Recruitment practices: Hiring from within

Recrutiing the data and analytics talent you need is a perpetual challenge, which is why looking at all possible sources makes sense. Within your organisation there may be a ready-to-go, untapped pool of skilled workers with the right understanding of your business. This whitepaper considers the pros and cons of hiring internally.


If you launched a recruitment programme and 13% of your target audience responded, it would be considered a resounding success. With talent acquisition a constant struggle for organisations looking to create or grow a data and analytics function, anything that expands the prospect pool has to be welcome. So what if an important source of new hires proved to be individuals already working within your organisation, but in other functions?

At a DataIQ Leaders roundtable, the chief data officer of an international bank explained how he had decided to create an in-house data science community to bring together practitioners and those with an interest in it. An open invitation sent to the whole organisation resulted in 13% of its staff asking to be involved. Part of the rationale was to find additional resource to support innovation. As the CDO said: “Experiments want people to run them.” As well as revealing a previously unguessed-at depth of interest in data science, the new community also brought to light an individual who was doing a maths degree in their spare time and had not told any of their colleagues about it.

It is that kind of undiscovered in-house talent that makes hiring from within a useful additional dimension for any D&A recruitment programme. While it is unlikely to deliver the quantity of candidates required on its own, individuals who do come from within the organisation are a significant bonus. Based on the discussion of this human resource, here are some key pointers when considering how to hire from within.


3 upsides of recruiting internally

1 – Open positions can be filled more quickly

At one retailer, positions for which it is currently recruiting are open for an average of 112 days and even longer for more senior roles. Even when the right individual has been found, the process of induction can mean a similar length of time is required before they are fully productive, meaning the potential loss of six to seven months of output. By recruiting an internal candidate, they may not have a lengthy notice period to serve, will already understanding the company’s operating model and processes, and may mesh quickly with the incumbent team and its client base. There is also a political dimension which can be leveraged to the advantage of the D&A function. One chief data officer pointed out to HR that they are listed as a keyman risk by the organisation – this meant they could argue for a deputy to be recruited which had previously been resisted.

2 – Incumbents have fewer preconceptions 

Many organisations have looked to partner with academic institutions in order to establish a flow of qualified graduates and post-graduates. Getting first choice of individuals before they finish their courses can be a useful way to be ahead of rivals. However, a number of DataIQ Leaders noted that many data scientists on courses are not aware of the real-world state of the data they will end up working on – academic data sets have been cleaned and normalised for use already – and are often not interested in the data engineering required. By contrast, individuals working within an organisation are more likely to have had direct experience of complexities and problems with data, so will probably understand the need to get involved with the raw materials before they can move on to modelling.

3 – There is no need to learn the business

It is a common frustration of hiring for data and analytics positions that candidates do not have any understanding of the business they are joining (and often lack any business knowledge at all). An internal hire will clearly be immersed in the culture, processes, goals and challenges which the organisation faces. That shortens their induction period and time-to-value – in one case reported by a DataIQ Leader, a successful internal hire brought genuine subject matter expertise which allowed them to identify hidden value within a business process.


3 downsides of recruiting internally

1 – Established salary bands do not map well against D&A roles

In many organisations, existing salary bands do not include data and analytics roles, so these have to be mapped against other positions. This often does not work in their favour since the nature and responsibility of the jobs can be hard to quantify or benchmark. One DataIQ Leader commented that a suitable internal candidate in their organisation who migrated into an entry-level analyst position would almost certainly have to take a pay cut if they made the move. This could be a significant barrier unless the individual is very highly motivated to build a new career. Offering below the market rate will make recruitment a struggle, both internally and externally, which other benefits such as pension schemes or flexible working can go some way to mitigating. Getting trained in data and analytics techniques can be attractive to internal candidates who will be aware of the expansion and excitement around this function. But this can lead HR to be unenthusiastic about internal transfers out of a fear that the individual will get skilled-up and then leave for more money elsewhere.

2 – Everybody wants to be a data scientist, nobody wants to be an analyst

Data scientist has been a high-profile job for the last few years and attracts a significant level of interest (as the bank’s new community experience demonstrated). But there is a downside – data science is considered to be innovative and cutting-edge with considerable freedom to experiment. By contrast, the tasks of an analyst may seem more constrained and less free-wheeling. Especially if there has been long-term engagement between analysts and internal clients, this perception may be hard to get past. 

3 – An internal candidate’s past may follow them

Candidates who are attractive to the D&A function are likely to have been involved with data or analytics in some form elsewhere in the organisation in their previous role, even if not in such a direct way. Where they have been engaged with a line of business, any conflict or challenges which that threw up may have created a reputation around them or embedded a view of their abilities. A DataIQ Leader working in a government company reported having had exactly this difficulty – one individual who had worked on policy where they had to interface with a government department had subsequently moved into data governance and is proving very adept. But the “taint” from the previous role (which had inherent difficulties and to which they were not best suited) has carried over. The data leader is working to support the individual, standing behind them, and is applying very visible quality assurance so that others in the organisation are clear that outputs are to the right standard. 


3 actions to take when recruiting internally

1 – Be visible

Internal communications are fundamental to the effectiveness of any internal recruitment drive. Other functions need to be aware of the data and analytics team and any job opportunities that exist within it. Some organisations actively encourage the process of hiring from within – at one transport company, this is seen as part of community engagement because it creates a career escalator for local hires. One of the most successful analysts there started out as a security officer within the business ten years ago, for example. But this is  a rare culture to find, so D&A needs to keep shouting about what it may have to offer staff working elsewhere.

2 – Recruit curiosity

It is a commonly-accepted view that a key aspect of a successful data analyst or data scientist is their curiosity of mind. While this can be tested for with problem-solving tasks, it is harder to spot in advance. But there are certain activities that are good indicators, such as running personal side projects, engaging with hackathons, or sharing analytics-related content on social media. You may even get lucky and find a candidate come calling on the D&A function, as one organisation did – that’s the strongest-possible sign of an active curiosity.

3 – Run projects or hackathons

Current practitioners in the D&A function are typically keen to engage with projects outside of their day-to-day tasks. Some organisations encourage this formally – at Google, data scientists can spend up to 30% of their working hours on side projects. That is likely to be too high for less well-resourced organisations, but creating an opportunity for experimentation and innovation is likely to deliver significant benefits. Whether using in-house data and a specific business problem or partnering with an external, non-competitive organisation such as a charity, this type of event will both motivate the existing team and also serve as a magnet for any interested, internal candidate. If a person from within the organisation responds to a company-wide announcement of a hackathon, then they are very likely to have some qualities that are of interest. That broad enthusiasm is exactly what the international bank uncovered when it launched its data science community.

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