The Future isn't what it used to be

Remember when Video calling was the stuff of science fiction?  Now the technology's been around for years, but the vast majority of phonecalls are not video calls.  On the other hand, SMS has had phenomenal growth - 8.6 trillion text messages are sent each year, according to Portio Research.  Decades ago, if you had to predict:

On a global phone network where both high-definition video calls and short text messages are possible, which would be the dominant messaging system? would likely think that video calls would be the dominant technology.  Certainly British Telecom thought so, and gets bonus points for the Aussie Accent in this clip:

...but the future has a way of surprising us, and what existing trends tell us now can only tell us so much.

One of the problems with extrapolating existing trends is that it can miss major changes at the periphery of the prediction - your overall direction might be right, but the implementation won't be as you expect it. I love the prediction in this video from 1957 that by the year 2000, recipe books will be replaced by punch-cards - right direction, wrong time-frame, and understandably but amusingly misses predicting the extinction of punch-cards in the late 70's / early 80's.

It's instructive when thinking of the future to think about the extension of current trends and developments - but the world doesn't always work in a linear way.

To effectively use data to forecast the future, the forecast is only a starting point.  Here's a process that works in Strategic Workforce Planning:

  1. Do a current state analysis - for a given topic, look at how things are today.  For the workforce, this means profiling the demographics, skills, productivity, locations of your staff.
  2. Extrapolate existing trends - look at the changes that are already occurring, and extrapolate these into the future.  This will identify unsustainable trends, and give you directional insight.  In workforce planning, these changes will be occurring through your hiring and retention trends, and internal movements.  This is what's sometimes referred to as the No Change Future State - if all existing trends continue, what will the future look like?  At this point, you get the "punch card recipe book" view of the future workforce - directional, but likely very very inaccurate.
  3. Do an environment scan and look at those PEST factors (Political, Environmental, Socio-Economic, and Technology factors) that may have an impact on your forecast.
  4. Of the factors from point 3 above, identify the two factors that both a) have an uncertain outcome; and b) will have significant effects on the outcome.  Note that this is not a risk matrix; risk matrices score factors on likelihood and impact - here you are scoring on uncertainty and impact.  A factor that's uncertain and would have a high impact, for example, would be an election result where the two parties have significantly different policies that directly impact your business model.
  5. Create a grid of those two factors - and think about what would happen in the future (whatever your timeframe) in your area of interest in each of those scenarios.
  6. Find commonality in those four scenarios in terms of how the world would deal with each of those scenarios; and you may have some insights into future events in that space.

    Chances are, you'll still be off the mark, but you'll have gone through a process of looking at some of the ways that you might be off the mark... and you will probably get some insights into just how varied the possible futures may be.  This will allow you, when planning strategy, to think about some techniques and initiatives that may be applicable to all possible futures, and even uncover areas for improvement that can be made today.  Ultimately, planning for the future is more about building in flexibility than it is about building in certainty.

    Special Bonus Video - clothing in the year 2000, circa 1930.  It's the sleeves what does it.

    posted by Alex Hagan

    Bob does his own workforce planning by outsourcing his job to China

    Hitting the news last week was a story about an employee who outsourced his own job to China, at 20% of his wage, so that he could watch cat videos all day while getting paid.  According to The Next Web, "Bob" was paid several hundred thousand dollars a year across multiple employers, and outsourced the lot to China for $50,000 a year.  His typical work-day was something like this:

    • 9:00 a.m. – Arrive and surf Reddit for a couple of hours. Watch cat videos.
    • 11:30 a.m. – Take lunch.
    • 1:00 p.m. – Ebay time.
    • 2:00 – ish p.m Facebook updates – LinkedIn.
    • 4:30 p.m. – End of day update e-mail to management.
    • 5:00 p.m. – Go home.

    Verizon, the company who ultimately discovered what was happening (not the employer) said on their blog: "Investigators had the opportunity to read through his performance reviews while working alongside HR. For the last several years in a row he received excellent remarks. His code was clean, well written, and submitted in a timely fashion. Quarter after quarter, his performance review noted him as the best developer in the building."

