Where do you find the skills to implement analytics and then drive out their value? A recent Data IQ article featuring MBN Head of Business Development Rob Huggins looks long and hard at the recruitment options and finds that companies are having to work out new ways of meeting the challenge, from developing their own capabilities to looking off shore.
So, the board has agreed your data strategy, IT is working to put the right feeds in place and your analytics project is fully-funded and ready to go. All you need now is to find the human resource to implement the analytical data warehouse and tools, then a team to carry out the data mining and modelling which is set to transform your business.
What could possibly go wrong? Getting to yes is so often the hardest part of any new idea in business. Having overcome the financial and cultural hurdles that can get in the way of data and analytics projects, it might seem as if the outputs lie just a few months in the future. There lies the rub – so many organisations have had the same idea that there are far more fishing rods in the talent pool than there are fish for them to catch. It is not just the people with the ability to code and model who are in short supply – McKinsey’s Big Data report last year put that shortfall at between 140,000 and 180,000 in the US, which translates to 25,000 to 30,000 in the UK.
Behind that headline figure, it also suggested a need for 1 million managers capable of translating the business challenge into analytical terms and then repeating that job the other way around once an insight finding emerges. For the UK, that represents a missing cadre of up to 200,000 executives with those skills. To understand the scale of the problem, the Institute of Chartered Accountants of England and Wales, whose members deliver analogous professional skills to their companies, has a headcount of 140,000.
When demand outstrips supply to this extent, it is no surprise that, “we have a massive challenge as recruiters,” according to Robin Huggins, head of business development at MBN. He segments analysts into three types: loyal company types who are not interested in moving on; “job hoppers” who switch employers every 12 months; and loyal, but interested types who might make a move if the conditions are right.
Although the recession has kept a lid on job mobility, it has not kept down salary inflation. “Analysts with two or three years’ experience are now getting mid-level salaries that used to go only to those five or six years into their job,” says Huggins. At the same time, many of those loyal workers and job hoppers have realised their value to the business and are bidding up their pay and packages. The difficulties facing any company that wants to become analytics-led are revealed in the experience of one major UK broadcaster which works with MBN on a long-term basis. “They originally came to us with the task of building an analytical function that was to be best-of breed. We worked hard to find them senior analysts with experience, hands-on analytical ability and commercial knowledge – and we just could not find people at that level,” he says.
In general employment terms, the position on offer was a peach – well-paid, with a Central London location and at a high-profile, pioneering brand. Despite these advantages, the company eventually had to adopt an entirely different approach. This involved using interim contractors for six to nine months and getting them to transfer commercial skills to PhD and Masters-qualified hires who brought maths and statistical abilities. Huggins notes that, “they are just now ready to do the job. The company has grown its own, but was also able to pay them two thirds of what its target candidates would have got.”
This model is being adopted more often by other companies in a similar situation. It is why outsourcing partners with a large pool of analysts under contract, such as the big four management consultancies, are currently reaping significant revenues from the increased interest in data and analytics. Huggins identifies two other solutions which are being tried. The first is to outsource the back-end data mining activity to an overseas services provider, typically in Asia where there is a much greater supply of maths graduates to draw on. A number of data-driven marketing agencies use this approach, deploying a smaller team of analytics minded managers in the UK to take the brief then deliver the results. An alternative, but identical model is to pull together analysts who previously worked on specific, vertical tasks (such as risk modelling or pricing) into a single, centralised analytical resource – the likes of Accenture, Deloitte and Capita are doing just this. The second solution tackles the problem from the technology end. “There is a trend towards using open source software,” says Huggins. “The cost of licensing a proprietary analytical package onto the desktop of an individual is high. Then once you have bought it, you need people with skills in that particular software – and they are demanding high salaries.”
With the arrival of alternative data and analytical software such as WPS or r, much of this technology cost is removed, a much bigger pool of highly-engaged developers can be tapped into and a lot more business-savvy executives can be considered. “The catalyst has been the rise of sports betting. A lot of these people are sports fans using their expertise to develop spread betting and odds capabilities which they might be able to sell on. That has been their springboard,” says Huggins.
Given the level of requirement and a lack of human resource, it is not surprising that a new generation of providers has been eyeing this marketplace for its potential. Technology has much to do in closing the gap, as do specialist analytical agencies. BigData4Analytics is an example, founded two years ago by Mike Fish, who brings a dozen years of experience in software and venture capital and who has partnered with a former Oracle and Teradata executive. The agency brings a team of eight data scientists to bear on a raft of challenges which clients are struggling to resolve, often because they lack the right resource.
While it is currently boom time for consultancies who have an analytical resource to offer and new technology is making it easier to achieve some of these goals at lower cost, do not expect the skills gap to be closed any time soon. Recent political decisions are actually making the problem harder, rather than easier to solve.
“Government policy on foreign workers with skills has hit us very badly,” says MBN’s Huggins. “It used to be easier to bring in people with Tier 1 visas and to get them extended, so clients were happy to take on somebody with less than a year left on their visa.”
Which goes to show that however hot the marketplace might be for data and analytics, there are still some issues that are even bigger and hot, with immigration currently top of that list. While companies work on growing their own analysts and practitioners redevelop their skills set for next generation tools, it seems likely that human resources will remain the biggest hurdle for any project launched this year.