Pete Williams: Prioritizing Scarce Data Team Resources

Pete Williams, Director of Data and Online at publishing company
Penguin Random House UK, shares how he’s learned to balance scarce
data team talent with reaching business goals

Pete Williams has held many data and analytics leadership roles
since 2013, in various sectors. But a common challenge across all
of them has been the need to manage finite data team resources
effectively.


In this week’s Business of Data podcast, he shares his approach
to doing this in a way that balances working towards an
organization’s long-term strategy with meeting its short-term,
tactical goals.


“I’ve been guilty of taking on more work than my team and I could
handle in the past,” Williams explains. “You take it on without
realizing that little thought has gone into what you actually
need to do to achieve something. And before you know it, your
scope explodes, and you can't deliver.”
How Williams Prioritizes Data Team Projects

Williams says his approach helps to deal with what he calls ‘wild
card’ projects. These are unexpected projects that must be
prioritized and can only be delivered by either supplanting the
team’s current workload or bringing in more resources.


Since data team resources are finite, Williams recommends
managing them by dividing the team’s work between providing
ongoing operational and strategic support for the business and
research and innovation.


He argues that the ability to weigh all potential projects
according to a common scale is also vital. Creating a universal
template for evaluating potential analytics projects both helps
company stakeholders understand the data team’s workload and
creates a fair system for deciding which projects to deliver
first.


“A common assessment template gives everybody a chance to pitch
for the team's scarce resources,” he explains.


An effective project evaluation template should ask questions
such as: Will the project generate revenue? Is it cost-efficient?
Will it save time? Does it serve an environmental purpose? This
will help company stakeholders to agree on which projects should
move forwards and which are less likely to drive business impact.
Key Takeaways


Anticipate ‘wild cards’. Data leaders must
allocate team resources to strike the right balance between
delivering long-term strategic projects, providing short-term
tactical support to business units and working on ad hoc ‘wild
card’ initiatives


Use a common scale to weigh projects. As more
projects come in, it will be harder to prioritize them. All
work should be considered on the same merits


Define what success will look like. Data and
analytics project proposals should include defined outcomes
that both demonstrate the value they will bring to the business
and enable comparison with other projects in the pipeline