    Bob and Bob - Productivity Consultants from the movie Office Space

    What's surprising is not that this is possible (though Tim Ferris, author of the best-seller the 4 Hour Work Week should get in contact for a case study), or that someone would try it.  It's certainly not surprising that Bob was fired.  What's surprising to me is that "Bob" got away with it for a long time, and may never have been detected had he set up his VPN properly to make it look like the connection was coming from his home (and, as a telecommuter, actually watched his cat videos from home, rather than come into the office).

    I'd love to know if the organisation that Bob worked for is now looking at an "official" outsourcing the role - clearly his tasks were location independent and results based, and Bob's "results" were the best in the organization at 20% of the cost.

    What are your thoughts - is Bob the hero or the villain in this story?  And assuming his employment prospects as a developer are dim now, what career should Bob move into?

    This post was originally published on

    The False Proxy Trap

    Earlier this month, Seth Godin wrote about the False Proxy Trap:
    "Sometimes, we can't measure what we need, so we invent a proxy, something that's much easier to measure and stands in as an approximation."
    We do this all the time in HR out of necessity - we measure employee satisfaction because there's a connection between satisfaction and productivity, for example; and it's difficult in many (but not all) roles to measure productivity directly.  Godin goes on to explain how this can become a problem when we focus on the proxy (in this example, employee satisfaction) and forget the goal (in this example, employee productivity):
    "...When we fall in love with a proxy, we spend our time improving the proxy instead of focusing on our original (more important) goal instead"
    I believe we often fall into this trap too - being obsessed with employee satisfaction metrics as if they are an end in themselves, forgetting that the point is to increase employee productivity - and that:
    1. There are many other paths to boosting employee productivity; and
    2. Not all of the ways to increase employee satisfaction will also increase employee productivity.
     What are some other examples of the "false proxy trap" in HR?  Please comment below!

    posted by Alex Hagan

    Big Data for the Workforce - Workforce Analytics makes it into Harvard Business Review

    Big Data is big news, and workforce analytics got some press this month under the guise of Big Data - even though the tools and benefits of workforce predictive analytics have been around for years.  Is there more to come?

    Over on this post about Cultural Change at Aetna, I mentioned that there were two Harvard Business Review Articles of particular interest to Strategic Workforce Planning - that posts covers the first of these.

    The second article that came to my attention was Making Advanced Analytics Work for You, part of a series of articles about "Big Data".  This article sites an example of where a predictive model for workforce planning made a direct contribution to the bottom line.  
    "Ultimately, that approach of using a simple tool to deliver complex analytics substantially improved workforce planning and reduced the need for new hires and overtime."
    Using a ssimple tool to deliver complex analytics substantially improved workforce planning and reduced the need for hires and overtime

    It's interesting that it took Big Data to get the benefits of workforce analytics into HBR - when the tools and benefits have been around for years!  Still, we can expect to hear more and more about the benefits of data analysis and predictive modeling over the coming years, and that can only be a good thing for workforce planning.

    posted by Alex Hagan

    Cultural Change and Strategic Planning

    Over the last couple of editions of the Harvard Business Review, there have been two articles that have particularly caught my eye as being relevant to Strategic Workforce Planning.

    Cultural Change that Sticks
    The first article that caught my attention was Cultural Change that Sticks, which gives some insight into an enormous strategic shift that Aetna made in the early 2000's, and the implications that had for its' organizational culture.  It talks about the importance of aligning organizational culture to organizational strategy when making a major strategic shift:
    "Too often a company’s strategy, imposed from above, is at odds with the ingrained practices and attitudes of its culture. Executives may underestimate how much a strategy’s effectiveness depends on cultural alignment. Culture trumps strategy every time."
    The article goes on to suggest five principles that are critical when dealing with cultural change in an organization.  Perhaps not surprisingly, there are close parallels to the strategic workforce planning model in these principles (though we word them a little differently):

