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GPS Project Management: How Project Creation Studio Plans for the Unknown

The LiquidPlanner Blog - 12 hours 52 min ago
project management

For the past year and a half, Ian MacDuff has been testing a new approach to managing customer work with great success.

As Vice President of Client Engagement at Product Creation Studio (PCS), a Seattle-based design and engineering firm, MacDuff is a seasoned product engineer and team leader. He and his ace team at PCS are responsible for helping aspiring innovators in the technology and healthcare industries develop some of the world’s most recognizable and interesting products. These range from name-brand fitness trackers to amazing machines that help slow the spread of degenerative vision problems. PCS is in the middle of bringing these inventions to life; consequently, the company places a great deal of emphasis on managing each project efficiently and effectively.

project management

Building and Solving for the Unknown

When a client comes to PCS with a new idea for a product or machine, Ian and team are responsible for nurturing the idea and turning it into a working prototype for testing. If successful, they go into full-scale manufacturing. No two product ideas are ever the same. And with every new concept comes a series of engineering, design, user experience and production challenges that his team has never before faced. This uncertainty, which takes many forms—form circuit board, software and user design related roadblocks, to budget related issues—can crush months of work in the blink of an eye. This is especially true if the product design team struggles to quantify and communicate challenges with customers in the moments when they crop up.

A GPS Approach to Project Management

Ian knew it was important to make his customers fully aware of every bump, snag and change throughout the product design lifecycle. As a result, he hit on a simple yet effective way of managing risky project work that takes into account changes, and enables real-time communication with customers. He calls it a GPS approach to project management. This might just be the key to a new way to work in which risk, change and uncertainty are no longer viewed as destructive forces, but things to be embraced as part of the journey.

We sat down with Ian to learn more about how his unique GPS style of project management. In the following video, he tells us how his GPS project management integrates with LiquidPlanner’s


Do you have the tool it takes to manage project uncertainty? Find out! Take our Project Management Health Check, a 9-question multiple-choice assessment of your project management process.  

Take the assessment!

The post GPS Project Management: How Project Creation Studio Plans for the Unknown appeared first on LiquidPlanner.

Categories: Companies

Quote of the Day

Herding Cats - Glen Alleman - 13 hours 53 min ago

The essence of mathematics is to not make simple things complicated, but to make complicated things simple - Stan Gudder 

This notion that estimating is hard, estimates are a waste because they are always wrong, willfully ignores the basic mathematics of making decisions of in presence of uncertainty. The foundation of all decision-making, Probability and Statistics. Without this understanding there can be no credible information provided to the decision makers. 

Categories: Blogs

Next Generation Project Management Software

Next Generation Project Management Software Digitalization and Collaboration

The project and portfolio management (PPM) software market is changing. It is changing so fast that it’s hard for practitioners to keep up with the latest offerings.

This is an edited version of a white paper I wrote with some colleagues for the PMI EMEA Summit in Barcelona. In this article we look at emerging software in the PPM space and discuss how its selection and implementation needs to be done in line with an overarching digital strategy. The objective is to show how this holistic view delivers a greater chance of success and increases buy-in from end users.

First, let’s look at the plethora of tools available to PPM practitioners.

Stick or Twist? Finding A Tool

“Big change driven by digitalisation is prompting PPM leaders to rethink their approaches to IT PPM, including the tools they use to support them,” reports Gartner.

However, at the same time they conclude that many traditional on-premises PPM application vendors are now offering fixed-price and fixed-scope cloud-hosted deployment of their applications with relative success. In other words, the market is confusing: Stick with what you know but host it in the cloud, or move to a new digital offering?

Project management practitioners are looking for new lean and agile project management tools to support their day-to-day work and often seek them outside the tools that their organisations offer them.

In parallel, organisations demand greater project collaboration capabilities to deal with more challenging projects and improved portfolio analytics to better manage portfolio risk but cannot find an all-in-one tool to satisfy all their needs.

Gartner’s analysts conclude that the PMO software marketplace is still emerging and they feel uncomfortable in showing the right way, pushing organisations towards the use of only one project management tool. They suggest practitioners should use tools on a project-by-project basis, avoiding standardisation for now.

But We Need Standard Tools

This clear message is at odds with the reality of working in a project environment and requiring a set of standard tools to do a job.

We observe that there is a persistent request coming directly from project management practitioners: they repeatedly look for alternative tools and ask for information on project management tools tagged as agile, open source, web-based, or cloud.

We wonder whether this desire to investigate and move to new technology comes from this new project management tools market configuration or it is its cause.

Researching What PPM Tools Can Do

Aiming to offer project managers direction and information on how to approach emerging project management tools and to explain what they can do with and expect from each of these tools, Maria Cristina Barbero and Niccolò Siani started a research project under a partnership between The University of Rome “La Sapienza” and the largest Italian IT services firm, Engineering Ingeneria Informatica Spa, which acted through its 100% controlled management-consulting firm, Nexen Business Consultants Spa.

It’s easy to find technical information online about each project management tool, and they are often compared against each other on the basis of technical and contextual aspects.

Comparing Tools Against A Case Study

Instead of taking that approach, the research focused on proving the functionality of tools through the use of a real 7-page case study that required the use of the most relevant project management and team collaboration functionalities. It covered identifying requirements, interconnecting tasks, resources, planned values, actual values, baselines, performance measures, forecast techniques and timesheets.

From an online search and consulting with a group of Italian Project Management Professional (PMP)® credential holders (>400), the research team built a list of around 90 emerging project management and collaborative tools. They were able to try the case study on 48. The research assigned the software product a global rank based on the ability of the tool to support the chosen functionalities.

The image below shows a sample of the research results: Every “Yes” and “No” is the response to one of the 23 questions asked during the case study test and each star and half star is a qualitative weight related to one or more of those questions. You can’t see it particularly well in this picture but I’m sharing it more to demonstrate that the research was thorough.

Tools tested

A tiny snapshot of the analysis that the different software tools went through

I hope that the paper is published somewhere soon so that I can link to it, but at present it is not available online.

The Future: Software Supporting Faster and Iterative Working

So what does that research tell us?

Aside from being an in-depth comparison of project management tools (and you can read my own software reviews here), it highlights the move to online and iterative ways of working.

The research discovered that monolithic IT systems are unfriendly and inflexible. To operate, compete and survive, businesses have “created” bottom-up systems combining several personal preferred, but not integrated, tools.

Apps, clouds, and the availability of free tools are pushing consumers and corporations in the direction of a free digital tools republic where it is no longer effective or appropriate to be chained to a “corporate system” that will never be able to be up-to-date with what happens around us.

