CIO

CIO Insights: What not to do when hiring talent

Three Australian IT leaders share their advice
Note: This image was not used as the basis for the scenario in this article.

Note: This image was not used as the basis for the scenario in this article.

It’s the same old conundrum: You need a particular skill but it's not in abundance in the market. This means how you go about sourcing talent is crucial, especially if you are planning to have it in-house.

In this fifth installment of CIO Insights, we talk to three leading Australian technologists about where you could be going wrong when recruiting and sourcing talent.

Scenario: The CIO is planning to tap into data and analytics to help grow the organisation, and needs to add to the team to execute and complete projects.

The CIO hands over a job description to a recruiter to source a data scientist or data analyst, an "IT resource needed for big data projects who has at least five years’ experience in working in this type of role and has a master’s degree in data analytics".

The recruiter has a ‘tick-off’ list but cannot find an ideal candidate who ticks all the boxes. Nine months down the track, the organisation still has not found a suitable candidate, with the CIO feeling like his or her only option may be to outsource the role.

What could be wrong with this situation?

Elizabeth Wilson, CIO at Edith Cowan University


Really, the whole way it has been done [in this scenario] is pretty appalling.

It says “IT resource”. It’s very cold, and it’s not a human approach to this. You really need to take a marketing approach to attracting people into a job, particularly if they are really important roles for you.

So you need to use language that will attract people. What I find with myself and with the people we employ now is the culture of the organisation is extremely important to people. So referring to people as an “IT resource” doesn’t indicate a kind of nurturing culture.

Data scientist is a fairly new type of role, so to ask for that many years’ experience is unrealistic.

There’s a fine line in making it so broad that anybody can apply for it where you get say 300 people applying who don’t have the attributes that you are looking for, and being so narrow that you are really narrowing the field of candidates unrealistically. Somebody may be a great fit for the job, but they might not tick every single box that you want.

For me, there are two things that are really prime: aptitude and attitude. Skills can be taught, but aptitude and attitude can’t be taught. If you make a tick box where you absolutely have to have this particular skill, or this many years of experience, then you really are missing out on some opportunities. The whole way they have approached it has really narrowed the field of possible candidates.

Focus more on the attributes required to fulfil the role, and be prepared – given that it is a fairly new type of role – to grow your own. Look for people who have the right aptitude, and then grow them into the role. This means you have to be prepared to train people or develop them into the roles.

One of the conundrums for universities now is how do we predict what the future requirements in technology will be when we don’t even know what the technology will be in future? Specific technologies might not be here by the time the kids get out of university.

So it’s about focusing on a core set of skills that might be required for people who work in technology in the future.

Also, industry and universities need to work more closely together in formulating courses – industry needs to have input into the education process and universities need to have a really good understanding of what industry is looking for.

One of the really important things, especially for the more senior roles, is the less technical or softer skills that become more and more important. We need to have a more balanced approach to how we train people.

Maybe you do one year where you specialise in being a data scientist, but there needs to be broader understanding of the whole technology landscape before you get to that. You need to understand how you capture data through applications, business processes in relation to data – there are lots of things you need to understand before you can be really valuable as a data scientist.

In the technology space, people are always looking if a role is going to enhance their career opportunities in the future and what might those career opportunities be in the organisation. Rather than just having someone work on a narrow thing, look at how that could be expanded so he or she can do more interesting things. So it’s also about marketing these other benefits of working in your organisation.

Ajay Bhatia, CIO at Carsales.com.au


Firstly, I’m not surprised they haven’t found anyone.

To me, top talent cannot be boxed inside a specific skillset. I’ve always strongly believed in hiring people who can work beyond the brief. If that’s the kind of people you want, then putting them into this box of five years’ experience and a master in analytics just doesn’t seem right.

We are in a fast moving world, the skillsets are always changing. And it’s about people’s ability to learn fast, rather than having lots and lots of very specific experience.

If the organisation wants to bring product fast to market and needs to employ top talent to do that, then it needs to employ people who can work beyond the brief. Yes, their skillset may be data analytics that you’ve allocated to them, but there may be many times you would need to ask them to work beyond that on a day to day basis.