    • Match Culture and Strategy - Strategic Workforce Planning aligns the Capability, Availability, and Productivity of the workforce to the Organizational Strategy.
    • Focus on a few Critical Shifts in Behavior - Typically, Action Planning involves a limited number targeted strategies to close the gaps between the "No Change Future State" and the ideal future workforce.  In this post from way back in 2010, I spoke about the importance of focusing on a few critical human capital metrics, that are targeted to specific parts of the workforce.
    • Honor the Strengths of Your Existing Culture - In workforce planning we talk about understanding the Current State and the trends that are occurring, rather than starting from a blank slate.  In doing this analysis we look at not only the challenges with segments of the workforce, but the opportunities also - such as those metrics and trends that point to statistically significant high performance in a part of the organization.
    • Integrate Formal and Informal Interventions - Perhaps not a complete match here, but in SWP we look at both formal (metrics and statistics); and informal inputs into the process, such as Environment Scanning and Scenario Planning.  Good workforce planners look outside the formal structures of an organization and segment by talent, not just by roles or departments; and
    • Measure and Monitor Cultural Evolution - Two of the critical and ongoing pieces in workforce planning are Environment Scanning and Progress Monitoring - these allow you to check that your action plan is actually working, and that the future that's unfolding is in line with the future you forecast when you first created your plan.
    The second article is about Big Data, which I'll post over the coming days...

    posted by Alex Hagan

    Right People, Right Place, Right Time... Wrong Mantra?

    In the past week, I've read several different definitions or introductions to Strategic Workforce Planning as  getting "The Right People, in The Right Place, at The Right Time".  It's catchy... but is it true?  There are a couple of long-term trends that are occurring with workplaces that indicate we should change the definition...

    Let's think about what the intersection between the Right People, the Right Place, and the Right Time might look like:

    Under this definition, the optimal workforce is at the intersection of all three...
    • The right people in the right place (but at the wrong time) might be thought of "The Bench" - parts of the workforce that are not utilized currently, but will be when demand increases.
    • The wrong people in the right place at the right time are parts of the workforce where there is a demand for work, but those people are not the right people to perform the work.  These might be parts of the workforce that are now misaligned to the organizational strategy.
    • The right people at the right time, but not in the "right place", are parts of the workforce that would be able to do the work if location wasn't a requirement.  If the work could be performed remotely in any way, it might fall into this segment of the diagram above.  This includes offshoring, telework, and outsourcing; but it also includes those parts of the workforce that just happen to be located in a different office, or a different department.
    It seems that workforce planning should include the work inside that last segment - if the work needs to be done and can be reallocated to other parts of the workforce (productively), then options that will allow that to be done should at least be considered in a strategic workforce plan.

    Increasingly, the workforce is becoming location independent - and this is only going to increase.  By changing the mantra to "Right Skills, Right Time" I believe Strategic Workforce Planning will be more inclusive and effective.

    posted by Alex Hagan

    Want to increase profit margins by 50%? Implement Strategic Workforce Planning

    There's been a lot of coverage this week about a new research report by the Boston Consulting Group, who issued a press release entitled: Talent, Leadership, and Strategic Workforce Planning Top the List of Critical HR Capabilities in 2012.  The title is a bit misleading, but the content clarifies.
    Let's be clear, these three areas have always been critical - the research shows that:

    1. Organizations are now self-reporting both that they see the link between those three areas and organizational profitability; and
    2. They are also conscious of their own deficiencies in those areas.
    Significantly, the report shows that companies using best-practise Strategic Workforce Planning have revenue growth 1.4 times - and profit margins of 1.5 times - those that are least capable in Strategic Workforce Planning - a compelling reason to start a Strategic Workforce Planning programme in your organisation.
    This also raises an interesting question - if organizations are aware of the importance of Strategic Workforce Planning, but are also aware of their own inability to implement it, what information or resources are organizations looking for that they can't find now?  I'm sure many of the people reading this post will have some answers to that question - and I'd encourage you to leave a comment with your thoughts. 

    posted by Alex Hagan

    Lies, Damned Lies, and Correlation Analysis

    There are three kinds of lies - lies, damn lies, and statistics - Benjamin Disraeli
    Aruspex uses a number of statistical techniques in its' strategic workforce planning software, one of them is correlation. Correlation explores the strength of a relationship between two set of data - price and sales, for example. It is a fascinating and useful tool when done the right way, but it can be fraught with danger for the uninitiated, particularly when applied to workforce data. Today I'm going to cover a little bit about how we use correlation, and some of the traps.