Moving from traditional to contemporary approaches to project management activities, companies that adopt a linear, phase-by-phase, project management style will probably decline in favour of faster, more iterative and lighter approaches that are driven more by results than processes.

This also implies a change in the adoption of project management tools: worldwide, project managers will probably need to manage a diversity of software tools, with different deployment styles and maturity of use, because single-platform convergence will be difficult to achieve. Integrating traditional tools with emerging ones is going to be the norm.

Integrating It All Together

The key elements and requirements which drive the configuration of an integrated Project Management Information System are:

  • enterprise tools
  • a people culture
  • existing contracts and agreements
  • the desired level of monitoring and controlling.

As project managers championing new software we’ll need to incorporate all of these if any new tool is going to be effective in the enterprise.

Challenges Of Working in a Digital Environment

We work in a digital environment, but we are not ‘digital’.

That’s why we need a strategy to implement technology and a holistic view, taking into account those points mentioned above. Because the way in which people choose to use the tools we offer them cannot be taken for granted.

The way in which people choose to use the tools we offer them cannot be taken for granted.
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The implementation strategy requires having a plan with the final objectives defined. It also means considering the change management activities to support our digitalisation project as communication, processes, and training are critical for success.

Implementation Issues

Sometimes this implementation strategy doesn’t happen as planned (or isn’t planned at all).

We add digitalised applications to the existing situation without a defined improvement path.

We are attracted to the latest cool application, with the potential to jeopardise the software environment.

This could be a reaction to old structured and inflexible systems but pushing an agenda of continuous innovation without a tangible, declared objective could be even worse.

A simple solution is a digitalisation strategy (simple to say, if not to actually get done in practice). Defining the final objectives and benefits expected allows companies to be flexible regarding what they want to achieve. Flexibility in a defined direction is important in the digital space because things are moving so quickly.

A strategic direction will also help the change management effort as after the definition of the direction and the benefits, you can shape the implementation path to take into account the existing environment.

Integrating Project Management Information Systems in an Existing Environment

So let’s talk about the existing environment.

The existing environment includes the employees that must be involved in the process, but also refers to existing digital applications that must be integrated or terminated.

Old digital tools could be worth keeping in some form, so don’t automatically assume that they are a problem.

We’ve seen that massive centralised PPM systems are not the trend of the future and so we should expect that as project managers we’ll use many applications, hopefully wisely integrated.

For example, legacy applications that employees find user-friendly could be improved and used to minimise the organisational stress of a too wide digital-change.

Digital Does Not Mean Efficient

What we shouldn’t forget is that business could be very digital but at the same time not efficient.

For example, if the accounting system is not integrated with the project management system, that demonstrates a disconnection from the model in use to select our initiatives through portfolio management processes that utilise metrics and data from both.

It’s rework to rekey the data into both systems. That’s not efficient, even if both systems are ‘digital’.

In other words, without digitalisation it is very difficult to operate effectively in the economic market, but digitalisation doesn’t automatically mean integration and unqualified success. That takes work and a proper understanding of how people and systems work together.

This continuous digital evolution inside and outside our organisations, is a digital storm that must be controlled with a flexible digital strategy managed by a digital strategic team that, in the coming years, will supervise the merging of new and old tools with the aim of creating a fully integrated and holistic PPM approach.


About the Authors:

Elizabeth Harrin (you know me) is the author of several project management books, including Collaboration Tools for Project Managers (PMI, 2016). She writes the blog and regularly reviews emerging software tools online.

Luca Romano has more than 20 years of international experience in business consulting, project management, portfolio management, organization, operations management, and training. He is a senior manager in Nexen Business Consultants as part of the Engineering group. He is a professor of international project management and operations management at the European School of Economics, a professor of project management at MiNE Master–Cattolica/Berkeley Universities, and an assistant chair at the Engineering School of Roma Tre University in two courses: Organization and Project Management.

Maria Cristina Barbero, PMP, PMI-ACP, SMC® has been the Director of the BU Change and IT Strategy of Nexen Business Consultants, the consulting company of Engineering Group, since 2005. She graduated in Mathematics and with an MBA in Global Management. She started her career as a software developer and is now an experienced consultant in organizational project management, especially dealing with IT organizations and software projects. She teaches project management at University of Padova and has been a PMI volunteer since 2007. She is one of the six members worldwide of the PMI Standards Member Advisory Group.

Pin It Next Generation Software for Project Management

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Categories: Blogs

The business case is implicit in what we do

Ron Rosenhead's Project Management Blog - Sun, 09/25/2016 - 15:36

Not my words but the words of a client.  She is a senior executive asking for some support. Below is the substance of the conversation starting with what do you mean by that?

Client: Well, because of the nature of the business, it’s already within what we do

Ron Rosenhead (RR): Would you mind if I questioned that?

Client: Well….yes …OK

RR: The business case is the justification for the existence of the project on the basis of its benefits to the business or stakeholders. It looks at the financial viability of the project as well as the risk. Does that make sense?

Client: Sure

RR: So, this project, what is the business case? Give me some real benefits of running with it.

Client: (After a pause) Well, ….my hesitation shows we really do not have a business case. But if pushed I would say the real benefits are …….

RR: How common is that among the projects you know about i.e. no business case or one that is not really a true business case?

Client: I would say very few have business cases. That’s my view though.

RR: That’s not a problem. I am after asking you.

Would it be fair to say that the company is running with a wide range of projects and some of these do not fit with the overall strategy of the business?

Client: Well….in my area…well I guess and it is a guess, there are some that are what you would call ‘nice to haves’ rather than ‘must haves’.

RR: OK, thank you for being honest. What do you want to do about this?

Client: Let’s start with this project. We need to develop a business case and I will get the project manager in here, brief him and get one developed this week.

RR: What about the wider picture within your department? What are you going do about all of the projects underway?

Not THIS type of business case...but this!

Not THIS type of business case…but this!

We went on to discuss a wide range of aspects including:

  • resource allocation – are some staff allocated to projects that in actual fact should never have been started
  • risk management – that the number of projects within the business was a risk. I queried whether they had enough staff to deliver them all
  • skill issues – some staff have received project management training other have not. No project sponsor training has ever been organised
  • benefits management – the very loose definition of business benefits within their own projects or the complete lack of any benefits

This client realised that there were simply too many projects, some should never have been started and some had no links to the overall strategy.

What about your company?


