If you’re a project management professional with aspirations to manage big data projects, you already have a good foundation. You can make an immediate impact without having to go back to school for a Ph.D. in Data Science or Statistics. Your current project management and soft skills are ideal for establishing the framework for a new or existing big data project team and their projects. You just need to enhance the skills and knowledge you already have.
Here are eight ways to hone your skills as a big data project manager:
1. Develop your cross-functional team management skills
Cross-functional team management skills are one of the keys to running a successful big data project. Managing your big data project will likely put you into contact with new departments and technical/business specialties, so you’ll want to learn their various needs and how to address them. The cross-functional team for a typical big data project can extend to the following people:
- Executive team
- Data warehouse team
- Data team
- Business Intelligence (BI) team
- Domain experts
2. Become your team’s CLO (Chief Learning Officer)
Staying on top of new technology has long been important for anybody working in the information technology (IT) industry. Big data means taking that game up a notch. A project manager of a big data project team also needs to function as the team’s chief learning officer (CLO). This means:
- Identifying big data skills gaps on the project team
- Getting executive sponsorship for big data-related training and continuing education
- Putting together a plan to close the skills gaps via a combination of free and fee-based training (online, in-house, and through third party providers)
- Linking big data-related training and continuing education to team member performance reviews
The difficulties of hiring data scientists are well known out in the market. While project managers can certainly take the lead in fostering big data expertise in-house, this also requires creating a robust internal education track for technical staff and knowledge workers assigned to big data projects.
3. Manage your team’s big data knowledge base and processes
As a big data project team matures and settles on tools, methodologies and processes, the big data project manager should manage how the information is captured and documented.
The documentation process slides down the list of priorities on too many software development projects. But capturing your team’s body of knowledge is important for the following reasons:
- Locking down and refining processes passed on from a data scientist to a knowledge worker so the latter can work effectively
- Cross training team members to build out your team’s big data tools and technology knowledge
- Onboarding knowledge workers who are applying their existing skills to big data analytical and reporting tasks
4. Bring your change management skills
Tom Davenport, in his Harvard Business Review blog What Makes Big Data Projects Succeed, cites good change management as an element of successful big data projects. It’s up to the project managers to bring their own change management skills and implement the necessary change management tools and processes for their project team.
5. Join with other big data leaders in your community
The big data sector has an impressive sense of community for shared learning and professional networking. If you’re going to project manage in this field, look for opportunities to join the local community in your area. Take advantage of meet-ups, user groups, and big data conferences available in your local area.
6. Develop big data thought leaders on your team
Big data is still evolving with technology decision-makers across multiple industries trying to grasp the true benefits they can bring to their data intensive projects. Prospective customers are seeking out experts to help them. A project manager of a big data team should help develop the big data thought leadership on their team.
Here are some thought leadership tactics to consider:
- Work with corporate marketing to author corporate blog posts around big data topics.
- Work with corporate marketing and public relations to position team members as big data experts that industry publications and websites can interview.
- Work with the sales team to lend gig data technology expertise from the team for client sales calls.
7. Learn to manage up (if you aren’t already)
Some of the most troubling aspects of big data may not even be the technology or its implications on business. Rather, it’s the bad information and slipshod marketing that coats big data in a range of misconceptions. Thus, it’s important for a project manager of a big data project to manage executive leadership expectations for big data appropriately. There’s also the positive buzz around big data that’s bound to garner more executive attention. It’s important for the project manager to buffer their team while ensuring executive questions and concerns are being managed. This “managing up” should also extend to the sales leadership in the case of external products and projects.
8. Remember the basics
While your first big data project brings changes and additions to the traditional project manager role, there’s no reason to divert from the basics of project management. The successful big data project manager builds out from their foundational skills to assume a role that enables data scientists, developers, and knowledge workers to do their best work while building their big data knowledge and standing.
What other skills does the project manager new to big data need?