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June 23, 2015

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Banking pay, Executive Reward, HR, Pay Regulation, Reward, Reward Strategy

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Time, value and a bonus

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Introduction

I was at a City lunch in a conversation with a senior executive of an American bank and her partner, a gifted financial analyst.  We discussed the impact of bonus accrual accounting standards on balance sheets.  Then she made a startling statement.  “The accruals cost us millions, but the executives value their bonus at a fraction of its face value.”   We then spent two hours discussing that statement.

In both women’s eyes the issues are the trends in executive compensation to long deferral periods, bonuses held in stock and the potential value reduction through future downward adjustment and claw back. The issue for executives is economics 101.  A dollar has less value tomorrow than today and uncertainty over the number of tomorrow’s dollars reduce the value still further.  Yet, the increasing costs of executive incentives weigh heavy on the corporate balance sheet and in the eyes of the shareholder advocacy groups.

Pressures on bonus structures

The demand for longer bonus deferral periods reflects the perceived risk horizon of the impact of executive decisions.  The driver for deferral into stock is to increase executive alignment with shareholder interests.  Increasing conditionality around claw back of bonuses paid and value reduction of unvested payments is a reaction to executive misdemeanors.  All of these are worthy objectives – but they come with unintended consequences.

Impact

The cumulative impact of these changes is that the face value of the incentives becomes close to meaningless to the recipients.  Future value becomes unknowable.  Long deferral periods lead to great uncertainty as to value (the very basis of the Black Sholes calculation).  Stock value is heavily impacted by external events such as market crashes. Decisions made in good faith can, with several years’ hindsight; look wrong if not negligent, leading to high levels of management risk aversion.  The cash flows on which an executive has to base her future become smoke and mirrors.

Organisational penalties

The core of a reward strategy is to attract, retain and motivate.  If the recipient of a reward does not value the payment at the same level as the cost to the organisation, the strategy fails. Motivation and retention is reduced if lower value than the cost is attached to the award.  Yet, the balance sheet, P&L and share dilution have heavy organisational effects in both dollar and reputational terms.

The impact on the individual executive’s behavior is also meaningful.  Risk aversion becomes important to avoid penalty.  Capital protection rather that appreciation becomes a driver to reduce future uncertainty.  As we have seen in some labor markets, upward pressure on base salary and thus dollar certainty is increasing.

Unintended consequences – lose lose…

We are at a tipping point.  Remuneration costs are rising, for executives value is falling; external criticism is increasing rapidly as is remuneration regulation. There is a vicious circle of increasing face value to make future value meaningful; something of a tail chasing strategy. The system is broken.  Not yet beyond repair, but the longer the malaise festers the more painful the eventual solution.

A root and branch review is needed and needed now.  Executive compensation has always been complex and opaque.  Its death rattle is now being sounded – at least in its current form.  The reward profession needs to move contemplation from its navel to this vexed subject before it is too late; although what the alternatives are I shudder to contemplate.

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October 14, 2013

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HR, Metrics, Reward, Reward communication, Strong analytics

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Pay reviews; the Compa ratio magic. Strong Analytics V

Compa1

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.

Compa4

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

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September 25, 2013

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HR, Metrics, Reward, Reward communication, Reward Strategy, Strong analytics

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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.