I was recently having dinner with a former colleague and he reminded me that it was only four weeks until opening day of football training camp. Normally this wouldn't be important, except he's a rival in my fantasy football league and was clearly trying to impress me with his attention to player moves, injuries and variables that would influence his draft day picks. “After all of the March free agent signings, I don’t even know who’s playing for whom anymore,” he admitted.
It made me think that of the similarities between managing a fantasy football team and a digital analytics team.
1. Build Your Team Around the League Scoring System
Scoring systems in fantasy football can change depending on the whims of your league commissioner. Last year our quarterbacks lost points for interceptions. Quarterbacks with accurate arms did better than those that passed for lots of touchdowns, but had lower pass completion percentages.
When choosing your team, build it for the organization that you’re in, not the one you think you should be. If you have lots of data collection set up work ahead of you, make sure you have someone on your team who knows your digital analytics platform. If you are planning to do deep dive analysis more than dashboards, then choose a strong analyst. If you’re going to be doing customer experience testing, then have the right person for the task. You can find a list of basic positions in my Dream Team article.
2. Know Team Member Strengths
Some receivers are great at putting up big yardage numbers and some score more touchdowns. You need to have realistic expectations about their ability and performance.
Same goes for you analytics team. You can have analysts who are stronger at doing the work and others who are stronger at communicating results and presenting to your stakeholders. Rather than get frustrated with what your team can and can’t do, consider analyzing and understanding their strengths. We just used a tool called StrengthsFinders to get a sense of individual attributes. Even though we all do digital analytics, we found our strengths to span 17 different areas. It is very helpful in understanding how to work with each other for problem solving, brainstorming and communication.
3. Play the Match Ups
In fantasy football, you look for the most favorable match ups between your player’s offensive potential against the team he’s playing against. For example, you’d hope that your running back is playing against a team that gives up lots of yards and touchdowns to running backs.
In considering your analytics team match ups, you’d want to make sure that you assign your resources to projects that play to their strengths. If you can’t have them lead such a project, then you’d assign a lead who can guide a junior resource or someone who needs mentoring or coaching to gain more confidence and skill in the performance of the task. Read Morten Kamp Andersen’s article on analytics team skill sets to help you consider match ups within your team and on specific projects.
4. Strong Flex Options
Having a good running back or wide receiver to score points from the flex slot can either be a failsafe if your starters are having poor games or a dependable point source week to week.
You analytics team is likely not deep. While it’s important to recognize and play to everyone’s strong suit, it’s also important to make sure that everyone has a strong second or third skill in case you need to fill in on more demanding projects or your “starter” isn’t available. Use team coaching, shadowing opportunities and external training as a way to give your team additional exposure and skills so they can be ready to step in when needed.
5. Play the Waiver Wire
If it’s a bye week and you need a good running back to fill in, you select the strongest free agent and plug them into the lineup for that week’s game.
If you have a specific analytics project that needs to be done, but no one on your team to do the work, consider pulling in a contractor or consultant for the initiative. You should always be on the lookout for new talent … either for an experienced hire, or trainee or junior with advancement potential. Sources can be people within your organization who have shown an interest in analytics, or currently support your work from another team. External sources can be from local networking groups, conferences and the Digital Analytics Association.
Title image by fotoedu (Shutterstock)
About the Author
Phil is senior manager, Enterprise Intelligence Digital Analytics of Ernst & Young. Phil was one of the earliest adopters and advocates for the use of analytics and has 16 years of experience in the field as a practitioner, industry analyst and consultant.
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