Picture: courtesy of


Related Posts:
Categories: Blogs

Where Are We Going, Doesn't Much Matter It Seems

Herding Cats - Glen Alleman - Sat, 09/24/2016 - 17:15

Chesire Cat“Would you tell me, please, which way I ought to go from here?”
“That depends a good deal on where you want to get to,” said the Cat.
“I don’t much care where–” said Alice.
“Then it doesn’t matter which way you go,” said the Cat.
“–so long as I get SOMEWHERE,” Alice added as an explanation.
“Oh, you’re sure to do that,” said the Cat, “if you only walk long enough.”

(Alice’s Adventures in Wonderland, Chapter 6)

When we hear

The idea behind the #NoEstimates approach to software development isn't to eliminate estimates but, rather, to explore other ways to solve problems without specifically asking, 'How long will it take?'

We first need to ask by what principle of decision making in the presence of uncertainty, what kind of business project has no interest in how long will it take? The answer seems to be a de minimis project. 

Because in the real world not Wonderland with Unicorns, those paying have some sense of where they want to go, how much they are willing to pay, how long they are willing to wait to get there, and what value will be produced by their investment. De Minimis projects have no concern for those answers.

And those spending that customers money appear not very interested in applying known solutions, instead are answering with the Cheshire Cat's words, since the No Estimates advocates appear to live in Wonderland.

For those interested in learning how to produce credible Estimates and make decisions in the presence of uncertainty, here's some starting places that have served me well:

  • How to Measure Anything, Douglas Hubbard.
  • The Flaw of Averages - Why We Underestimate Risk in the Face of Uncertainty, Sam L. Savage.
  • Forecasting and Simulating Software Development Projects: Effective Modeling of Kanban and Scrum Projects Using Monte Carlo Simulation, Troy Magennis.
  • Decision Analysis for Management Judgement, Paul Goodwin and George Wright.

There are many dozens of other books, and 100's of papers describing how to make estimates in the presence of uncertainty. 

After you do some reading and you hear someone say, estimates are hard, estimates are guesses, estimates are always wrong. estimates are a waste, we can decide with estimates, you'll know they didn't read any of these, haven't a clue what they're talking about, and just making things up as the go. Just like the cat

Related articles Flaw of Averages The Reason We Plan, Schedule, Measure, and Correct Essential Reading List for Managing Other People's Money The Flaw of Empirical Data Used to Make Decisions About the Future Making Decisions In The Presence of Uncertainty Decision Making in the Presence of Uncertainty Why Guessing is not Estimating and Estimating is not Guessing IT Risk Management
Categories: Blogs

Team flow: how to make productivity contagious

Asana Blog - Sat, 09/24/2016 - 03:21
Team flow

Team flow

It’s generally agreed upon that the employees who are the happiest and the most productive have one thing in common: they frequently achieve flow. Flow is when we are so focused and involved in our work, we lose track of time. Sometimes we even forget to take breaks—that’s how “in the zone” we are. Flow is when we’re accessing our best ideas, seeing creative solutions to problems, and getting a lot done. We’re probably also enjoying ourselves!

“Flow” was discovered by a Hungarian research psychologist, Mihaly Csikszentmihalyi, who is the Distinguished Professor of Psychology and Management at Claremont Graduate University. In his 1994 book, Flow: The Psychology of Optimal Experience, he wrote, “the overwhelming proportion of optimal experiences are reported to occur within sequences of activities that are goal-directed and bound by rules—activities that require the investment of psychic energy… Often hours seem to pass by in minutes; in general, most people report that time seems to pass much faster.”

Flow is contagious

“Flow” is even more intriguing is when it becomes a group activity. The phrase “emotional contagion” is used to describe “catching” someone else’s mood. “Flow contagion” occurs when people are able to feed off of one another’s focus.

Csikszentmihalyi wrote, “Surgeons say that during a difficult operation they have the sensation that the entire operating team is a single organism, moved by the same purpose; they describe it as a ‘ballet’ in which the individual is subordinated to the group performance, and all involved share in a feeling of harmony and power.”

“Flow contagion” occurs when people are able to feed off of one another’s focus.Tweet Talking about flow

Lou Leone, a leadership coach who frequently advises startup leaders, says that managers can have a conversation with their teams about what “flow” is, exactly. “By making everyone aware of what the ideal environment is for flow, teams are more likely to be able to experience it more often,” he says.

Caroline Webb, a former McKinsey and Company partner and the author of How to Have a Good Day, says it’s important to find the right language to effectively communicate the concept to your team. “For some, it may help to replace the word ‘flow’ with a more directly descriptive term like ‘deep work’ or ‘total focus,’” says Webb.

What’s also important, and channels the original research on flow conducted by Csikszentmihalyi, is that team members have engaging projects and activities on their plates that invite flow consciousness.

Says Webb, “Managers can encourage their colleagues to seek out activities that play to their personal strengths. First off, that might mean having a conversation with people about their real personal strengths, in companies where that’s not part of the regular dialogue. Then, they can encourage their colleagues to craft a new project to play to those talents.”

Alternately, says Webb, after having these conversations about the strengths and skills their team members most enjoy using, managers can encourage their teams to apply their strengths more fully and deliberately to work that’s already on their plates. 

Creating a “flow contagion” strategy

Managers can encourage their teams to consider what systems each individual could put into place to help themselves get in the zone. Leone says that to invite flow, there could be “an individual routine that each member goes through at the same time to help create a state to foster flow.” The routine could be as simple as someone having his favorite coconut water on hand, or suiting up in her favorite power blazer (or hoodie).

Also, if one observes a routine when working to invite a state of flow, that coconut water or that blazer could start to serve as a “positive prime,” triggering the brain to enter a state of flow.

Managers should then help team members integrate their flow routines. “It can be very helpful to agree to a shared ‘zone’ for that deep work. I know that my book publisher designates Fridays as a ‘no meeting zone’ to create more space for people to do deep work,” says Webb.

Webb recommends that managers set a schedule for their teams to try to get into the zone at the same time for a specific window at a certain time and day. “It sets a norm that it’s OK to put on your headphones, close the door and dive deep into something,” Webb says.

When a team experiences flow collectively, they’re able to feed off of one another’s energy.Tweet In the zone, together

While it’s commonly understood that someone wearing headphones doesn’t welcome interruption at that time, when team members are in “team flow,” communicating with others during deep work periods is okay.

“When a team is in flow, it should be easy for an individual who is in flow to break out, help another teammate, and then go right back into his or her individual flow. The flow is occurring both individually and at the team level,” says Leone.

The difference between an individual being in a state of flow and a team being in a state of flow is analogous to the difference between independence and interdependence. When a team experiences flow collectively, they’re able to feed off of one another’s energy. The advantage of the entire team aiming for periods of flow is that individuals who are in the zone aren’t threatened by distractions or others’ requests: everyone is in a co-active state of high productivity.

