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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Epidemic of thieving bankers

Photo-by-Ian-Davidson

Introduction
Why have so many well paid, highly educated men (and it is almost entirely men) working in financial services caught the disease of fraud and theft? There is manipulation of LIBOR and FX rates, alleged dubious dealings in derivatives, insider trading; even down to evasion of train fares. Is the infection caused by greed, hubris, poor leadership or a corrupting culture? What is to be done?
Environment
Financial services is one of the most heavily regulated, monitored and controlled environments. Yet, even allowing for the gross incompetence of the regulators, the level of wrongdoing is breath-taking. It is essential, for the survival of the already low levels of trust in financial services, that the infection of thievery and self-enrichment is tacked with the vigor of attacking an epidemic.
Are societal norms to blame? Over the last few years we have seen enormous growth in tax evasion, expense fiddling and influence peddling (and that is only the politicians). It is arguable that the environment among the well off and those who should be setting an example in society is that obedience to the rules, both the spirit and the letter is for the little people. Even when caught the response is often that nothing wrong has been done; it is the rules that are at fault or that the regulations are to be gamed to the highest extent to the advantage of the individual. In that context I guess that a little rate manipulation is seen as quite acceptable. Informal sub cultures have developed, despite all the regulatory training and people development: where criminal or near criminal behavior is not just acceptable but encouraged. The disease spreads tenaciously, secretively, hidden from the cleansing light of day until it is too late. Certainly Human Resources appear to have lacked any form of X-Ray vision to detect the wrongdoing not just at an early stage but at any stage at all.
The Epidemiological approach
It is time that an epidemiological approach to the problem is taken. Examination of the causes, spread, transmission and monitoring of the disease in the hope of finding a cure or eliminating the causes of this epidemic is necessary and timely. We have big data tools, masses of data, specific examples and outbreak centers’ – perhaps even a patient zero or two. Trying to kill the diseases by punishing the host (in this case by large fines on the banks paid for, ultimately by the shareholders) is akin to killing the dog in order to get rid of the fleas.
Consequences
If we do not take the epidemiological approach now we risk simply driving the behavior underground making it harder to find and with even more painful consequences for the bank customers and the little people who always seem to carry the cost burden be it via higher taxes, austerity or erosion of personal wealth. This is the winter of our discontent, it is time to let lose the weapons of disease control before it turns in to a cancer that destroys the entire body of financial services.

Complex can of worms – The Investment Association urge fund managers to divulge pay practices

Photograph-by-Ian-DavidsonIntroduction
The Investment Management Association has urged its members to disclose their pay policies and how this encourages alignment between investment teams and clients. At one level this is a worthy aspiration, particularly given the recent attacks on the industry by the Institute of Directors. On the other it is a smoke and mirror exercise to hide poor practice and misaligned reward. Anyone with any knowledge of the workings of financial services reward knows that broad principals often hide dirty details at the operational level.

Complexity, culture and competition
The publishing of generic pay policies cannot reflect the necessarily complexity of remuneration structures and practice in the investment management industry. Investment and asset management is, like the majority of financial markets, heavily segmented, heavily differentiated and deeply complex, There are considerable differences between the activities of an Equity Index fund, an active bond fund, a property fund and an active emerging markets equity fund. Their risk and reward profiles are totally different as is often the time frame in which they operate, There are multiple flavours of “funds of funds” as well as cross holdings of house and non-house funds with the occasional derivative overlay. Each and every segment will have a different reward strategy, outputs and labour markets. The industry has long ago moved away from “long only” strategies to complex and hybrid mixtures of long, short, derivative and real asset funds; all with very different revenue and risk profiles,

The characteristics of retail and institutional funds can be different as are their objectives. The maturity and fund flows also add layers of complexity to structuring remuneration. Some investment funds are nearer hedge funds than the traditional investment approaches with hedge fund like carry arrangements and performance fees. No one set of remuneration principals can cover the vast array of arrangements – often set on a fund by fund basis and changed every year,

