors, consultants, remuneration committees, regulators and last but not least, reward professionals must start to prepare themselves for the changes that are beginning to appear on the horizon of the reward landscape.  It must be acknowledged that the future seldom turns out the way we expect; but there are sufficient broad trends emerging to at least give a probability of a more equal approach on pay.  In some ways this becomes a self-fulfilling prophecy.  If we start to think and prepare for a more transparent and equal pay environment it is more likely to happen.

Acknowledgements

I would like to thank two globally recognised reward experts, Jon Terry of PwC and Cliff Weight of MM&K for sharing their insights on the subject with me.  However, all the views expressed in this article are mine alone.