    Aruspex has used correlation to forecast the future workforce requirements for its' clients. We do this in some cases by finding relationships between the size of a workforce and how much that workforce produces. Once we've identified a relationship, we can then apply the formula to identify the size of the future workforce required to be to meet production forecasts. One of our clients used this technique recently to forecast a 10-year staffing plan in a complex environment. The approach worked well for our client because they had variable production levels, and needed to minimize the inefficiencies of being understaffed (the opportunity cost of not being able to meet demand) and its' opposite, the "bench" cost (having a workforce that was too large and could be better utilized in other parts of the business).

    Despite its' uses, however, correlation does have its' limitations and traps. Some of these are illustrated by the latest offering from Google Labs, Google Correlate. (The service builds on the technology used by Flu Trends, which analyses what search terms are being run at any moment and can detect possible flu epidemics as they happen). By loading data sets into this service, you can find correlations between your data set and what people search for on google. The results are interesting, but not always useful, for the following reasons:

    1. Small data sets lead to a lower degree of confidence in the results.
    Intuitively, we know that flipping a coin once and getting a "heads" does not mean that we should expect that coin to always return heads. Similarly, insufficient data points in correlation analysis can lead to useless - or worse, misleading - results.

    2. Even with large data sets, correlation can be a coincidence.
    It turns out that the workforce participation rate in Australia for the past 10 years, has been highly correlated with google searches for "Portland Craigslist". It's fair to say that this is likely to be coincidental, despite the correlation being very high. Most Australians have not heard of Craigslist, and would wonder what shape an Oregon was. Sometimes correlations will occur that don't meet the common sense test.

    3. Correlation is not the same as causation
    The US Bureau of Labor Statistics releases a quarterly Employment Cost Index. It turns out that the change in this index since 2000 highly correlates with search terms including "appreciation" - that is, an increase in employment cost coincides with an increase in google searches for the word "appreciation". What this analysis doesn't tell you is whether employees "appreciate" higher remuneration, or whether the higher remuneration is because employers "appreciate" the efforts of their employees. It certainly doesn't explain why either employees or employers would bother to google "appreciation".

    4. Sometimes co-correlation is due to a third factor you haven't considered
    The Employment Cost Index also correlates highly with terms including "House of Pizza" and "Asian Buffet". You could infer that an increase in discretionary income leads people to have celebratory dinners (in which case, Dominos and Pizza Hut could consider a marketing campaign to the "just got a payrise" market, because the House of Pizza seems to have that market all sewn up. Maybe an adwords campaign where their ads are triggered on searches for "appreciation"?). Alternatively, it could mean that there is a third factor that drives both wage rises and discretionary spending on restaurants - such as economic sentiment.

    5. Just because you find a correlation that makes sense, it doesn't mean you can or should use it.
    You may find highly correlating factors that do make sense, but aren't helpful or usable. For example, increasing wages correlated with searches for dentists and child support. You can draw some conclusions from this, but those conclusions are not very actionable.

    6. Finally, you'll get some gems.
    Often, once you sort through the factors above, you will find some things that are relevant, and of more than academic interest. The relationship between voluntary turnover and reducing salary increments that we found for one of our clients, for instance. The relationship between commute times and divorce is an interesting one for consideration in work design (once again, it's not clear whether the long commute is cause or effect). Peaks in voluntary turnover at certain Length Of Service Intervals can be identified via correlation, where this relationship exists in your data. Optimizing productivity by aligning work hours to employee's biorhythms is an interesting field of research that uses correlation.

    So if you're looking to identify useful patterns in your data, remember that correlation analysis can be useful where:
    • You have a significant amount of data points (a lot of employees, a long history of data, or a combination of the two);
    • You have one or more variables that you want to explore (what are some of the factors related to voluntary turnover, high performance, etc; and
    • You keep front-of-mind that correlation never tells you what is cause and what is effect.
    P.S. It turns out that the shape of Oregon is almost an irregular trapezoid, in case you were wondering.

    posted by Alex Hagan

    Delayed Retirements – a pending exodus or a structural change?

