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  • Andrew Dugdale

How Big Data is unlocking new sources of Corporate Wealth

Updated: Jul 5

Big data can be like adding sales executives


Pretty much everyone these days has heard of ‘Big Data’, but how many firms are actually using it to unlock new sources of corporate wealth?

Lets’ start at the beginning – what is ‘Big Data’? Here’s what Google tells us: “extremely large data sets that may be analysed computationally to reveal patterns, trends, and associations, especially relating to human behaviour and interactions”

How well that concept of analysing large tranches of data plays into the sales talent arena!

Good sales talent is often the hardest to hire, and the most critical to get right. Failure is an expensive option, with not just losses in hard costs associated with the hire, but also in second round costs (loss of potential revenue), and third round costs of short, medium and even long-term reputational damage caused by putting a below par sales person out in the field representing your firm, in front of your customers. On the flip side, a good sales hire is a significant long term asset for any firm, delivering high levels of EBITDA year after year, as well as being a strong ambassador for your brand and reputation.

How vital is it then that the lens used for hiring sales talent changes from the traditional interview/‘gut feel’ process where failure is always an option, to a much more robust, data analytic approach, delivering significantly enhanced certainties.

So why is ‘Big Data’ not being regularly used right now to enhance hiring effectiveness and revenue performance of sales people? The answer is very simple – until recently there have been very few sources of high quality, reliable and robust ‘Big Data’ about sales people’s capabilities available to analyse.

Why is this? Because most of the data captured to date has not been robust or reliable enough to withstand the rigorous scrutiny placed on it by ‘hard analytics’. There has just not been the means or opportunity to capture data that is of sufficient relevance, quality and, most importantly, reliability, about individual sales people, to enable the formation of a database of knowledge, capable of being analysed through ‘Big Data’ methodology.

However, this is all changing very rapidly.

Earlier this year, LinkedIn Talent Solutions released a new report entitled “Data is the new corporate superpower!”[1]

In their findings under a section entitled “Data makes you an instant hero”, the authors say “Companies win in today’s world by hiring and retaining the best talent. That’s why you’re always feeling pressure to find more people, with more niche skills, faster. The truth is, data is your ticket to getting there. When everyone else is throwing out opinions about whom to hire, how to hire, and where to hire, you can sit at the proverbial table and point to the facts. Thus it’s no surprise that 69% of talent professionals believe using data can elevate their careers. Those who don’t? They get left behind”.

The same article under the section entitled “Answer your pressing questions and crack your tough issues” the authors say “the most common uses [of data] are to better understand attrition, skills gap, and offer-compensation issues”.

It is this that gets us to the nub of the problem. Understanding these factors, and doing so from a position of knowledge and confidence has often been seen as the real ‘missing’ in the hunt for these elusive Big Data advantages.

However, what has been notable, until recently, by its absence has been the sources of this ‘Big Data’. Especially sources capable of withstanding the rigorous analysis required for firms to feel confident relying on this data, in order to gain the powerful advantages big data offers, when hiring, promoting, or developing sales candidates.

One example of a sales talent assessment and analytics provider which has recently launched its own big data portal is SalesAssessment.com. Called Sales Talent Insight, this new big data offering uses reliable candidate data gathered from tens of thousands of assessments taken by candidates over the last ten years, from more than sixty countries, taken in sixteen languages, across a very wide spectrum of business sectors, and covering twenty one sales roles.

It is this huge database of reliable data that enables SalesAssessment.com to crunch the numbers and accurately predict which of your potential new hires, or which of your existing sales people, are wealth creators, and which are, or if hired, would be creators of competitive disadvantage for your firm.

Further advantage can be gained when the assessment data is aggregated across teams, regions, or even company-wide, and used to analyse the overall trajectory of the organisation’s sales talent performance potential, mapped over time. This new talent KPI is a very powerful predictor of a firm’s likely performance in the short to medium term horizon.

How does this work? Statistical analysis of any population will show that they conform to a normal distribution curve. This means that the majority of people are centred around average, with diminishing number of people above or well above average, and the same for below or well-below average. Hiring based on classic recruitment approaches is not able to reliably differentiate between those who are the above average, or even high performers, from the mass sitting at or even below average.

Yet the difference to a firm’s results are disproportionate to the few percentile points between one candidate and the next. If you happen to hire someone who is average, this means that a competitor who may be hiring based on ‘Big Data’ analytics, can choose to select only well above average candidates. This leaves you with a problem – your average sales person is never going to be seen by the customers as being up the standard of your competitors’ sales people!

This will result in disproportionate sales losses; think ever slipping pipelines, opportunities that just ‘disappear’ without a valid reason; these are symptoms of being outsold.

Big Data sales talent analytics enables firms to choose to only hire those sales people who are above average or high performers, leaving average and below average sales people in the market for your competition.

Couple this with clever regional or geographic analyses, such as that carried out by Novartis when recently looking to decide whether to put an office in Mumbai or Bangalore, and the power of Big Data starts to become clear.

Here’s what Novartis had to say (in the LinkedIn report):

“For months, Novartis debated internally whether its new office should be in Mumbai or Bangalore as each city had strategic appeal. By leveraging data from LinkedIn, the recruiting team was able to compare each city’s talent pool on factors such as mobility and employers. Career level was also a key point of comparison as Novartis successfully recruits most employees at mid-career. In the talent report, Mumbai was the clear winner over Bangalore with its much larger population of mid-career talent. Once the data was shared with all stakeholders, it only took three weeks to reach consensus on Mumbai.”

Add this type of demographic big data to data from advanced assessment analytics, and the ability is there for firms to locate ‘talent pools’ with the specific skills sets needed to map ideally to the expectations of each element of your segmented customer base, thus ensuring that you have competitive advantage at each and every interaction with your customers… and for the first time, this can all be achieved with reliable, robust data analytics – not ‘gut feel’.

If a firm were to take this even one step further, and add in the thinking shared by Prashant Pansare in his article “Trends that will shape the future of data analytics in 2018” [2] published on LinkedIn Pulse, in which he says “Businesses can now use data to accurately predict the needs of their customers”. With this ability available from Big Data analyses, plus the latest ability offered by LinkedIn to identify rich seams of potential talent, and adding in advanced sales talent analytics available from firms such as SalesAssessment.com, you now have the means to reliably “locate talent pools, in the areas you need them, with the specific skills sets needed to map ideally to the expectations of each element of your customer base”.

This is Big Data starting to offer us a glimpse of the new horizons in hiring premium quality sales talent, and through this, developing net new sources of corporate wealth.

Why is everyone not doing this?

It’s new, it’s different, but – those that see the potential, will be the winners. Finally, maybe, the answers to the old McKinsey War for Talent[3] questions that have vexed hiring managers for so long are starting to appear?

  1. https://business.linkedin.com/content/dam/me/business/en-us/talent-solutions/cx/2018/pdf/global-recruiting-trends-2018-v03.18.pdf2.

  2. https://www.linkedin.com/pulse/trends-shape-future-data-analytics-2018-prashant-pansare Further to a recent article, Prashant Pansare talks about how firms are using Big Data to analyse their customers: “Businesses can now use data to accurately predict the needs of their customers. This data could be made available in various formats; text, image, and video. Big Data is predicted to be the most powerful technology that gives answers to many consumer-centric questions that companies are trying to answer these days.”

  3. https://www.slideshare.net/dkdmadhubhashini/the-warfortalentmckinsey


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