When teams optimize their time by moving into periods of high focus and productivity together, they end up working like a beautifully synchronized crew team. They probably move about as quickly, too.

Categories: Companies

Primavera P6 Activity Calendars Don’t Match WBS Calendar

primavera p6 wbs calendar differentAsk Plan Academy. Primavera P6 is a great scheduling tool, but I hear from people who struggle with P6's Calendars alot. Here's another Ask Plan Academy question about WBS bars and Calendars from Tom, a project scheduler: "In Primavera P6, the Calendar on the WBS lines is different than the calendars that I'm on seeing on each activity. What gives? How do I fix this problem?" Yes. This is confusing. It's confusing when you see that the
Categories: Blogs

Kanban Training: Essential for Success?

LeanKit Blog - Fri, 09/23/2016 - 16:58

Does your team need Kanban training in order to be successful? No, but training can put you on the right track. Learn the benefits of Kanban training.

The post Kanban Training: Essential for Success? appeared first on Blog | LeanKit.

Categories: Companies

Software Review: Vizzlo [2016]

Vizzlo Software Review General Information

Name: Vizzlo

Vendor: Vizzlo

Hosting options: Web only

Cost and plans: Free plan (includes Vizzlo branding on your images), Premium Plan at $11 per month, plus options for businesses that include sharing images between teams from $15 per month

Languages: English

How Software Reviews Happen

This is how the software review process normally goes for me.

Software company: We’ve got a really cool product we’d like you to review.

Me: Oh?

Software company: It does 1000 things and will take you hours to investigate and review thoroughly, but it’s really good.

Me: Will I actually use it in my daily life afterwards?

Me (answering Me): No. I’m happy with the tools I have thanks.

Software company: So will you review it?

Me: Meh. Maybe.

It started the same with Vizzlo: “Dear Elizabeth, we love your blog, please review our software.”

But then I looked at it. And bought it.

That’s only happened once before, with Apollo (which I actually don’t use any more).

Goodbye Mediocre Business Graphics

As regular readers will know, I have two jobs: I’m a copywriter, speaker and author here at and I work as a salaried project manager as well.

I’ve used Vizzlo to create graphics for both roles.

Vizzlo has over 75 template graphics for you to choose from, covering everything from Venn diagrams to milestone charts, timelines and process diagrams.

It also has Gantt charts and waterfall diagrams but I haven’t used those yet. I’m not going to move away from my trusted project management tools for project schedules but I can see why you might want a pretty Gantt chart mocked up in 5 minutes.

Here’s a picture that took even less time that that (shush, don’t tell anyone. I’d rather you all thought I spent hours creating bespoke graphics).

Example of Vizzlo Graphic

Creating Your First Vizzard

Why they had to call them Vizzards and not ‘graphics’ or something that actually made sense, I don’t know. But the library is full of Vizzards (i.e. templates) and that’s where you start.

Vizzlo Graphics Options

Choose what you want to create. It’s not an unlimited choice – you can’t start from a blank sheet and add icons to make your own – but there’s enough stuff in there to create pretty slides for presentations and project communications.

Let’s create a rhombus milestone plan. Once I’ve chosen it from the Market and hit create, up pops my edit screen.

Vizzlo Rhombus Chart

This is what you can see if you have a paid-for account, so if you go for a free account you won’t get all the options to customise the colours.

It’s really easy to add more units to whatever template you are using. What I have found though is that the size of the page is fixed. As you add more boxes, rhombi or whatever, the amount of words you can fit in each of them gets smaller. So you do have to choose your template carefully.

Change the titles and descriptions, edit the theme if you like, decide if you want the points numbered or not and you’re done.

Vizzlo Milestone Plan

Hit save and the graphic is stored in your Documents tab so you can go back and edit it if you need to. This is a really useful feature to have – something that is missing from apps like Picmonkey.

Benefits of Vizzlo
  • It’s fast.
  • It’s structured.
  • The user interface is clean and easy – no learning curve.
  • You can store you documents to edit later – essential if you do have milestone charts in there that need to be edited for your next presentation.
  • It’s not expensive, given the amount of time it saves me.
Limitations of Vizzlo

The thing that I found the most disappointing is the selection of default templates. The Vizzards in the marketplace look beautiful with nice greens and blues. This isn’t a default style.

I can’t imagine using the Dark or Gradient themes in any professional presentation. The Blueish theme is also pretty bad, unless your company colour is royal blue.

The only one I felt comfortable using was the Light theme and that’s mainly the reason I upgraded to a paid account, so I had more control over the colours, and also could take off the Vizzlo branding which is important (in my opinion) for professional documents presented internally.

In summary…

I love Vizzlo at the moment and I’m happy to have paid for a year’s access. I think I am going to get a lot of use out of it. I’m averaging a couple of graphics a week at the moment – not hundreds but enough to feel like it is helping add to my communications without adding a huge burden of trying to align elements in PowerPoint or start from scratch in Picmonkey.

I would be interested in what’s going to happen this time next year. Will I still be using it? Will there be something better? At the time of writing Vizzlo is in the early alpha phase so it could be developed into something awesome and even in the short while I have been using it I have seen more complicated Vizzards be added.

It’s certainly something to check out if you create visual images for your project communications.

*Update* Literally days after I wrote this the company released new themes, nearly all of which are usable in a professional context, so yay!

Vizzlo Software Review Pin It

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Categories: Blogs

Business Dysfunction, Malfunction and Strategy

Herding Cats - Glen Alleman - Thu, 09/22/2016 - 20:03

Mike Cottmeyer posted

This is an interesting article that misses the point of what's going on. Companies have too much management because they are poorly architected and not organized around value producing assets. When you don't have sufficient encapsulation, you end up with too much orchestration. Management is not the problem. It's a symptom of the problem. Firing, or redeploying managers, without fixing the underlying organizational issues will fail cause you to faster and harder. The solution is to refactor the organizational architecture, increasing encapsulation, and then redeploy managers as you are able to reduce the need for them.

The root cause of this dysfunction is the lack of line of sight traceability for Why the firm is in business to how the firm fulfills the strategy needed to deliver on that WHY.

Here's one way that has been shown over the years to connect the dots between Why and How and critically importantly, how the projectize the work efforts needed to implement the strategy.