    It's nice to get out of the rat race, but you have to learn to get along with less cheese. - Gene Perret

    Retirement at sixty-five is ridiculous. When I was sixty-five I still had pimples. - George Burns

    The Conference Board has this month published a new report “U.S. Workers Delaying Retirement: What Businesses Can Learn from the Trends of Who, Where and Why” which highlights the need to pro-actively quantify future retirements and create a strategic workforce plan to address long-term issues.

    Median retirement ages have been trending upwards for many years, and the report attributes this trend to several factors, including:

    • people are living longer and require more wealth to be accumulated before they retire;

    • changes to social security such as increasing the minimum age for receiving a full pension from 65 to 67 are forcing workers to delay retirement (increasing pension ages by 2 years seems a popular trend – both Spain and France have also done this in the past year)

    • the removal penalties for collecting benefits while working has enabled workers to continue working beyond their nominal retirement age; and

    • systemic shifts from defined benefit plans (employers bear the investment risk) to defined contribution plans (employees bear the investment risk) have made retirement intentions more responsive to economic conditions.

    The report also finds marked differences in retirement rates and ages across industries and geographies. As a whole, the report raises some interesting points for Strategic Workforce Planning:

    a) Planners should identify which of the changes that are delaying worker retirements are permanent, as opposed to temporary – temporary changes such as workers delaying retirement due to stock-market performance may lead to a glut of retirements when the investments recover. Multiple scenarios should be modelled – at a minimum, consider a scenario where retirements revert to pre-recession levels; and another where the current retirement rate (or median retirement age) is now a permanent attribute.

    b) Some industries, such as Health and Construction, have had a more significant drop in retirement rates than others. States suffering from the largest house-price slumps tend to have more workers delaying retirement. It’s important that planners model figures relevant to their industry and geographies, rather than generic economy-wide figures.

    c) As with any trend, there are opportunities as well as threats. Some of the retirements that are occurring are involuntary retirements, meaning that there is a pool of highly-skilled workers who may be looking for work on a temporary basis or outside of their traditional industry.

    Telling the story behind the data

    When advising on workforce planning and strategy, we often talk about the story behind the data.  To me, there are two reasons why this is so valuable:
    Firstly, it allows the observer look deeper into patterns and trends – not just recognising that they do exist, but gaining an understanding of why they exist.  Without going through this process, it is easy to jump to the wrong conclusions and make disastrous decisions about your workforce – as outlined in an earlier post in this blog.  Looking behind the data gives you actionable insight.
    Secondly, creating a compelling story can help you to engage others in the practise of Strategic Workforce Planning.  Data without a story often doesn’t compel.  The data is important - but the story is what brings it alive.  Recently I stumbled across this video from Hans Rosling, who I’m sure you’ll agree is excellent at bringing the story alive.  His site GapMinder, by the way, is an excellent source of global economic data and visualizations.

