Voices on Project Management

by Lynda Bourne

In my last post, Information Is Subjective, I outlined the way data is gathered and transformed into information by the subjective application of personal knowledge. Now, let’s look at how knowledge is created and shared (the gold connections in the diagram above).

People know things: Knowledge is organic, adaptive and created. It exists in the minds of people. Some of each person’s knowledge is explicit—they can explain the rules that apply to it. But much is tacit: intuition, gut feelings and other ill-defined but invaluable insights, grounded in the person’s experience.

Therefore, managing knowledge means managing people.

The fact that knowledge exists in people’s minds does not preclude joint activities to create knowledge, share knowledge and refine knowledge. But the people involved need to be in communication with each other.

Some of the structured ways this can be accomplished include:

• Various forms of meetings. People working together to debate or brainstorm a challenge and build on each other’s inputs often enhances creativity.
• Mentoring and coaching to help transfer tacit and explicit knowledge from the coach or mentor to the trainee or mentee.

Structured approaches work well if the information that needs to be transferred or created is understood, and the people involved focus on creating or acquiring the required new knowledge.

Less formal approaches are better for generating completely new information or insights that people did not know they were about to create.

Spontaneity and serendipity are encouraged through social interactions, such as:

• Communities of practice where people with a common interest interact. Good communities draw members from a diverse range of workplaces, backgrounds and knowledge levels.
• Member associations such as PMI.
• Other social networks and the activity of networking by an individual.
• Creating an organizational culture of open communication that allows and encourages both the asking of questions and the provision of advice. People cannot know what they don’t know and a small piece of friendly advice at an opportune moment can prevent a painful learning experience.

Knowledge will never be uniform in its distribution or in the way people interpret what they know. The function of a creative knowledge management system is to smooth out the differences as much as is practical and to facilitate the creation of new knowledge through the synthesis of different people’s ideas and insights.

So as you venture forth to share knowledge, remember:

• An effective knowledge management system is built on a symbiotic relationship between an effective information management system and a culture that encourages and facilitates the open exchange of knowledge and ideas between people.
• An information system on its own will at best simply make useful information available to people. There is no control over how, or if, the information is accessed or used appropriately.
• A knowledge management system on its own may create brilliant insights, but the information is organic and transient. Everything is in people’s minds and their knowledge leaves the room when they do.
• A knowledge management system is most effective when it combines these two elements and provides governance and oversight to extract the maximum value from the information held within the organization through personal interaction, conversation and other social processes. 

by Dave Wakeman

I try to start each post with some sort of hypothesis. In some cases, the hypothesis is clear to me, and, hopefully, you. Other times, however, the hypothesis doesn’t become clear until I’m done writing. 

This month, I’m on the side of a clear hypothesis built around much of what I have written about the last few years: The ultimate consideration project professionals need to keep in mind is that we’re in a people business. In the long run, the person with the best people skills often has an advantage. 

But what does that really mean? 

Communication is the key skill of a project manager.

I’m sure this falls into the trite, clichéd area of project management advice. But as I’ve witnessed time and again over the last few months, we often need a refresher on the basics of our profession. 

Being an effective communicator starts with having an expectation of what clear communication looks like, having a schedule that highlights what communication will look like and following through on your communication ideas. 

No matter what, remember your number-one job is to be a communicator. 

Communication is a people skill. 

Decisions are emotional, not rational. 

Spoiler alert: No matter what the decision is, emotion drives it. 

People like to think of themselves as rational. But that in and of itself is a nod to the emotion necessary to take action on an idea. 

You see, by trying to remove all emotion from a decision, you are often slowing yourself down because you are afraid of making a mistake. 

Being afraid is an emotion. 

Being excited is an emotional response. 

Whatever action you take is driven by emotion. 

Even if you don’t take any action, that’s an emotional response. Apathy occurs when the idea that you are being asked to take action on isn’t interesting enough for you to care about. 

People have emotions. Project managers deal with people. 

Projects are driven by ideas. People have ideas, processes don’t.
This one is likely to get the most action in the comments section because as project managers we think of ourselves as process driven. 

This is true. 

But, if we’re only process driven, we’re likely not doing our best work. Because even though we have processes in place to help guide a project and deliver it effectively, we still have a lot of discretion in our actions — or we should. 

Let’s think about this. If you have a certain amount of experience, I hope that you’ve had the opportunity to make mistakes and have successes. In the course of these experiences, you should have learned how to do things effectively or differently than the standardized process might suggest. 

Here is a dirty secret: In most cases, by the time a process has been established, there might be a better way of doing it that hasn’t had the time to be incorporated into the process yet. 

That’s why discretion is so important. It can save you time, money and trouble on your project. 

Processes don’t have discretion, but people do. 

While these are only three examples—and they’re likely obvious to most of us—I think it is important to hit refresh about the role of project managers from time to time. 

What are other examples of project management being a people business? 

By Christian Bisson, PMP

Machine learning is one of today’s hottest tech topics.

It’s essentially a type of artificial intelligence (AI) in which you give your software the ability to “learn” based on data. For example, you probably notice how YouTube, Netflix, Amazon and many other companies suggests videos or products you should check out. These suggestions are based on your previous online actions, or those of other people deemed “similar” to you.

For some time now I’ve been working on projects that involve this technology. We often have clients who want machine learning even though they do not know if it’s even relevant to them. Since “everyone is doing it,” they want to do it too.