Notes on balanced scorecard from Glen Alleman With Balanced Scorecard concepts from this briefing, go read Execution: The Discipline of Getting Things Done, then you'll have a foundation for correcting and even avoid what Mike talks about Related articles Architecture -Center ERP Systems in the Manufacturing Domain IT Risk Management Why Guessing is not Estimating and Estimating is not Guessing Deadlines Always Matter
Categories: Blogs

Partner Success = People, Process, and Technology Integration

Tasktop Blog - Thu, 09/22/2016 - 17:35

To succeed in the software industry, you have to build, sell, and support your software better than others. Throw in a partner ecosystem and you have to ensure that all your partners have the same ability; at least to the extent that they can sell and support the product1. This increases the complexity of the organization but also enables the organization to scale, and increases the overall value of the product.

As the partner manager for EMEA, one of the biggest challenges is not only to keep updated with the latest technologies, but also to know how we are doing in the eyes of our partners. Thus, it was delightful to win the “Best ISV partner 2016” award from Tricentis, one of our Testing/QA technology partners.


Left image: Tricentis’ Franz Fuchsberger and Alan Ota (left and right, respectively) presenting the Best ISV partner award to Dr. Tuuli Bell from Tasktop (middle) at Tricentis Accelerate 2016. Right image: At the same conference, Adrian Jones, Tasktop VP Sales EMEA, shared his wisdom. Watch a video of his presentation about DevOps success and integration at

The title of this post “people, process, and technology” is a commonly referenced starting point for any analysis or improvement project in the service management industry. However it also applies to successful partnerships in the software space; ensuring that we work together whether it’s new people joining the implementation team, changes in the sales operation process, or developing new ways to leverage the integrated technologies.

Hans Peter Bech, Jelena Galkina, Emma Crabtree, Preben Damgaard: Building Successful Partner Channels: in the Software Industry, TBK Publishing, 2015.


Categories: Companies

8 Best Practices for Prioritizing Project Work for Your Team

The LiquidPlanner Blog - Thu, 09/22/2016 - 17:27
prioritize project work

Prioritizing project work is a challenge for project teams across many industries. While shifting priorities are a natural part of working life, when you don’t prioritize work you can lay havoc to all your team’s projects and initiatives, and even drain team morale.

prioritize project work

Effective prioritization is as much an art as a science. Here are some best practices for prioritizing work for your project team.

1. Make the Project Schedule Visible to Everyone

Running a project team without using a schedule that’s accessible by everyone is a sure-fire way to set your team up for problems. At some point during a project an executive is likely to make a demand that shifts priorities; or, another team’s work is delayed and that has a ripple effect. This new information doesn’t always disperse itself through the entire team, so you have some individuals working on either a shelved task, or yesterday’s priority.

To keep team members updated on their top priorities every day, use a collaborative project and work management tool that lets everyone from individuals to managers to stakeholders have unlimited visibility into the project schedule and all the associated work in progress.

2. Create a Project Backlog

A great way to prioritize team work is to use the project backlog concept from Agile software development. This lets you capture all of your project tasks before you assign priorities to team members. A great way to put this into play, is to use a work management application that includes a folder for your backlog tasks; or, create your own team folder for backlog tasks yourself.

The project backlog concept can be an important tool to show management all of the work that falls under your team’s responsibility that still needs prioritization.

3. Manage Your Team for the Long and Short Game

I once worked for a manager prone to distraction because he was eager to please his managers and show off to his office crush. To display his industriousness, he responded to incoming work requests by pulling the whole team off ongoing work, despite looming deadlines. If he used a project schedule, he would have realized the team was almost evenly spread between longer term projects and short-term work.

Instead of always defaulting to all hands on deck, this manager could have pulled a team member or two from a project where the new priority wouldn’t compromise the whole team’s deadlines. Managing the short and the long game means effectively prioritizing work on longer ongoing projects, as well as the shorter projects that will occur as well.

4. Know Your Business

The manager from the preceding point #3 had a few more shortcomings: He didn’t understand the subject matter, the technology or the processes underlying his team’s projects. Further complicating matters, he would take work management advice from his office crush, someone who knew even less than he did about the team’s work. This combination really messed with the team’s priorities.

When you know your business, you’re in a much better position to prioritize project work. Here are some ways to learn more about your business, and continually stay on top of trends:

  • Read widely in your field and industry.
  • Pursue continuing education.
  • Ask each team member about the work being done.
  • Learn what matters to your manager, other stakeholders and customers.

When you know the business, and understand how your team’s work fits in to a larger vision, you’ll be able to set the right priorities for your team.

5. Give Project Tasks a Finish Date

Most organizations are kept in business by meeting deadlines and delivery dates, especially manufacturing companies. When team members receive a task that has a deadline attached to it, they’re much more inclined to start that over another one without a finish date. That’s why best laid project plans always include deadlines or finish dates assigned to every task that makes up the project.  The dates alone can help both management and team members prioritize their work. And if priorities still aren’t clear, or there are too many overlapping dates, this spurs conversations about project priority and what work most matters to move forward.

6. Add Buffers: Account for Uncertainty in Your Schedule

You can be sure that something unexpected will occur during the course of your project—a stakeholder request, a delay, resource issue, you name it. When you work in an environment that’s especially notorious for shifting priorities, some project or team managers will build in a buffer of time to plans. For example, a buffer could be a few hours or days added to a review period. You can remove a few hours from the buffer without disrupting project delivery while still meeting new priorities.

Another way to do this is to use a project management tool that accounts for uncertainty by letting you make ranged estimates for work and consider best case/worst case scenarios, rather than a single-point deadline. This way the buffer is automatically built in to the schedule.

7. Learn How to Predict Incoming Priority Shifts

I once had a project lead who was able to create a little oasis of productivity and rationality in what was otherwise a dysfunctional organization. His secret was that he could tell when a priority might shift before it even happened.

He did this by becoming a student of project failure and dysfunction; he could identify the exact project milestones where the process might break down and priorities would change.

He took a proactive stance: Whenever he saw a possibility where a priority would shift, he adjusted team priorities and schedules accordingly. The lesson I learned was to always try to be aware of all parts of the project, not just my own responsibilities. The issues that affect your team’s priorities usually begin upstream.

8. Draw the Line between Urgent and Important Tasks

Managing the long and short game also means balancing priorities on urgent and important tasks, and knowing when to draw the line.

Drawing the line means:

  • Urgent tasks get immediate attention based on business-critical factors like winning new business and keeping existing business. Getting a check from a customer as the result is often the big decider with urgent tasks for many organizations.
  • Important tasks receive ongoing attention, and are only put on hold when an urgent task truly requires all hands on deck. Important tasks support the projects that together keep the business going, so don’t undervalue their priorities.