    New Year’s Resolutions for Workforce Planners

    Well, it’s that time of year again where many of us reflect on the changes we want or need to make in the coming year.  Each year at Aruspex, we publish the top 10 New Years’ Resolutions for Workforce Planners.  We encourage you to pick at least three for 2011!
    1. I resolve to take achievable, pragmatic steps toward workforce planning. Workforce Planning is a journey which you must travel one step at a time, rather than attempt to implement a fully fledged approach on day one. You might start by introducing environment scanning, creating the right people metrics, or even building a forecast of your "no change future state". Whatever you choose, take the step, and then you can take the next one.
    2. I resolve to look outward and forward, not just inward and backward. Many workforce planning and analytics efforts focus on what has happened in the past inside our organization. Looking at external factors and looking into the future is becoming more important. Ensure that your workforce planning and executive reporting includes these vital aspects.
    3. I resolve to learn Strategic Workforce Planning techniques. Adding skills such as scenario planning, forecasting, and gap analysis to your current skill set might be the most important step you can take in preparing your organization for the future.
    4. I resolve to treat the talent market as a market, and apply marketing techniques to it. The talent market is becoming increasingly challenging, and we need to start competing in it just as we do in the markets for customers and capital - that way we will be competing to win!
    5. I resolve to be willing to forecast the future. Forecasting the future is an inexact art, but many disciplines, including finance and marketing, do so - with varying degrees of accuracy, but almost always with value gained in the process. Remember, all our knowledge is about the past, but all our decisions are about the future.
    6. I resolve to filter data and convert it to information and insight. While a lot of data can be interesting, very little of it is normally useful. Data becomes information when it is positioned in context, and is insightful when it relates to your organization and the executive can easily understand and interpret it to take action.
    7. I resolve to make Workforce Planning a priority in my organization. Can you imagine hearing "it's not a priority" for business planning? With the economy providing brand new challenges and changes, failure to workforce plan could prevent you from achieving your business plans, and the return on investment in workforce planning is usually compelling - make a real business case for your executive!
    8. I resolve to stop letting today's issues make me stop planning for tomorrow. Think of Workforce Planning as the ounce of prevention you need to prevent the pounds of cure you are spending putting out the fires of these burning issues. Look to the future and phase out this fire fighting!
    9. I resolve to share my experiences with other workforce planners.
    10. I resolve to say "why?" and "what if?" at least three times a week!
    Please feel free to share with us in the comments section what's happening with you and resolutions for 2011; how you went with your goals for 2010; and/or whether you think there are any more we should add to the list!
    From all of us at Aruspex, happy holidays and best wishes for 2011. 

    Aruspex wins best Workforce Planning Software award

    Today at the HR Demo Show in Las Vegas, Aruspex won the “best in class” Workforce Planning Software award. The first conference of its kind, the show does not include trade show booths on an exhibit floor, but live, 1-hour software demos. A demo under those conditions (live audiences, live demos) shows what the market really wants to see – the software, not the spin.

    A number of comments in the twittersphere were the speed of implementations, the flexibility of the interface, the integrated methodology, and predictive analytics, and capacity to deal with contingent workforces.

    Other comments included reference to the company culture that showed through in the demos – the CEO’s passion, that it was an “exciting” and “fun” demo with a “sense of humor”.*

    We’re truly honored and would like to congratulate other winners and thank the judges!

    * I was in Vegas with our CEO in August and trust that it was a different sense of humor today!

    Word Cloud for Strategic Workforce Planning

    Being such a believer in “the story behind the data”, I love tag clouds as a way to visualize a lot of qualitative information, which is pretty important in workforce planning.
    Lexy Martin shared a link to Wordle with me, so I used to analyze this blog…and then saved the results in the Wordle public gallery.
    I love it – the four biggest words are workforce, story, planning and sense.  What are the biggest words in your word cloud? 

    Not-for-profit investments in workforce – industries AND cities. Sourcers – pay attention!

    Last week I tweeted on the Gates Foundation investing in skills in the energy workforce, and here is another story on not-for-profit funding in labor markets.  In this case, it’s the Living Cities Collaborative investing in five inner city projects, including employment, aka workforce.  The cities in the project are:

    • Baltimore – focus on creating job opportunities and improving neighborhoods in Central and East Baltimore, while preparing residents for opportunities created by the construction of the Red Line, a 14-mile east-west transit line.
    • Cleveland – implement procurement, hiring, employee incentives and capital investment programs that develop local jobs and businesses that benefit low-income people in the region
    • Detroit – create a model for older industrial cities of concentrating population and activity in sustainable corridors, expanding opportunity for low-income residents, and reusing vacant land
    • Newark – integrated investments in housing, public safety, access to healthcare, green space, fresh and healthy foods and employment
    • Twin Cities – develop frameworks to create and preserve transit-accessible affordable housing and mixed-use, mixed-income developments, catalyze neighborhood-led development, link residents with job opportunities, and establish a more appealing private investment environment in transit corridors

    These are very interesting workforce supply opportunities for employers who are in, or could be leveraging, these areas.  In a workforce planning sense, they are new sources of supply, most of which may results in lower cost and higher engagement, particularly due to the collaborative, local approaches to the projects.  Employers who get involved in these initiatives may be able to create long term workforce advantage in these locations.  They are non-traditional, but potentially highly valuable.

