“The measure of intelligence is the ability to change”

“The measure of intelligence is the ability to change” – Albert Einstein

 

I think we will never know for certain when, where or who the first person was who decided to record data about individuals. The only thing we do know, is that it was a fantastic idea. There are different stories about the first time of manual data analysis. Florence Nightingale, a nurse who helped wounded soldiers during the war, assigned ‘points’ that provided herself and others insights in the status and prospects of wounded soldiers. Her presentation on the collected data and the analysis of that imperial data was iconic for that time[i]. Another example is John Snow, who used data collection and analysis to track down the source of a Cholera outbreak in London.  Through the data analysis, he concluded that cholera was transmitted by a microbe like agent or germ spread via water and challenged the accepted theory that it was transmitted via “bad air.”[ii]

 

Data capturing isn’t new, neither capturing it in relation to individuals. However due to all the technological advancements that we have seen and most likely will continue to see, we have more access to data that we ever had before. These advancements in technology ensure a broader product landscape for Talent Intelligence. Which enables us to access data and transfer it into actionable insights and intelligence to advice on strategic business decisions in relation to the external workforce, to people. “An instinct or a feeling is no longer enough in this time of continuous change, there needs to be precise and compelling data to back up business decisions”.

 

About  3 years ago, we wrote a whitepaper – with the help of many great colleagues– around Talent Intelligence, called: “Why what and how: A guide to commercially successful Talent Intelligence in a Digital era”. At that moment Talent Intelligence existed, but it was maturing and trying to prove value delivery for organizations around the world. We brought the insights of a variety of Talent Intelligence professionals together with the aim to inform professionals and organizations that have an interest in Talent Intelligence to understand more about the basics of it. Based on the number of downloads, and positive reactions, I’d like to think that we have achieved our goal. In my opinion the whitepaper is still good base to understand Talent Intelligence. However, I don’t need to tell you that in the past two years a tremendous amount of change has come our way. Due to changes that organizations are facing, they need to be more innovative than ever before. This to keep pace with the rapidly changing and competitive environment to achieve their goals. To be innovative, organizations need to have the right skilled people at the right locations, and they need to be proactive[iii].  And Talent Intelligence as mentioned in the whitepaper, evolves and changes as well.

 

But there is always change, if we want to improve our work, we need to listen, learn, innovate and become even more important.  And to improve, we need to change. Like Albert Einstein said: “The measure of intelligence is the ability to change”[iv].  In my opinion the most important is pro-activeness, and an area where Talent Intelligence can play an important role. I think within Talent Intelligence we have always been a bit reactive (or at least I have been). There is question, a hypothesis, or an issue and we conduct research. I think under the current market conditions, this need to change. More proactive advisory will be in my opinion the key added value for the next years for every Talent Intelligence department. How is the future going to look like, how can we anticipate early and how can data gathering and analysis help? I’m not saying you need to develop a glass sphere, although that would be nice, but look at the data analysis, what has happened in the past, and what conclusion can be made or what are the trends we see. There is so many data out there, that we can use to our benefits, even ones we don’t use to the benefit they can bring (e.g. recruiter feedback). We know what we know, but there is so much we still don’t know yet[v]. Having access to so much comes with new challenges. An approach to find the right data in the sea of available data and adequate protection are just two aspects that come to mind.

 

