The Data Dimension of Modern IT Projects

What is Project Management?

As described by Project Managers of today and of the past, project management is:

“the art and science of managing teams to achieve a unique undertaking by managing the competing constraints of cost, time, and quality.”

There are currently ten (10) “knowledge areas” identified by the Project Management Institute (PMI):

• Scope
• Time
• Cost
• Quality
• Communications
• Human resources
• Risk
• Procurement
• Integration
• Stakeholder management.

Interesting to note, the PMI had only 9 areas for many years. The most recent addition is “stakeholder management”. Indeed, that has always has been an aspect of project management that requires specific management.

Anyone that has been a project manager with decades of experience knew this long before the PMI integrated it into their curriculum, tests, and best-practices.

Project managers must evolve, and that is what I am here to talk about.

The Modern IT Project in an Enterprise Setting

To illustrate, I will use an example desktop PC transformation for a global corporation which has 30,000 seats.

Project Business Intelligence & The Life of the Project Manager

The size and complexity of projects has become so large that it can be a full time job for the project manager to collect, organize, and cleanse data and to turn that into a project plan. It will take significant time each week to update status reports and dashboards. Survival of the fittest has made it such that IT project managers have Excel skills and are VLOOKUP masters.

In our sample desktop transformation project, the business intelligence around those PCs will be sketchy. In the early project planning phase it should be part of the IT project manager’s planning to identify what data sources exist and how those will be consumed by the project.

It should be part of the project plan to identify data sources that are needed but do not seem to exist. This translates into a risk — specifically a risk due to missing project intelligence.

It is worth noting, that in many organizations the ownership for delivering project intelligence data is shuffled around. By that, I mean the stakeholders say “You can get that from this team”. And then you go to that team, and they say “nope, try this team”.

After it bounces around with ownership being avoided, at the end of the day it gets placed upon the project. Hence, why I have come to think of data & analysis as being a core dimension of project management.

Complex Projects Have a Significant Data & Business Intelligence Need

There will be internal enterprise management tools deployed which inventory hardware and there will be data from human resources systems. Between IT asset management systems and HR systems, you can bang those two data sources together to get a good source of data on the 30,000 PCs, who uses each, and by combining the HR data the PC data can be pivoted by region, business unit, department, etc.

In the planning stages, the project manager spends days or weeks on this, knowing it will be needed to build deployment waves, etc.

The next problem that happens, is that there is a need to publish weekly reports with metrics. Now the project manager has to go through that data crunching process each week, or they just make up numbers as best they can.

Data “Refresh” Need

It will almost always be necessary for the project manager to have to cleanse the data, because of mismatches between source systems, etc. It is this that makes the ongoing update efforts take significant human cycles.

The Political Landscape

I would be remiss if I did not mention the political aspects which all of this happens. As the project manager goes about identifying source systems, and how the data will be collected and collated, the resulting output will likely cause some stakeholders’ brows to raise. This is because the numbers don’t match what the head of end user computing has been publishing.

Now the project manager has to spend time with that stakeholder to help them understand why the numbers the stakeholder has are flawed. Throughout the project, there will be rocks thrown at the data and numbers. The project manager must always be prepared to fend off these rocks.

The Project Manager Becomes the Data Czar

What happens in all of this, is the project manager’s data becomes the golden source. That is a good thing, but it is a double edged sword. Because there will be other projects and programs which also would benefit greatly from that data.

Data Needs Evolve as Risks Appear

In addition, as all of this is happening, at some point it becomes apparent that certain software packages which are deployed may not play well with the desktop transformation. The head of the global packaging team will say those packages are deprecated anyways, and from their perspective that is the end.

Good Data is a Must for Risk Management

From the project manager’s perspective, the idea of having teams re-image PCs in the middle of the night and the possibility that there will be business impact, that is just not something that can be ignored. Should that happen, the project manager won’t want to say, at that time, “sorry, that package is deprecated”. So the question becomes “How can we know which desktops, and who uses those packages, so we can make sure they don’t still require it.”

Now the project manager has to seek out package data from some internal system, and integrate that with the golden source of data, and produce a risk heat map that shows where we think there are PCs with deprecated packages.

