Every decision in the project lifecycle is important. Some will influence expenditures, many will drive the
timeline, and others will determine the quality and effectiveness of the effort’s outcomes. Solid expertise
and experience are central to making good decisions, but smart decisions also rely heavily on accurate
and timely data. Information of all types should be employed to help your team make the best decisions
based on your organization’s overall goals and mission.
If you’ve had trouble agreeing on the best choices or selecting the right course of action, consider what
might be complicating your project teams’ data-driven decision-making efforts.
1 – You don’t like what the data tells you. Few project teams will tell you they aren’t expected to deliver
good results on time and within budget. But sometimes those expectations are complicated by a lack of
consensus during the project planning phase which leaves room for high-level stakeholders to influence
decisions later in the initiative’s lifecycle. Even if the data shows a clear direction for an upcoming
decision, the leadership team may have something else in mind. Human nature doesn’t always follow
best practices and people sometimes reject the findings from their data analysis because they don’t like
or agree with the answer.
2 – You don’t understand what the data tells you. So much project information is readily available that
teams frequently have more data on tap than they can evaluate, process, or use. This data abundance
can make it difficult to separate actionable insights from the noise. Depending on the number of data
sources and the volume of information flowing in, there may appear to be conflicts between different
information sets, or it might not be clear how (or if) several distinct metrics relate to each other. When
faced with confusion, people will often simply ignore what they don’t understand and move forward with a choice that isn’t properly informed by the data.
3 – You don’t believe what the data tells you. Most people begin a data analysis exercise with at least
some vague thoughts on what the outputs will be. If that early concept doesn’t match the findings, it can
be tough to unravel where reality and expectations diverged. When the analysis will inform a decision
about a strategically important project, understanding the nuances of ideas versus data is a must. Were
the experiences that shaped your predictions wrong or just a poor match for the current decision? Was
the data too old to be useful? Was the analysis done correctly? Seasoned professionals in any discipline
are likely to trust their gut when faced with conflicting information, and that can put your project on the
wrong path if you can’t prove your theories. Working with a data analytics specialist will give your
stakeholders the background necessary to identify the truth behind the data and reconcile the team’s
instincts with the information to ensure your decisions are based on fact.
4 – You don’t know which datasets are relevant to the decision you need to make. Teams have a lot
of information to choose from and they need to curate it—by dates, sources, type of data, or any another
combination of attributes—to ensure they’re focused on the data that’s most relevant to the current
situation. Something may be measurable without being particularly meaningful in the context of making a
single project decision. A data analytics expert can help you move ahead with the right blend of metrics
and background to inform each decision, plus support your team in building context around the
information to assist in making difficult decisions and determining next actions.
PMAlliance, Inc uses a team of highly experienced and certified professionals to provide project management consulting, project management training and project portfolio management.