A data manager must meet very specific, highly specialised technical requirements. But as is becoming clear, a truly robust organisation thrives on communication, teamwork, problem-solving and project/process management.
That’s why enterprises are keen to build teams that can bring those values to the forefront, and are increasingly interested in a candidate’s soft skills. It’s a brave new world in which the old paradigm that power equals influence is being inverted – instead, as the traditional top-down management model gives way to a more lateral structure, those with influence will wield more power.
The ideal data manager of the future is strong communicator, with a solid grasp of the organisation’s needs, sharp commercial acumen, and the capacity to comprehend big picture challenges – and visualise solutions. Here’s our breakdown of the balance of skills the ideal data manager of the future would possess.
| Technical Skills
|| Soft Skills
- Data Science
- Big data
- Long-term vision
Where this falls down
Due to this lack of communication skills, we see many organisations engaging external consultancies to build business cases for IM projects.
The consequence is that the skills remain with the consultancy and aren’t transferred to the internal team. If this sounds familiar to you, consider how to include this knowledge transfer in your next scope of work. And ask yourself whether you’re overlooking the importance of soft skills in your recruitment practices.
Interviewing for soft skills
Hiring managers must embrace the importance of non-technical skills in order to build a strong team with the potential to make a real, long-term impact on the organisation’s data efforts. With that in mind, here are some suggested interview questions to get a sense of a candidate’s skills in communication, teamwork and problem solving:
- Describe a situation in which you felt you handled communications very well? What did you do, and why do you think it worked?
- Was there ever a time when you were negatively affected by poor communications? Perhaps the directions given to you for an assignment were not clear, or lack of clarity hurt a team project you were part of? How did you resolve it?
- What are some strategies you might use to tailor communications and convey technical information to people with different levels of expertise?
- Describe what working as part of a team means to you.
- How did you handle a situation where your approach to a project differed from a team-mate’s?
- Tell me about a time when teamwork helped you reach one of your own goals.
- What process do you follow in solving problems?
- Was there a recurring or unsolved problem at your last job you would have liked to solve? How would you handle it now?
- Tell me about an elegant or complex solution you’re most proud of having engineered.
Hiring decisions are driven by very specific and highly specialized technical requirements. But a truly robust data organization also thrives on communication, collaboration, problem-solving, and management of relationships, as well as projects.
Employers therefore should be keen to find skilled workers who can bring those values to the table, and who have the attributes or competencies that will enhance the performance and productivity of the enterprise. Non-technical skills add a level of depth that can make a tremendous impact on an organisation’s success, by collaborating on strategy, improving communication and morale, streamlining processes, and increasing customer satisfaction.
The importance of long-term vision
In our recent ‘State of Data’ survey, we were interested to see a divergence in views on the topic of long-term vision. While 24% of respondents considered it the most important quality for data managers to have, 13% thought it was the least important. We found it worrying that nearly 1 in 7 respondents appear not to think data managers need to understand the context of their work and how it contributes to the organisation at large.
We believe the data manager of the future must have long-term vision, in addition to a well rounded set of talents that balance technical acumen with soft skills. By continuing to engage in recruitment practices that focus solely on technical skills, companies will miss out on the unlimited potential of their data efforts.
What characteristics do you think the data manager of the future should possess? Are soft skills just as important as technical aptitude? Share your thoughts with us below – as always, we love to have your feedback.
To learn more about the state of data in 2015, download our whitepaper here.
"I think the route to becoming a valuable Data Manager is likely to be similar to that of an IT Manager. Most successful managers start out in a hands on position (coding) and eventually move into more business facing roles before abandoning any hands-on skills and focussing purely on management. It is important to remember however that just because managers (by definition) are no longer hands on, they still retain a solid grasp of fundamental principles. This, combined with their vision and ability to inspire teams is what makes them valuable. Loss of technical skills is almost inevitable as people move into more senior positions." - Andrew Dean
"I agree that soft skills are becoming as important as technical skills for data managers, but I believe there is a third set of skills that are explicitly required – business management skills:
• Project management.
• Programme management.
• Business process management.
I think there are two reasons for this:
The first reason is that, in practical terms, the only way of moving towards the long term vision is through projects (or, more likely, programmes), which need to be justified in terms of the benefits for the organisation. The Data Manager of the Future needs to be able to initiate, get approval for, and manage these projects within the overall business environment.
The second reason is that data only has meaning within the context of the business processes in which it is being created and/or used. The Data Manager of the Future needs to be able to act as a bridge between each of the business processes as well as with the technical function and so has to have an overall understanding of how the business actually works. Additionally, it is much easier to make the data model more complicated than it is to make it simpler –and the Data Manager needs to be able to push back hard to requests for new data to ensure it is really needed.
These reasons are particularly important whilst the idea of proper structured data management is still being “socialised” within organisations –my last employer used the SCOR (Supply Chain Operations Reference) Process Model: Plan, Source, Make, Deliver, Return and Enable. We added Data as a separate explicit process to both ensure that the data requirements of each of the other processes were being met; and that there was data alignment and consistency across the processes." - Mark Rothery