When a new work request comes in, ask yourself if it falls into Urgent or Important task buckets. If you’re not sure, use it as an opportunity to have a conversation clarifier around what the larger goal is, and structure your priorities from there. You don’t want to be the person always saying “yes” to an incoming “urgent task.” Because as we all know, not every piece of work is business-critical—no matter how much it might feel like it is.

Be a Proactive Manager of Priorities

Your team wants to be working on the right priorities! They want to know that the work they’re doing is the right work to move the business forward, no matter how often priorities change. As a project manager or team leader, it’s up to you to stay proactive in directing the undulations of the team’s priorities. Make sure your team has the tools and schedule access they need to know what their priorities are; get to know what your team is doing, what individuals need, and what your stakeholders are expecting from you.

If you manage priorities effectively, not only will you increase productivity, you’ll improve your team’s morale. Everyone wants to do work that really makes a difference!

Are your team’s priorities supported by a solid project management process? Find out! Take our Project Management Health Check, a 9-question multiple-choice assessment of your project management process.  

Take the assessment!

The post 8 Best Practices for Prioritizing Project Work for Your Team appeared first on LiquidPlanner.

Categories: Companies

No member of staff should ever feel like they did…

Ron Rosenhead's Project Management Blog - Thu, 09/22/2016 - 11:03

Both of the sales assistants were incredibly embarrassed. One of them must have apologised around 8 times alone. My wife and I could see her discomfort and we could certainly feel it.

But why were she and her colleague put into such a position and by such a prominent high street store?

I needed to get some new clothes. I had a 20% off voucher and headed to the store with my wife.

I found just what I wanted and went to pay. An in store card had to be obtained to obtain the discount.  Here comes the problem; neither of the members of staff had been trained to link the card to the computer system. They tried very hard but could not do what was necessary.

No project manager or team member should feel embarrassed if you train them properly

No project manager or team member should feel embarrassed if you train them properly

Sadly, there was no one available who was trained to do this!

We felt very sorry for both staff members who tried very hard to sort out the issue but were clearly not able to.

We wasted around 15 minutes of our time and they wasted the same trying to sort this out.

A lot of the work I do is with new project managers. I have often heard them say on project management courses these words (or similar):

‘I wish I had done this course some 6 months earlier.’

They have expressed to me their frustration at having to deliver a project with no overall approach. They were having to deal with risk issues they had not expected or a plan that omitted a key task or maybe they failed to include the project report to a senior manager as no one told them they had to.

They had not been trained. I guess until this incident with the sales assistants I had not realised the real issues they faced, especially their feelings.

To repeat, no member of staff should ever be put into a situation where they feel embarrassed or at a loss for knowledge. Managers should manage effectively and ensure staff have the required knowledge and skills through a combination of training, coaching and on the job practice. Yes, all staff have a responsibility. However the manager must start the process off.


Picture courtesy of Google Images by Claire Murray



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Categories: Blogs

Manage Your Workshops with Workshop Butler

NOOP.NL - Jurgen Appelo - Wed, 09/21/2016 - 21:00
Workshop Butler

I am officially an investor now.

I have always been an investor. After all, I have always invested my time, energy, and resources in ideas that seemed to make sense to me. That’s what entrepreneurs do!

But now, I have taken my Lean Funding approach to invest in someone else’s idea. Actually, it is my idea as well, but I have no time to pursue it. I happily let Sergey Kotlov take our idea in a new direction and grow it into something fantastic.

Whether you organize workshops for managers, developers, marketers, or yoga students, there are always things you need to do for your classes, particularly when you work with more than one trainer:

  • Manage your trainers and their licenses
  • Publish the event schedule on your website
  • Provide info about topics, locations, and trainers
  • Process registrations online
  • Send notifications to participants
  • Process feedback and evaluations
  • Produce certificates of completion
  • and much more

Not surprisingly, Workshop Butler started its life as the back-end system for all Management 3.0 workshops worldwide. It has served the brand well, with more than 100 facilitators using the system on a regular basis.

Now, Workshop Butler has evolved to power other brands as well, including Collaboration Superpowers, Lean Change Management, and more.

If you offer classes under a brand name, with multiple trainers, various topics, and different locations, I suggest you check out the Workshop Butler public beta and get Sergey Kotlov to show you around the system.

It would make me happy. {8-)

The post Manage Your Workshops with Workshop Butler appeared first on NOOP.NL.

Categories: Blogs

GirlsGuideToPM: My Top 10 Articles of All Time

In case you’ve only just stumbled across this blog, this year I’m celebrating 10 years of blogging about project management.

I thought it was time to look back and see what the stand-out articles were over the years. Here are the top 10 articles year by year.


I reported on the state of the Gypsy Moth IV project: the restoration of a historic yacht. At the time, the project was desperately short of cash.

Gipsy Moth IV did make her planned round-the-world journey and continues to operate today, taking groups on breath-taking sea journeys.


In September 2007 I published a guide to why projects fail. It touched on the classic reasons for project failures – poor sponsorship and so on – but also focused on how we define failure on projects. It’s still something that I don’t think we spend enough time doing. Key success criteria, and, in contrast, what failure looks like, are still areas of projects where miscommunication leads to unhappy stakeholders, even if you deliver what you said you would.


In 2008 I was living and working in Paris, France, which involved several office moves. I wrote about what every project manager needs as her office survival kit – things that travelled with me from office to office (and not work-related paperwork, either).

By the way, I refer to La Défense as crummy in this article, but by the time I left I had come to appreciate the arch, the architecture and the little cafés hidden between the offices. And also the massive shopping centre.


I declared 2009 the year of the Office Goddess and I wrote a series of posts about how to excel at work.

This was one of my favourites: about Pareto and the 80/20 rule and how some stuff just needs to get done.

That was back in the days before I had brand guidelines for how my blog should look.


My project alphabet was a popular post of 2010 and inspired Derek Huether to write a book about zombie project management*.

(Don’t know what that is? Here’s the scoop on zombie projects and how to kill them).


One of this year’s most-read articles was 5 Project Management Apps You’ve Never Heard Of.

Checking in today with the companies mentioned, three are still going, one looks like it has been taken over by Easy Projects and the last one’s website is no longer working. For more up-to-date software reviews, see my complete list here.


I hadn’t realised it, but What Makes A Good Project Manager was actually the top post of 2012. I re-ran the article just recently, which shows I still rate it as a good piece of writing too. (I didn’t write it, by the way.)


Google Analytics tells me that 6 Things I Didn’t Know About Being a PM was the top post of 2013.

I hadn’t read this one for a while (probably since I first published it) and it was good to look back. I still believe that all this is true.