    Are your workforce planning and/or strategic sourcing teams paying attention to opportunities like these, or are you more likely to be trying to get involved later, when the risks are lower…but so are the potential benefits?

    For strategic HR stop quoting and predicting numbers, start telling happy tales?

    Systematic HR’s post today on the art of the story and how it helps us make sense of the present made me think of a Roger Martin post in June, where he showed us that story telling is a vital skill for great strategy development. So, telling stories is great for the past, the present and the future.

    Martin’s post “moving from strategic planning to story telling” is about overcoming some of the main roadblocks to good strategy development by creating happy stories instead of focusing on SWOT analyses, spreadsheets and other idea killing approaches:

    Think about a strategic options as being just a happy story about the future. It doesn't have to be right and it doesn't even have to be sensible. It just has to result in your organization being in a happy place in the future. In fact, if it were absolutely right and utterly sensible, your company would probably already be doing it.

    Then, Martin recommends, look at the stories, and work backward to “what would have to be true?”

    When you have assembled the happy stories/options, you can then begin to deploy the most important question in strategy: what would have to be true? For each individual story, what would have to be true for it to be a terrific choice? Work backward from an attractive possibility to see what would have to be true to make this a feasible and attractive option.

    The story, of course, is also necessary for making sense of the present and past for, or as Systematic HR put it:

    HR is comprised of quite a few random pieces of data, from technology enabled analytics, process outcomes, talent data, HR transactional data, etc.  HR outcomes and strategies are usually aggregations of each of these areas as individual data points combine to create overall direction and outcomes – formulating the data in such a way that it can actually give us a sense of place, direction and story is more important in HR than any other function that I can think of

    Couldn’t agree more.  Place is today and the past, direction is your trends, the story creates your future, which is why these two posts with different aspects of story telling make so much sense together.  How are you doing with a sense of place, direction and story?

    How do you plan for what you CAN’T teach?

    Following on from last week’s post on biology and workforce, here’s a study looking at biological reasons for shyness.  It demonstrates a born personality trait called Sensory Perception Sensitivity, which causes

    This is all very interesting, but how might it impact talent strategy?  It’s basically saying that some individuals can’t be taught some behaviors including rapid decision making.  From the article:

    Example: Thinkers could survive in a dangerous situation that requires thought, but doers may have better chances in situations that require aggressive action.

    Combined with last week’s information on the relationship between biology and work, it means that in talent planning and development one size really does not fit all.  Rather, the types of strategies needed for different roles and groups will vary, not just because the nature of the work varies, but because the nature of the people drawn to the work varies.  Different strokes for different folks.

    Of course, good strategic workforce planning includes this as a fundamentally accepted situation. 

    Does your workforce planning approach incorporate this reality, or deny it?

    Born to the job? How biology impacts workers

    Fascinating article over in The Economist on various research biologist are doing on management and work.  The article looks at various studies in genetics, endocrinology, molecular biology and psychology and what the research might mean for business and particularly for their workforces.

    There are lots of interesting things in there, including the table I’ve included here which seems to show that we are born to engineering, business, creative arts, etc, but our genetics don’t impact our results in sales, finance and other areas.  It also looks at the impact of hormones, nature/nurture..and then the objections and issues this thinking faces.  These are mostly ethical issues, of course, but all worth a read.

    In a workforce planning sense, this might mean that our build, buy, rent decisions may need to vary according to the particular function – buy scientists, build sales people, for example.  The work is all very early, and nowhere near offering conclusions, but the conclusion of the article itself is worth thinking about.

    Often, the practical applications of science are serendipitous—and may take a long time to arrive. And even if they never arrive, understanding human behaviour is just plain interesting for its own sake. “We in business schools often act like technicians in the way we conceptualise and teach our topics of study,” he laments. “This owes much to the fact that a business school is more like a trade school than it is a part of classic academia.” Now, largely as a result of efforts by Dr Zyphur and others like him, management science looks set for a thorough, biology-inspired overhaul. Expect plenty more lab coats in business-school corridors.