With 90.9%, location feasibility was the most common service offering in the whitepaper. I expect this to remain. However, based on my experience and conversations with other Talent Intelligence professionals, I believe that the questions we try to answer have shifted. Also, the way we challenge the business needs to shift. I will explain: The pandemic has shown me that I like to work from home. Close to friends, family, and commute time savings (and don’t get me started about the amount of commute cost it saved me). Of course, I miss colleagues, but for me personally the commute savings weigh higher (new born mom, so diapers cost me a fortune). And this is just me, I’m one of the 3.46 billion people in the global total labor force according to the World Bank (2021)[vi]. There will be more people like me and people that feel the opposite then me. Despite this, working from home is a new working location. It opens up a larger talent pool and opportunities to focus on skills needed regardless of someone’s location. Location studies are not only studies focusing on talent availability and forecasting anymore. Questions as which countries have the infrastructure to work from home? A culture to work from home? Why is the business so focused on location ‘X’? Conduct a persona analysis based on individual needs. These will become more crucial than before. We need to go deeper and understanding the bigger picture of what is going on. What works in one country, might not work in another. What might work for one person, might not work for another. What do you prefer, do you want the person with the best skills suited for the job, but who is located in a country where you have maybe 5 people employed ? Or do you go for the persons with average skills, but who lives in your HQ. Of course, I’m no tax expert, and certainly know that maybe not everything is possible. But I think this skill-based hiring approach is going to be more crucial than it is ever been. And very important, not everyone is the same, so I’m asking my-self already for a very, very long time, why on earth are organizations making one-size fits all policies?

 

Secondly came competitor insights. Will they remain crucial, yes! Every company is searching for those talented professionals that can help achieve the goals of the organization. So how a company is differentiating itself, remains or is going to be even more important. Many organizations are focused on compensation. They want to hire the best talent and are not afraid to pay more than the competition. There was a time that compensation was part of almost every single research I did, or where my peers where talking about. A recommendation or a mitigation strategy often entailed: ‘revisit your compensation policy together with Rewards’. But I haven’t advised this anymore and to be honest, I don’t think this is going to be the main question in the future. Will compensation get people into your company, yes it will. When you get a job offer which pays you more, it makes you think right? With more compensation, your kid can go to University, you can finally ask your girlfriend to marry you, or you can go on a nice holiday, one you really, really need after Covid. But the question Talent Intelligence is going to get more, is ok, we have the talented people in, but how can we make sure we retain them? I can recommend a location all I want based upon estimated talent availability and market conditions, and so on, but If you as an organization are not able to retain those people you attract, then I can recommend what I want, but it will be up for failure. If they will leave your organization, why are they leaving towards the competitor, what do they do differently than your organization? Exit interviews can be a source of information for this. Harvard Business Review (2016) surveyed 188 executives years ago around the exit process and three-quarters of the companies in their study conducted some type of exit interview for at least some departing employees. Harvard Business Review however identified that exit interview can often fail due to two reasons. The first is data quality. The usefulness of an exit interview depends utterly on the honesty and forthrightness of the departing employee. People may be less than candid on their way out the door for many reasons. Some feel pressed for time or unmotivated to explore their feelings. They may not want to say anything negative about a supervisor they like, or anything at all about a supervisor they don’t like. As one HR leader at a European mining company explains to Harvard Business Review, “Are they really going to tell you they’re leaving because they don’t like their boss? Probably not, because they want references.”[vii]

 

The second reason Harvard Business review explained, is a lack of consensus on best practices. The goals, strategies, and execution of exit interviews programs vary widely, and the findings and recommendations from empirical studies are often vague or conflicting. But Harvard Business reviews mentions that the deepest problem is that many organizations use exit interview programs as an excuse not to have meaningful retention conversations with current employees. And that is the evolution of Talent Intelligence, we, or at least I in my role, have always been focused on how can we attract candidates. And that is still very important, don’t get me wrong. However, the focus needs to shift into partnering with internal departments, to identify what makes employees stay. Think back at John Snow, our theory can be that employees are driven by compensation, but is that actually the case? Therefore, I think it is going to be more valuable than ever before to tie in internal data, HR and employer value proposition data (sentiment). What is our turnover at the location we investigate, what can we offer and how does it compare to our competitors (ties back in to the competitor analysis: how can we differentiate ourselves). Does talent know our company, do they buy our products, how many people visit our websites. What do our employees actually want and are we able to provide that? We need to have a broader view and tie in different type of data. Answering only the questions your stakeholder asks you, is not enough. We need to challenge them: “Location “X” is where you can find the talent, but if you don’t mitigate risk “XYZ”, it would be better to go for location “M”.

