Developing people skills is the new frontier of success for the data professional; enabling the promise of data having an impact and transforming the enterprise
Introduction
The real world of working with data in the enterprise reveals some significant gaps in the toolkit of the data management professional. While the environment is replete with technical competence, tools and programming knowledge, all of these capabilities lend themselves well to human to machine interfaces, i.e. people working with systems. What can be lacking is the set of skills in working with people. Machines don’t have emotions, entrenched views, or biases (unless programmed that way). A solid technical skillset is no longer enough. The well-rounded data professional needs a set of soft skills to be successful in the dawning era of the modern data-driven enterprise. Consider five soft skills that would make an impact in the toolkit of the data professional.
Soft Skill 1: Change Awareness
There are some foundational skills needed in life that leaves one wondering why we were not taught them in school growing up, like how to negotiate or deal with conflict. Learning those skills as a kid would certainly make it easier to navigate life’s challenges. Well, in much the same vein, change awareness is a skill that every data professional should learn prior to starting their career. Remember the promise of data? It is supposed to transform the organization. Well, if that is true and that is what is taught in schools and universities, why are data professionals not equipped to at least be aware that data can affect change and that change needs to be managed. It doesn’t mean the data professional needs to manage the change, but they do need to be aware of the impact of change.
Soft Skill 2: User Experience
User experience (UX), the feelings a user experiences when interacting with an interface, is a well understood and valuable field in the software industry. However, it has not yet made the same splash in data and analytics yet, although that is gradually changing. Nevertheless, the data professional can still stand out from the crowd by learning from the field of user experience.
Even a basic knowledge and application of user experience principles can be a game changer for the data professional and most of it is common sense such as leveraging personas when gathering requirements. Personas also offer a great way to push back on chart junk and low value information through focusing on what data is truly needed.
Figure 1. What is User Experience? Image credit: Sherif Amin
Soft Skill 3: Wireframing
One of the most powerful skills the data professional can learn is how to wireframe. This pertains to those who must present data to end users either through a report or dashboard. Why is it so beneficial? The practicality of it. Wireframing brings so many things together. Seeing the components of the report or dashboard can build consensus, gain alignment, drive towards business value, and save buckets of cash. Don’t bother building that dashboard until the wireframes have been approved; the approval will save so much time. Also, developing a wireframe in PowerPoint means there is no need to learn a new tool. Just collaborate with stakeholders until the wireframes are in a good state.
Soft Skill 4: Storytelling
Storytelling is a widely used term in data literacy but it is not necessarily easy to execute. The data analyst who understands the narrative arc will be able to capture the attention of the audience and bring them on a journey that leads to action. Storytelling is a foundational skill that every data professional should have. An extension of storytelling is data visualization best practices, for without one you cannot achieve the other. Knowing the data-to-ink ratio, appropriate chart selection, and picking the right layout for the dashboard are all vital techniques to drive adoption.
Soft Skill 5: Facilitation Skills
One of the hardest soft skills to master is facilitation, especially for the more introverted professional. Yet, bringing people together in a room to leverage data and build consensus yields huge dividends. So many big rocks can be addressed early that can save major heartache later. Unfortunately, to avoid friction, difficult topics often are put on the long finger and only come to the forefront later in the development process. When not addressed in smaller, more manageable sections, these issues or questions can coalesce into major problems and potentially derail the data project. Bringing a group of professionals together into one room can address existing tensions or challenges, but it is essential to have an experienced facilitator lead the discussions. Otherwise, the effort can be fraught with conflict and unresolved questions.
Conclusion
With technology progressing so quickly and more people choosing data as a career, it is important not to forget the people skills that will enable success and allow a smooth path for data to fully realize the promise of being able to transform organizations.