Culture
As we have learned from the history of the many investigations in to financial services malpractice; culture can play a larger role in determining behaviours, reward and performance than any set of policies. A typical example is the on-going issues with LIBOR fixing. The “nod and wink” or the tacit acceptance by senior management that certain behaviours will not be noticed if a profit is turned is as frequent in investment management as it is anywhere in financial services. The same pressures on sales and fund performance exist in this industry as it does in, say investment and corporate banking. The amounts at stake are of eye watering size. In 2013 assets under management just in the UK were £6.2 trillion and that is before the recent uptick in world stock markets. The FT estimates that an average compensation cost per employee at global asset managers is US$263,000 and is set to overtake investment banking pay by 2016.
Regulation in the sector is growing and increasingly odious. However, as history of the recent past shows, the regulators are invariably behind the curve and just do not have the intellect or resources to catch up with changing remuneration and risk profiles in fast moving, innovative financial services industries.

Competition
The competition for star players in the investment and asset management industries are just as intense as in investment banking. Individuals and teams move houses with remarkable rapidity; given the alleged longer term horizons. The facts are that performance is measure over months, quarters and annually the same as it always has been. Despite regulation, lucrative transfer terms are still a very active activity in this market place. Again, there are few star performances and everyone knows who there are. The fight to retain and recruit talent from a limited pool is one of the major drivers of remuneration in this sector. A 2013 survey by Heidrick & Struggles in late 2013 noted that:
• 41% of respondents are actively recruiting
• 57% of distribution professionals are open to considering new opportunities
• 50% of survey respondents had changed jobs in the last three years
Dated as this survey is, the trend can only be upwards given the ever increasing amount of assets under management in the global marketplace as investors scramble for return in the long-term low interest rate return environment.

The amount paid to these star players cannot be overestimated, although small in number their remuneration can add up to a considerable percentage of the employee costs of an organisation. Thus the use of averages is, like most remuneration measurement in financial services, deeply misleading. The differentiation, the complex nature of packages, the uncertain future value of compensation awarded today means that even establishing a base line is fraught with methodological difficulty.

Remuneration policies
If you wanted to be mischievous; it would be fun to play buzzword bingo with investment and asset management remuneration policies. They all want to attract, retain and reward. They all want to create shareholder value within the risk appetite of the organisation. The vast majority will pay lip service to employee behaviors and risk management as counter-balances to pure performance measurement. Frankly, I could write a remuneration policy for any of these organisations in a relatively short period of time.
These policies hide a complex reality of highly diverse practices with a dazzling array of performance metrics (often differing between individual peers in the same team) that would take an actuary to calculate the outcomes; and that is before the inevitable horse trading around what the metrics actually mean and how they should be applied.

The remuneration policy will no doubt talk of alignment of interest with clients; but what does that really mean in practice? As one large institutional investor said to me only last week; she did not really care how the return was made provided she they hit their target benchmark. Other investors will have strict ethical guidelines or even religious considerations as constraints on the activities of the managers. Thus what aligns with one client requirements will be an anathema to another. Yet it may well be the same investment manager running both funds – what then is “alignment”?

Concluding can of worms
The request made to investment managers to be more open on their remuneration is a good try but no cigar. Being pragmatic, it may be seen as a sophisticated effort to ward off yet further regulation and statutory disclosure. The reality is that, like so much remuneration in financial services any potential “truth” is deeply hidden and can only be understood by seasoned professionals and remuneration analysts and even then on the basis of numerous, conflicting assumptions.
I know from experience that the world of asset and investment management remuneration is complex as a necessity. It reflects the fragmented, segmented complex world in which these organisations flourish and make a great deal of money.
Trying to reduce the environment to the level of disclosure of remuneration policy is perhaps something of a pointless, resource wasting and ultimately a counterproductive exercise.

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.
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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.

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.