Asking for such specific experience at the expense of their IQ or EQ, is just not right. And by IQ and EQ I mean potential and the ability to learn things on the fly.

What does top talent really look for in an organisation or a job? To me, the first one is diversity in the role. I think diversity is one of those needs that every human has. It’s learning itself that keeps top talent going.

My observation around this over many, many years is when top talent stops learning that’s exactly the point they start thinking about moving on. So to be asking someone to do what they have been doing for the last five years isn’t really the best way to recruit this this scenario.

Give them variety in their roles; give them skill sets that will make it easier for them to get the next job. It’s not necessarily a bad thing that top talent comes in and say after three years moves on. If you haven’t been able to offer them that career path, that will happen.

At Carsales, I’ve found at least four or five cases where top talent has left us for those sort of opportunities, but they have come back to us in a year or two’s time. You don’t own anyone for life. People come back, and if they don’t come back they recommend you as an organisation to someone else.

The other problem is to do with process. This is my own observation, which might be a little bit controversial: As process goes up, the organisation’s attractiveness to top talent goes down. As process goes up, decentralisation increases.

What happens is if you want to do a new project you need to ask the data analyst, then the PM (project manager), then the product manager, the CIO and CTO, etc. People sitting in niche roles are getting frustrated through the entire process.

It slows the organisation down, and top talent never likes an organisation that is slow to make decisions. That’s why I’ve seen a lot of top talent start to work with startups these days and not wanting to work for larger organisations. They either start their own startups or they join a startup.

So the challenge here is for organisations not to grow into a mammoth organisation from a cultural point of view. It doesn’t mean you shouldn’t grow as an organisation, you absolutely should.

But you come up with a structure where there are small teams responsible for end-to-end for delivery of product or whatever key outcome you are looking for. Rather than creating lots of decision points, you create small empowered teams.

On a day to day basis, what makes top talent happy in an organisation is having not just a great boss but also brilliant peers. You are not going to spend every minute of the day with your boss, but you are going to spend every minute of the day with one or more of your peers.

Working with brilliant peers is so satisfying, in fact it’s infectious. You start to get better, they start to get better, then they start to make your organisation more attractive to other brilliant top talent. Eventually they create a culture of high performance.

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Syed Ahmed, head of business technology at Servcorp


I usually hire on potential rather than hard skills. Someone with at least five years’ experience in a nascent field is going to be hard to find anyway, so I would look for transferable skills such as problem solving or pattern analysis.

What you’ll find is people who come from traditional BI sort of space, who have reinvented themselves.

However, it’s a significantly different mindset to do big data type analysis versus doing traditional BI analysis. They are very different things, because they start from different points. One’s more exploratory and the other one is based on having a well understood set of parameters that you investigate.

There are parallel fields that lend themselves well to this sort of skillset – people who have a masters or a PhD in mathematics or propositional logic and that sort of stuff. You can tap into that sort of skillset.

It’s about how much time you want to invest in bringing them up to speed with commercial realities. What you really may want is someone with the core ability to attack a certain type of problem. Everything else you can polish around that.

I also wouldn’t necessarily start by looking for someone to fill the role directly if I didn’t understand it deeply first. My approach would be to engage a specialised consulting service to deliver two outcomes: set up the data analytics practice or framework, and then assist me in recruiting the right person to fill the role.

That way the consulting service, that I would ensure has expertise in data analytics, has assessed the maturity required to deal with the problem in my organisation, and can provide advice on what specific skills are required. They usually have a much better network of skilled professionals due to their focus or specialisation.

If engaging a consulting service was not an option, I would reach out to my personal network to source the data analyst.

If it was me, I wouldn’t write the job description for a data analyst by myself – I’ve been off the tools for so long so I wouldn’t know what to say technically. If you want to attract the right sort of people then you have to speak their language.

I don’t necessarily write job ads for developers or engineers, my teams helps re-write them because they understand what is current in the marketplace and what attracts the right sort of people.

Are you facing a particular challenge and need some advice? Contact Rebecca Merrett at rebecca_merrett@idg.com.au.

For more articles in the CIO Insights series, be sure to check out:
How to approach innovation
IT offshoring/outsourcing – how much is too much?
Dealing with shadow IT
Legacy systems – love them or leave them?