 

I still believe that LinkedIn and publicly available sources are the top used sources. I love LinkedIn, but I always want another tool that I can validate my data with plus LinkedIn’s penetration is high in some countries but low in others. Professionals fill in the information themselves and this can deviate from reality, fake profiles and so on. I often talk to people that are huge fans of LinkedIn talent flow, so am I. However, the only thing it shows us is where we are hiring and losing from. We need to think, ok what is the accuracy percentage of that company, on LinkedIn. Or how many users does LinkedIn have as part of the workforce of a country. If this calculated LinkedIn employee percentage is lower than 60%, I think we should challenge ourselves on using LinkedIn talent Flow data. It can give an indication, of course, but in my experience,  I have seen so many people not highlighting that accuracy percentage. A stakeholder that might be busy, sees as report and sees the data as the truth. But is it? If you have the LinkedIn talent data, check what is that company doing, read press release, check their open vacancies, compare that with yours. Talk to recruiters in the market, do they experience the same? What are new products they are going to launch, have they announced a merger or acquisition or a new partnership. What is the backend data?  Therefore, I never use one source of data. I prefer to use at least 3 different sources, if look into estimated talent availability. The outcomes will never be the same, I mean different sources, different methodology, different outcome. But it can show trends, it provides an overview. And for an average study I can use up to 60 different sources. Data availability and accuracy still remain a challenge. I always said to my team, be clear where the data is coming from, provide an accuracy percentage, if you assume highlight that you assume and why. Don’t make too many assumptions. Making assumptions within Talent Intelligence work is an underestimated risk that is getting bigger while the Talent Intelligence world is getting bigger. And everyone makes assumptions, we make assumptions based on who we are, what we value, how we are grown up, how we are thought, but that doesn’t necessarily mean it is the truth. If you cannot find the data, this should have been visible in a feasibility check before you take on the project. Hence a feasibility check is very important for me. It is about managing expectations, challenge your stakeholder and be pro-active in your advisory.

 

Is this the truth, is this the way moving forward? No, it is my opinion and I’m not perfect and I surely have still a lot to learn, but I think based upon my experience that this is a need to know on the whitepaper we have released a little bit over 2 years ago. And to be very honest, with all the changes that are happening in the market, this evolution will change.

 

[i] Science Museum, Florence Nightingale pioneer statistician, author: unknown December 10, 2018, https://www.sciencemuseum.org.uk/objects-and-stories/florence-nightingale-pioneer-statistician

 

[ii] Science Museum, Cholera in vicorian London, author: unknown July 30, 2019, https://www.sciencemuseum.org.uk/objects-and-stories/medicine/cholera-victorian-london

 

[iii] LinkedIn, Talent Intelligence: Why, what and how: A guide to commercially successful Talent Intelligence in a digital era, Marlieke Pols, December 24, 2019, https://www.linkedin.com/pulse/talent-intelligence-why-what-how-guide-commercially-successful-pols/

 

[iv] Medium.com, How to become more intelligence, according to Einstein, Benjamin Hardy, July 20, 2018, https://medium.com/the-mission/if-youre-not-changing-as-a-person-then-you-re-not-intelligent-according-to-einstein-73ba950d99d5#:~:text=%E2%80%9CThe%20measure%20of%20intelligence%20is,or%20external%20blocks%20to%20change.

 

[v] Brainy Quote, Donald Rumsfeld, data unknown, https://www.brainyquote.com/quotes/donald_rumsfeld_148142

 

[vi] World bank, labor force total, author: unknown, 2021, https://data.worldbank.org/indicator/SL.TLF.TOTL.IN

 

[vii] Harvard Business Review, making exit interviews count, Everett Spain, Boris Groysberg, April 2016, https://hbr.org/2016/04/making-exit-interviews-count