- How can your organisation retain its data talent in today’s competitive market?
Talent retention isn’t just an issue for data leaders. Leaders in all business areas have felt impact of the pandemic-induced “great resignation.” Indeed, a recent report by Randstad found that almost a quarter of UK workers are actively planning to change employers in 2022. Delegates were in broad agreement that covid exacerbated existing pressures within the data industry. Data’s importance has been highlighted by the response to the crisis, placing data professionals in hot demand.
Delegates fell into two broad camps: those that looking to stem the flow of talent out of the business, and those resigned to losing talent and instead thinking of ways to maximise the efficiency of a transient data office.
Those in the first camp aired their frustrations at a flaky younger generation of talent. Often impatient in the search of a promotion or susceptible to having their head turned by LinkedIn recruiters, early career analysts are leaving roles before these data leaders can derive value from them. Development initiatives can encourage retention, but there is an acceptance that salary trumps most efforts.
Leaders from the second camp have accepted that the Googles and Facebooks of the world will always have the upper hand when it comes to the salary war. There is a belief that trying to punch above your weight on salary or focusing too heavily on retention might not be the best approach for talent or for the team.
Instead, these leaders are happy for their data office to be used as a steppingstone so long as recruits contribute to the business. Doing so requires outlining the skills and competencies required for specific roles. Engaging with HR during the hiring process can help to ensure that new hires integrate quickly and generate value. Healthy churn can help ensure that teams retain the dynamism and ambition that comes with new, diverse recruits.
- What does good data leadership look like and how can we inspire/develop the next generation of data leaders?
Are you a leader?
It’s a direct question that split delegates almost evenly between those happy to say yes and those who struggled with the concept. Hanging over the debate was a shared mental model of what a business leader looks like – the typical driven, even sociopathic CEO or the evangelical tech bro. None present wanted to become either of those. Far more appealing is the model trained in military circles of servant leadership – the motto of Sandhurst officer training college is “Serve to Lead” – or operating in a collective model with relatively flat hierarchies.
When drilling down into the actions of leaders, there was commonality around key behaviours including:
- Representing data to the business as both advocate and shield;
- Serving the team to enable it to perform optimally;
- Balancing the day-to-day against the strategic purpose;
- Being the goal-setter and pace-setter.
Are your direct reports a next generation leader?
A level of EQ (emotional quotient) was highlighted as important for a team member to become a leader as it takes them beyond their technical and project management skills into the soft area of people management. Career development plans can be put in place to support this. For the data office, it is important to put in place succession planning as well as people profiling in order to align future needs and ambitions.
Organisations also need to offer a career path that allows practitioners to stay in their lane – becoming more senior with accompanying reward while still practicing at a technical level.
There was also a recognition that younger team members, especially Generation Z, are less work-oriented and need a different model to follow. Typically, a strong sense of purpose, social or environmental impact are important to this group. Existing leaders see this as an opportunity to change the model and also ensure they have the right focus.
- How can data leaders work together to make the data organisation more inclusive?
Diversity, equity and inclusion is a delicate subject that has been brought into sharp focus by the societal upheaval resulting from the pandemic. Delegates were in broad agreement that the data industry should strive to be more inclusive. Indeed, just under two-third of all new hires made in the UK data and analytics sector in the 18 months before September 2021 were male, according to a recent study by Harnham.
When pondering the root cause of biases within data, delegate perspectives varied. Several believed that existing inequalities are less about data and more about factors such as organisation sector, brand and location. The finance industry is male-dominated, and that filters through to data teams at financial organisations. Similarly, data teams within female-oriented brands are more likely to attract female candidates.
Several delegates reflected that the makeup of their data office has typically mirrored regional demographics. When an office is situated in a location that lacks diversity, it follows that data leaders will struggle to attract diverse candidates. With the onset of flexible working, location should become less of a determining factor (or excuse) for poor representation.
A range of methods are in use when it comes to tackling demographic imbalances. These range from broader cultural practices – looking for candidates outside of STEM subjects, publishing diversity statistics, spotlighting role models – to more specific measures such as anonymising candidate CVs and rewording job advertisements.
Certain words such as “analyst” and “leadership” have been shown to appeal more strongly to men, while words such as “collaboration” are more appealing to women. For neurodiverse candidates, video applications may be more appealing than written CVs. One delegate noted a significant uptick in the amount of females applying to an open position when the language and tone of the role description was carefully considered.