Somewhere with that corporation, there will be a way to get an inventory of each PC’s software packages. If not, as a last resort it is almost trivial to write a PowerShell script that can inventory installed software. However, it is not at all trivial to get that executed across 30,000 PCs, because of IT governance policies… and because somewhere within that IT Organization there is a team that is supposed to be doing this.

A Project Is Only as Good as It’s Data

A project manager that has good data which is integrated with the multiple systems is in a good place. With good data, every dimension of risk can be examined, planned for, and controlled.

Without that data, the project manager has blind spots. There will be risks that go undetected and at any point in the execution phase that will happen and the project will have it’s emergency brakes pulled abruptly.

Stakeholders will wonder why this wasn’t foreseen, and why they were blind-sided. The only answer is “because we didn’t have that data”, and just as the project manager says that, all eyes turn to the stakeholder that heads up that technical area and that stakeholder says “no, we do we have it”.

Recovering from this will take considerable stakeholder management efforts, and at the end of the day no one can roll back time and prevent the project hiccup, and all that is happening is blame is being placed.

Project Managers of the Future: Data Management is a Core Skill

The outcome is drastically different if the project manager is a subject matter expert in data mining, cleansing, and data integration. Because the project manager ensured the project had that data to cover that area of risk proactively. In my view, the better route is having a project manager that has the data expertise.

Moving Targets & Data Agility Needs Means Excel is Deprecated

Modern projects that touch 30,000 seats must consider that business continues. In our example, as the 30,000 desktops are transformed over the course of months, there will be business as usual efforts to deploy new desktops and decommission old. People will join and leave the company, and IT assets re-assigned. The entire company might do a re-organization, and your project will not be consulted to assess the impact.

Thus, it becomes necessary for the project manager to refresh their data on a frequent basis. That frequency will be weekly at a minimum, but the project manager that has data mining and business intelligence experience that can be once a per day, or 3 times each day, etc.

To Be Clear, We Are Talking About Automated Data Mining & Integration

It just is not possible to use traditional excel based data management to corral all the data, align it, and turn it into actionable data, and with the agility that is needed for frequent refreshes.

A project manager with expertise in modern data & business intelligence will be able to deliver the necessary data without having to manually refresh data.

Database & Business Intelligence Tools for the Job

A project manager that is fit to thrive in the future will depart from excel and VLOOKUPs in favor of SQL database with proper design. VLOOKUPs in excel are almost always used to do a JOIN.

The project manager that finds themselves spending significant chunks of time creating VLOOKUPs just needs to recognize that the better tool for that job is a SQL database.

If trying to use a spreadsheet , the project manager will extracting data a from source systems in CSV format, and there are data tools that can extract that same data into a database.

From there, the project manager would leverage BI tools like SSRS, MS PowerBI, Pentaho, Tableau, etc. to build reports and dashboards on top of that data. This is a lot easier than it sounds, and it is relatively straight forward and easy to create these presentation layer user interfaces into the data.

With the data in a BI tool, instead of the project manager having to do a weekly “re-crunch” of the data and put that into a deck, the project manager simply publishes the link into the reports and dashboards, and advertises it is updated daily, etc.

The Need for Other Systems to Ingest This Project’s Data

In addition, by using a business intelligence set of tools, the project manager also gains the ability to provide an interface for others and other systems to integrate with the project’s data. This has a lasting impact on the organization because this data will live beyond the project.

I am sure that still today, the links I established for dashboards during my company’s Windows XP → Windows 7 transformation are still working today, and likely being used to managed the Windows 7 → 10 transformation today.

How to Find an IT Project Manager of the Future?

All of this said, the bottom line is that a project management resume that highlights Excel skills isn’t as strong and future-proof as if the resume highlighted database and business intelligence experience.

Project Sponsors of a project that touches 30,000 assets should have a project manager that is asking for BI and database tools, and should grow concerned if that isn’t happening.

When interviewing an IT project manager for an undertaking that will have a lot of moving pieces, ask what their data management plan would be. Ask where they think they can find the needed data in a corporation, and how they would go about turning that data into intelligence that can guide the project.