Calibrating a project sponsor’s expectations is often a good idea. While the automated services generated through machine learning may seem magical, getting to that point involves challenges—and a lot of work.

1. It needs quality data.

The machine will learn using the data it has being given—that data is the crucial starting point. The data that’s available is what drives how the machine will evolve and what added value machine learning can bring to your project/product. For example, if you are trying to teach the machine to recognize vehicles on images it scans, and all you can teach it with are images of small cars, you are not set up for success. You need a better variety of images.

The machine’s ability to learn is directly tied to the quality of the data it encounters.

2. It needs lots of data.

Once you have quality data, you need it in high quantities. If you can only provide the machine with the website behaviors of, say, hundreds of users per month, don’t expect it to have enough information to be able to recommend the best products based on user trends. Its sample will be too little to be able to be accurate.

3. It needs to be tested continually.

Once you have the necessary data, the journey is not over. The machine may learn on its own, but it’s learning based on how it was built and with the data it’s being fed. There is always room for improvement.

4. It’s costly.

As amazing as machine learning is, it is not cheap. So keep an eye on your project’s budget. Machine learning experts can command high salaries, and there is a lot of effort involved with researching the best approach—creating the models, training them, testing them, etc. Make sure the ROI is worth it.

Have you had a chance to work on a project involving machine learning? What challenges have you faced?

By Ramiro Rodrigues

We are experiencing a great contemporary paradox: In spite of state-of-the-art gadgets and collaborative communication tools, which should be streamlining and facilitating work, we feel increasingly burdened with more responsibilities and response requirements.

The clearest side effect is the epidemic feeling that we are always short of what we wish we could have read, produced or done.

Of course, the benefits that technology has brought us in recent decades are indisputable. The production of human knowledge has gained stratospheric scale. The world has become "flat"—economies are now deeply integrated, and long distances have been collapsed by hyperconnectivity. But this also means that a good share of the world's population can now compete for the same professional space as you and your company.

Perhaps this is why recurring publications about better management of time and its countless functions become the focus of attention for the most attentive visitors to bookstores.

When everything is urgent, in fact, nothing is. If everything has the same priority, there is no way for anything to stand out. Perhaps this is the central issue behind the stress so many people feel today. Once the urgency of demands is generalized, it becomes difficult to produce high-quality, timely results.

What’s the solution? Planning, planning and ... planning. Only a good deal of planning — structured and strategic — allows corporate and project leadership to stay focused on real priorities and meet the right attention needs of their teams.

For the individual, planning is also a personal survival tool for organizing and balancing work, personal and social demands.

by Lynda Bourne

Knowledge is organic, adaptive and created—it exists in the minds of people. A person’s store of knowledge is built from their life experiences, their observations, and their formal and informal learning. Consequently, what one person knows will be different to what everyone else knows. Some of each person’s knowledge is explicit, meaning they can explain the rules that apply to it. But much is implicit: intuition, gut feelings and other ill-defined but invaluable insights grounded in the person’s experience.

Information is recorded, held in systems and made accessible to people. Good information management systems contain verified information in a useful format. This information is based on data. Because it is written, it is consistent—but it may not be correct. How the data is interpreted to create the information depends on people’s knowledge and perceptions.

Data Is the Starting Point

Data is a set of observations or measurements. If nothing changes in the world, another person can perform the same measurement or observation at another time and gather the same set of data. Data may not be accurate or reliable but it is based on observed facts about something. The potential for error rests in the way the observations or measurements were made.

The Interpretation of Information

Information is organized data. It provides the answer to a question of some kind or resolves an uncertainty.

However, transforming data into information is not automatic; it requires the input of knowledge. Someone has to look at the data and observe patterns that indicate something of significance or make decisions on what is important in a particular context. Information is refined data in a context that is designed to communicate a message to the receiver of the information.

The problem is different people with different knowledge frameworks will interpret the same set of data in different ways. You only need to listen to politicians arguing about the state of the economy to see how different the interpretation of the same set of data can become. The old adage applies, “There are three kinds of lies: lies, damned lies and statistics.”

When I reduce my knowledge to a codified or written format it becomes available to others as information. But I have no way of knowing how you or anyone else will use or change the information I have created.

Information Management Systems

Changing data into information is the first application of knowledge in an information management system. And the journey from data to useful information may need several passes through the information management system. PMI’s A Guide to the Project Management Body of Knowledge (PMBOK® Guide) identifies:

• Work performance data (gathered by someone during the course of doing project work)
• Work performance information (the data processes by discipline experts into basic information)
• Work performance reports (the basic information, selected, compiled and placed in context to be used by stakeholders).

At each step in this flow, a person applies their tacit and explicit knowledge to the information they have received. They then codify their new knowledge to create another piece of information ready for use by others. The problem with this process in isolation is it is asynchronous and based on individual transactions. This is suboptimal and potentially dangerous. 

However, the model of the information management system above is very common and spans global systems, such as Wikipedia down to simple knowledge repositories in project web portals. What’s missing in this type of system is the knowledge management element, which we will look at next time.

An information system on its own will at best simply make useful information available to people. There is no control over how, or if, the information is accessed or used appropriately. In a full knowledge management system, information is the bridge between data and knowledge:

• The raw data represents values attributed to parameters of something.
• Knowledge signifies understanding of real things or abstract concepts.

More on this next time.