This piece on 10 Killer Interview Questions for Project Managers is probably one of the all-time top articles. It’s been reprinted elsewhere and still gets read today.

Back then I did have responsibility for hiring (I don’t have a PM team working for me today) so I was speaking from my own experiences.


This was the year I wrote the definitive guide to project management success criteria. This is probably the most-read article I have ever written, and I’ve tried to expand it over the last 12 months to make it even more useful.

It was also one of my first articles to include a free thing. Right now it’s got a list of  done-for-you 20 sample success criteria so that you don’t have to think them up yourself.


We’re now in the 11th year, and the most popular article this year has been my guide to the project management conferences happening during 2016.

I had no idea that this would be such an important article for people, and it’s something I’ll do next year as well. I think it’s good to summarise the largest and best events to help you make decisions about what to spend your money on. There’s a lot of choice, and the list necessarily reflects the ones I feel I can best talk knowledgeably about (i.e. the ones I have been to and experienced the quality first-hand).

If you think I have missed any, drop me a line and let me know what’s happening near you for next year’s version.

Here’s to the next 10 years!

* This article contains affiliate links at no cost to you.

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Categories: Blogs

Marketing teams execute great ideas #withAsana

Asana Blog - Tue, 09/20/2016 - 18:27

Ads, content, events, campaigns, analytics, and optimizations—today’s marketers manage a wide range of different project types. It’s a tough balancing act to constantly churn out cool stuff that’s innovative and catchy while keeping up with all the stakeholders, deliverables, and channels involved to get great work out the door. We got the inside scoop on how three great marketing teams are tracking their essential workflows in Asana to execute flawlessly and get great results.   

Tribeca Film Festival plans and runs events #withAsana


Behind every successful event is a dedicated team keeping track of a ton of moving pieces. And if you’re organizing a citywide, weeklong festival for millions of people, we can only imagine the level of coordination required. Tribeca Film Festival, which recently celebrated its 15th year, is an annual celebration of both the international film community and of New York City. Each year, the festival takes over theaters across the city for screenings and lines the streets with posters and marquees celebrating the festival’s arrival. There’s a lot of creative work that goes in and out of the festival—and all of it is tracked in Asana. Asana helps the creative team execute on every tiny detail to put on a successful event.

Learn how to use Asana to plan everything before, during, and after your event to make it a success in the Asana Guide.  

Oru Kayak launches new products #withAsana



Oru Kayak is in the exploration business; their expertly crafted products are designed to get paddlers of all levels outside and onto the water. As it turns out, launching an Oru Kayak into the water is significantly easier than launching a brand new product into the market. Product launches require an enormous amount of coordination between teams. At Oru, designers make decisions on screws and combings while the marketing team coordinates a go-to-market strategy for their new boat. To make sure everything is progressing on time, Oru uses Asana for planning and tracking each step leading up to a launch.

Get step-by-step instructions for creating a roadmap that will keep your teams on track for launch day  in the Asana Guide.

Autodesk manages editorial calendars #withAsana



If you start looking around, almost everything that’s been built around us—from every bridge you cross to every building you see—seems to have been touched by an Autodesk product. Autodesk serves customers in architecture, engineering, construction, manufacturing, media, and entertainment and they cover emerging topics in each of these industries in their digital publication Line/Shape/Space. Content marketing is a critical component of their marketing strategy; the team consists of writers, editors, designers, and freelancers pushing out new pieces of content three to four times a week. The Line/Shape/Space team tracks their editorial calendar in Asana to streamline the process from ideation to publication.

Learn how to use Asana to build and manage your team’s editorial calendar in the Asana Guide.

Categories: Companies

Forgotten Questions of Change

Insights You Can Use - Esther Derby - Tue, 09/20/2016 - 16:30

I’ve been thinking about and observing organizational change for a very long time.

It seems to me that –in their enthusiasm for efficiency, planning, “managing” change– people often overlook some critical questions.

A handful of questions that could lead to more effective action, but seldom get asked:

  • What is working well now, that we can learn from?
  • What is valuable about the past that is worth preserving?
  • What do we want to /not/ change?
  • Who benefits from the way things are now?
  • Who will lose (status, identity, meaning, jobs…) based on the proposed new way?
  • How will this change disrupt the informal networks that are essential to getting work done?
  • How will this change ripple through the organization, touching the people and groups indirectly effected?
  • What holds the current pattern in place?
  • How can we dampen this change, if it goes the wrong direction?
  • What is the smallest thing we can do to learn more about this proposed course of action?
  • What subtle things might we discern that tell us this change is going in the right direction…or the wrong one?
  • What is the time frame in which we expect to notice the effects of our efforts?

What questions would you add?

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Categories: Blogs

A gentle introduction to random forests using R

Eight to Late - Kailash Await - Tue, 09/20/2016 - 12:44

In a previous post, I described how decision tree algorithms work and demonstrated their use via the rpart library in R. Decision trees work by splitting a dataset recursively. That is, subsets arising from a split are further split until a predetermined termination criterion is reached.  At each step, a split is made based on the independent variable that results in the largest possible reduction in heterogeneity of the dependent  variable.

(Note:  readers unfamiliar with decision trees may want to read that post before proceeding)

The main drawback of decision trees is that they are prone to overfitting.   The  reason for this is that trees, if grown deep, are able to fit  all kinds of variations in the data, including noise. Although it is possible to address this partially by pruning, the result often remains less than satisfactory. This is because makes a locally optimal choice at each split without any regard to whether the choice made is the best one overall.  A poor split made in the initial stages can thus doom the model, a problem that cannot be fixed by post-hoc pruning.

In this post I describe random forests, a tree-based algorithm that addresses the above shortcoming of decision trees. I’ll first describe the intuition behind the algorithm via an analogy and then do a demo using the R randomForest library.

Motivating random forests

One of the reasons for the popularity of decision trees is that they reflect the way humans make decisions: by weighing up options at each stage and choosing the best one available.  The analogy is particularly useful because it also suggests how decision trees can be improved.

One of the lifelines in the game show, Who Wants to be A Millionaire, is “Ask The Audience” wherein a contestant can ask the audience to vote on the answer to a question.  The rationale here is that the majority response from a large number of independent decision makers is more likely to yield a correct answer than one from a randomly chosen person.  There are two factors at play here:

  1. People have different experiences and will therefore draw upon different “data” to answer the question.
  2. People have different knowledge bases and preferences and will therefore draw upon different “variables” to make their choices at each stage in their decision process.