    Classic academia applied to workforce.  Hmmm, that could be interesting…

    The answer to the ultimate question of life, the universe, and everything. Oh, and some thoughts on what makes a good metric

    At Aruspex, we often discuss what is or isn’t a good measure internally, and with our clients.  Generally, those discussions cover these 6 broad categories:

    1. The metric must be easily explained

    Perhaps the most useless metric ever calculated (although it is fictional), is “The Answer To The Ultimate Question of Life, The Universe, and Everything”.  The computer Deep Thought in Douglas Adams’ The Hitchhiker’s Guide To The Galaxy takes 7-and-a-half million years to calculate the answer as 42, and goes on to explain:

    “I checked it very thoroughly,’ said the computer, ‘and that quite definitely is the answer. I think the problem, to be quite honest with you, is that you’ve never actually known what the question is.”

    As in the above example, it’s not useful to calculate a metric that leaves you wondering “yes, but what does that actually mean?” Good metrics can be explained, in plain language, in 1-2 sentences.

    2. The metric must be actionable

    Having metrics that are of only academic interest can lead to analysis paralysis… the benefits of good metrics are not that they are interesting, but that you can use them to assist in the development or monitoring of strategic actions.  If they don’t meet that test, then they are better placed in your annual report than in your workforce plan.

    3. The metric must be timely

    Knowing what the attributes of your workforce used to be is not insight… it’s hindsight.  It’s important that you can gather and report on data quickly enough that you can use it to make informed decisions.

    4. The metric must be repeatable

    If you’ve remembered rule #2 and the metric is actionable, you’re going to want to ensure that you can recalculate the measure on an ongoing basis.  Without this, you won’t be able to track whether the actions you put in place are working.

    5. More is Less / Less is More

    The more metrics you calculate and present, the more likely it is that the most important ones will drowned out by the ordinariness of the others.  Focus on the important few metrics that meet conditions 1-4 above.

    6. Good context makes a good metric

    Well thought-out infographics that give shape and context to your data can make you sit up and pay attention, elevating boring data to valuable insight.  Stacked column charts and tree-maps, done well, can identify patterns in data that you just wouldn’t notice in a table.

    I would be most interested to hear others’ thoughts about the categories here, and whether there are any you would add?

    Where the jobs are today – meh. The real focus should be on where they are tomorrow

    McKinsey Quarterly rightly points out that most US jobs are in retail, financial services and construction; and that cool emerging sectors like biotech are a very small share:


    However, when the BLS (the source of the data above) forecast jobs growth, it’s a little different:


    Retail and finance aren’t growing too much at all, but, unsurprisingly, healthcare is surging.  The first chart above places focus on retail jobs…the second says healthcare.  The single biggest growth section isn’t even IN the first chart.  Hmmm.

    In workforce analytics, this happens far too often – we slice, dice, analyze and even obsess over the past (that’s what all our data represents, after all)…and we might not focus on the future at all.  And what a big boat that may well lead us to miss…so why, if that big boat is likely to have the biggest impact on the business, do we keep putting workforce analytics (analysis of the past) ahead of workforce planning (analysis of the future)?


    Aside:  Each of these charts uses very different industry classifications, so it’s hard to see apples against apples – which is very often the problem with charts and datasets. Take care there

    Swarms, weak links and simulations – the future of work?

    Gartner are forecasting ten key trends which will change the nature of work in the next ten years:

    1. De-routinization of Work
    2. Work Swarms
    3. Weak Links
    4. Working With the Collective
    5. Work Sketch-Ups
    6. Spontaneous Work
    7. Simulation and Experimentation
    8. Pattern Sensitivity
    9. Hyperconnected
    10. My Place

    Most of them are around the nature of working and team relationships, but some (like the simulation and pattern sensitivity things) are about different ways of operating.  Most of them have some impact on the kinds of work, and hence kinds of capabilities, people will be doing.  Potentially big impacts for the future workforce, but at different times, in different ways and with different degrees of impact.  Some will evolve, some will be “switch on” impacts.  But they all need to be thought about.  Definitely a good piece of research for a few water cooler discussions with the leaders of critical groups.

    Or, to swarm over, I guess…