By James MacAvoy, October 29, 2019

Data. It’s a word that strikes fear and excitement in the hearts of all project managers, scrum masters, and project teams alike. 

We know we want it, but we’re not 100% sure what to do once we get it. 

We request, remind, chase down, test for, and eventually receive this precious data - only to have these familiar questions raised:

• Where do we fit this into our project life-cycle?
• How do I make this data actionable?
• Who ate my clearly labeled chicken salad sandwich in the office refrigerator?  (I know it was you, Jeff)

Although answering these questions is an important step, at the core we have to dig into why we have to ask these questions in the first place. 

1 / Fear of Data

The primary issue we have to deal with when it pertains to data is fear. 

At its root the inherent nature of data can force us to rethink our direction, disprove our hypothesis, or cause us to realize that we’re trying to solve the wrong problem. 

Any of these results can force a major shift in your project direction. For project managers in particular, who typically hate seeing their project plans flushed down the toilet, at first glance data can feel like a problem.

Data does present a problem also familiar to project management regarding the implications of data in the project and how do we mitigate potential issues.  The reality is, those questions are much easier to answer than potentially developing a product that is completely useless to the user.

As Shayna Stewart asks in her article “Does the consumer find value in my product?”, data — no matter how scary it might be — allows us to answer that question before our product potentially falls flat with that consumer.  

2 / Project Management Life-Cycle

The standard project management life-cycle typically consists of:

Initiation, Planning, Execution, Performance Monitoring, and Closure. 

In a typical digital project, if we incorporate data at all then it is usually within the planning phase. Then, often to a lesser extent, the performance monitoring phase and even worse, usually with a brand new team with no historical knowledge.

To effectively deliver a consumer-centric product that adds value to our users we need to incorporate the use of data throughout the project life cycle.

This means that we need to continuously be reviewing our direction against any learned insights as well as continue testing to validate our hypothesis and the decisions we are making through the project.

Additionally, the considerations we make while running a project will need to be reconsidered. 

As Project Managers, it is ingrained in us to deliver a project that meets all scope requirements, on-time, and at/under budget. 

We’ve all seen the project management triangle of constraints - and likely seen the illustrations of how when one of those constraints is affected the overall quality of that project is in jeopardy. 

3 / Value Delivered

What is typically not considered in the triangle of constraints is an incomplete picture of project quality: in addition to these constraints we should be considering value.

We have all delivered a project over budget, or later than planned. All of those situations are never fun, but the far worse situation is delivering a product that the consumer finds no value in. If we do that, then it really doesn’t matter if it's over budget or late because it’s already a failure.  

A reasonable argument might be that the value is already factored into quality, which in a sense is true. But all too often the project lead’s focus on quality is based on requirements or at the very least a project brief. Without the necessary data those requirements could be wrong. 

In this scenario how we calculate quality is just one part of what we need to factor. When we consider the overarching value to the customer, our definition of quality could actively change, as it should.

But There Is Hope…

Much of what we have discussed above revolves around being comfortable with fear and uncertainty.

We have to know and understand that the more information that data provides, the more that it could change our best laid plans. 

Additionally, the more we incorporate data into the traditional project management methodology and process the more likely we are to see those fears come to fruition.  

However, as project leads there are ways that we can avoid the potential pitfalls described above.  If we incorporate data into every phase of the project management life-cycle, and plan for the potential disruption that this new information may cause, we are far less likely to be surprised when this disruption happens.  

We know there will always be changes to a project, but as long as we do not ignore all the information we could have, no matter how scary, we can get in front of that risk and minimize what causes this fear in the first place. 

Training ourselves to understand that change is good, disruption is good, and ultimately adding value to our consumer’s lives is best.