How do you use data to make project decisions?

The thing about data is that it is only ever as good as the context under which it is collected, analyzed, and/or presented. Data without context is just a bunch of numbers, so, in my opinion, it is extremely important that project managers fully understand the contextual data that plays into project outcomes before defining project data requirements. One thing I have found very useful for gaining a better understanding of project context is placing a bigger emphasis on metadata. This has allowed me to better analyze past projects to determine why certain processes did or did not work, and by looking at the historical contextual data, I am able to fine tune my overall process to best fit the specific needs of the current project.

I believe that a better use of data comes from a better understanding about the data analysis process, including having the necessary support from the team to compose a good information base for decision making: ask, prepare, process, analyze, share, and act. Beyond that, it's important to have a good definition about data distinction, especially when it comes to data analysis for decision support. First one, the quantitatives data that include both statistical and numerical facts, for example the number of requests.... The other one is qualitative data, that describe quality or subjective items that cannot be measured with numerical data, such as user feedback about the service or product .

From my experience, data can be used to support or challenge a project path or roadmap. After you create the roadmap, it is important to test its true viability. This is where data can be applied. Some data will support your initiative. Some data will prove otherwise. My two cents.

The significance of clean data in #sustainabilityreporting Data is extremely sensitive in nature. Because it is the only way to ensure sound decision making, it is critical that we only use and process clean data. E.g., The grid emission factor is typically expressed in kg CO2/MWh. However, we usually get power consumption in KWh from electricity bills. After ensuring correct KWh (suggested to wire it directly from the meters), it must be converted to MWh and then multiplied by the corresponding grid emission factor (using macros). To ensure accurate data, the kg CO2 obtained is usually converted to tCO2 (again using macros). However, softwares such as #Enablon further smoothen the job by avoiding manual interference. Thanks. #GRI

My work so far has been very scientific in nature hence the data plays a significant role shaping project outcomes. However, I can't entirely agree with the fact that there's a single way to define the impact of data on a project outcome, instead, I believe you need the option of flexibility while working for a specific goal. Any project decision can be based on multiple factors, some are qualitative and the rest are quantitative. A combination of these factors can help you achieve the best result you intend for. However, there still will be some unseen factors that may influence the work. I suggest leaning on experience, skills and logic alongside the data to make fruitful decisions.

One thing I have found helpful is to have understanding of how the data will be used in the downstream process useful to decide the appropriate tools and platform that would meet the need.

It’s also important to define what will be your transactional data vs analytical data. We also need to consider the source of truth or master data management to effectively use the data stored.

In project management, the goal needs to be defined with the corporate model (mission and vision). One established, data should be collected from the front line workers to the customers themselves. That way, the framework can change with the needs of the clientele, as well as give support to employees where applicable. Storing data can be on physical computers/media and onsite servers, as well as backing up the information on the cloud platforms. Encryption, as well as security software, needs to be provided to each storing device used. The use of password-protected files is also a must. A project with its own dedicated email protocol or corporate intranet can allow for quality, dictionaries, and limit access to the project's team.

Information governance is the key here. Laws, contractual requirements, and best practices will inform your information governance strategy. Your strategy needs to be future proofed so you aren't having to constantly make changes. If you're using Microsoft Teams, should you create separate Teams for each customer, or one large Team that holds data for multiple customers? The latter approach may not meet legal and contractual requirements because people who aren't supporting the project will likely be able to access that customer's data. And then there are data retention requirements! The bottom line is It's important that PM staff coordinate with governance, risk, and compliance (GRC) staff to account for legal and contractual risks.

One thing I focus on here is the scaling and repetitive nature of the solution that provides me with the flexibility to do analysis but, at the same time can be automated on a recurring basis. For example, I would create a visualisation or dashboard once that updates automatically with the new data.

In project management, data is what will determine a preferred outcome. When a team synthesizes the known quantities that affect streamlining processes to client-employee relations, a corporation needs to actively engaged data from a human perspective. Graphs, reports, and algorithms give a team the black and white understanding of an issue and possible solutions. Data should be understood as a supporting role to the actual implementation of changes suggested by it.

One of the best bosses I've ever had taught me this: tailor your presentation to your audience. It sounds very simple, but it is truly profound. Just think about how many issues in the workplace are caused by unclear communications - as perceived by the audience. What was clear to the engineer speaking wasn't understood by the CEO for example. If your audience is technical, then they may appreciate "in the weeds" data. But if you are presenting to the C-suite, focus on presenting higher level representations of the data and keep "in the weeds" slides as backups.

It’s essential to tell a story that’s backed by data for effective communication. One thing I always keep in mind while sharing is to communicate “so what” for my beneficiaries so they get the message and do not get lost in the data web. One should avoid a common trap of trying to showcase their data work rather than the actual story or action point based on the data

What is your company's mission, vision, and goals? Does the data support this corporate mythology? Once the project team establishes that the information collected supports the corporate ideology, then appropriate communication can be sent in its various forms. It is important that feedback from the affected employees and customers be an integral part of any communication. Actionable data should create a sense of resolution to an existing issue and bring needed change to any system. How are people's lives being elevated? How does that fit within the corporate model? Data can be thus transformed into a marketing strategy that has gained support through its project management processes.

Defining the KPI’s in terms of business value of the data driven decisions is important. The KPI’s can be driven from past experiences or industry benchmarking

Decisions are affected by market swings and projected anomalies. Not every project is perfect. Some changes will have to be accounted for in the data. If the project itself has many moving parts, then estimating prices in materials and personnel will have to be made for future events. What is needed that the projections do not show? How is a setback going to be accounted for? In project management, using data can help offset the normal operations, but a good team will also create a buffer data set to bring real life scenarios into perspective, like increases to minimum wage, insurance, and some materials. To make decisions that have merit, a team needs to calibrate their project with the data that also has yet to materialize.

An example would be during Covid, when material increases were happening left and right. Contractors in the middle of awarded jobs with PO’s already issued to vendors and not even the factories were able to hold pricing. Being able to see where costs were vs what they were at the current time gave a way of projecting planned increases in margin so not all of the item increase is absorbed by any one party involved in the transaction or at the very least, help to decide who should absorb the added costs.

In project management, the review process is essential in creating improvements. One way is looking at old data sets and comparing the present with the past. In this way, the team can see how the mission, vision, and goals of the company are being supported, as well as where there is lack. When a team determines their strengths and weaknesses over a course of different projects, then the team can make adjustments going forward. Tools such as communication with employees and clients affected by changes, and also listening to those needs, will help project teams develop their data to include a more fluid understanding of every working part of their company.

My goal is to convene a future webinar to share promising practices about the experiences from advising on multiple Global Data collection and reporting efforts for global organizations and global projects.

Strive to keep your processes lean in each phase of the data collection cycle. This will inevitably serve to keep project efficiency up and shift focus toward the project goals. As the other contributor mentioned, focus on the story.

I worked for a community college. Our project management teams were focused on our technical, financial, and community needs. What was lost in translation were the employees. Many times, teams rely too much on data sets instead of actually asking the people most affected, in this case: front line employees and students. If you would like your decisions to help with customers, then the management and administrative aspects of the company need to keep the mission, vision, and goals front and center while giving employees the tools necessary to better serve their clients. Without a supported front line, the data is just a set of numbers, and affects the corporate bottom line, because customers do not like transacting with powerless employees.

I would like to see the International Development community work more with instilling the so-called 'soft skills'. These are the skills that touch people encouraging change. Would love you comments.