Taking a cue from the above, it seems reasonable to build many decision trees using:

  1. Different sets of training data.
  2. Randomly selected subsets of variables at each split of every decision tree.

Predictions can then made by taking the majority vote over all trees (for classification problems) or averaging results over all trees (for regression problems).  This is essentially how the random forest algorithm works.

The net effect of the two strategies is to reduce overfitting by a) averaging over trees created from different samples of the dataset and b) decreasing the likelihood of a small set of strong predictors dominating the splits.  The price paid is reduced interpretability as well as increased computational complexity. But then, there is no such thing as a free lunch.

The mechanics of the algorithm

Although we will not delve into the mathematical details of the algorithm, it is important to understand how two points made above are implemented in the algorithm.

Bootstrap aggregating… and a (rather cool) error estimate

A key feature of the algorithm is the use of multiple datasets for training individual decision trees.  This is done via a neat statistical trick called bootstrap aggregating (also called bagging).

Here’s how bagging works:

Assume you have a dataset of size N.  From this you create a sample (i.e. a subset) of size n (n less than or equal to N) by choosing n data points randomly with replacement.  “Randomly” means every point in the dataset is equally likely to be chosen and   “with replacement” means that a specific data point can appear more than once in the subset. Do this M times to create M equally-sized samples of size n each.  It can be shown that this procedure, which statisticians call bootstrapping, is legit when samples are created from large datasets – that is, when N is large.

Because a bagged sample is created by selection with replacement, there will generally be some points that are not selected.  In fact, it can be shown that, on the average, each sample will use about two-thirds of the available data points. This gives us a clever way to estimate the error as part of the process of model building.

Here’s how:

For every data point, obtain predictions for trees in which the point was out of bag. From the result mentioned above, this will yield approximately M/3 predictions per data point (because a third of the data points are out of bag).  Take the majority vote of these M/3 predictions as the predicted value for the data point. One can do this for the entire dataset. From these out of bag predictions for the whole dataset, we can estimate the overall error by computing a classification error (Count of correct predictions divided by N) for classification problems or the root mean squared error for regression problems.  This means there is no need to have a separate test data set, which is kind of cool.  However, if you have enough data, it is worth holding out some data for use as an independent test set. This is what we’ll do in the demo later.

Using subsets of predictor variables

Although bagging reduces overfitting somewhat, it does not address the issue completely. The reason is that in most datasets a small number of predictors tend to dominate the others.  These predictors tend to be selected in early splits and thus influence the shapes and sizes of a significant fraction of trees in the forest.  That is, strong predictors enhance correlations between trees which tends to come in the way of variance reduction.

A simple way to get around this problem is to use a random subset of variables at each split. This avoids over-representation of dominant variables and thus creates a more diverse forest. This is precisely what the random forest algorithm does.

Random forests in R

In what follows, I use the famous Glass dataset from the mlbench library.  The dataset has 214 data points of six types of glass  with varying metal oxide content and refractive indexes. I’ll first build a decision tree model based on the data using the rpart library (recursive partitioning) that I covered in an earlier article and then use then show how one can build a random forest model using the randomForest library. The rationale behind this is to compare the two models – single decision tree vs random forest. In the interests of space,  I won’t explain details of the rpart here as  I’ve covered it at length in the previous article. However, for completeness, I’ll list the demo code for it before getting into random forests.

Decision trees using rpart

Here’s the code listing for building a decision tree using rpart on the Glass dataset (please see my previous article for a full explanation of each step). Note that I have not used pruning as there is little benefit to be gained from it (Exercise for the reader: try this for yourself!).

#set working directory if needed (modify path as needed) setwd(“C:/Users/Kailash/Documents/rf”) #load required libraries – rpart for classification and regression trees library(rpart) #mlbench for Glass dataset library(mlbench) #load Glass data(“Glass”) #set seed to ensure reproducible results set.seed(42) #split into training and test sets Glass[,”train”] <- ifelse(runif(nrow(Glass))<0.8,1,0) #separate training and test sets trainGlass <- Glass[Glass$train==1,] testGlass <- Glass[Glass$train==0,] #get column index of train flag trainColNum <- grep(“train”,names(trainGlass)) #remove train flag column from train and test sets trainGlass <- trainGlass[,-trainColNum] testGlass <- testGlass[,-trainColNum] #get column index of predicted variable in dataset typeColNum <- grep(“Type”,names(Glass)) #build model rpart_model <- rpart(Type ~.,data = trainGlass, method=”class”) #plot tree plot(rpart_model);text(rpart_model) #…and the moment of reckoning rpart_predict <- predict(rpart_model,testGlass[,-typeColNum],type=”class”) mean(rpart_predict==testGlass$Type) [1] 0.6744186

Now, we know that decision tree algorithms tend to display high variance so the hit rate from any one tree is likely to be misleading. To address this we’ll generate a bunch of trees using different training sets (via random sampling) and calculate an average hit rate and spread (or standard deviation).

#function to do multiple runs multiple_runs <- function(train_fraction,n,dataset){ fraction_correct <- rep(NA,n) set.seed(42) for (i in 1:n){ dataset[,”train”] <- ifelse(runif(nrow(dataset))<0.8,1,0) trainColNum <- grep(“train”,names(dataset)) typeColNum <- grep(“Type”,names(dataset)) trainset <- dataset[dataset$train==1,-trainColNum] testset <- dataset[dataset$train==0,-trainColNum] rpart_model <- rpart(Type~.,data = trainset, method=”class”) rpart_test_predict <- predict(rpart_model,testset[,-typeColNum],type=”class”) fraction_correct[i] <- mean(rpart_test_predict==testset$Type) } return(fraction_correct) } #50 runs, no pruning n_runs <- multiple_runs(0.8,50,Glass) mean(n_runs) [1] 0.6874315 sd(n_runs) [1] 0.0530809

The decision tree algorithm gets it right about 69% of the time with a variation of about 5%. The variation isn’t too bad here, but the accuracy has hardly improved at all (Exercise for the reader: why?). Let’s see if we can do better using random forests.

Random forests

As discussed earlier, a random forest algorithm works by averaging over multiple trees using bootstrapped samples. Also, it reduces the correlation between trees by splitting on a random subset of predictors at each node in tree construction. The key parameters for randomForest algorithm are the number of trees (ntree) and the number of variables to be considered for splitting (mtry).  The algorithm sets a default of 500 for ntree and sets mtry to one-third the total number of predictors for classification problems and square root of the the number of predictors for regression.  These defaults can be overridden by explicitly providing values for these variables.

The preliminary stuff – the creation of training and test datasets etc. – is much the same as for decision trees but I’ll list the code for completeness.

#load required library – randomForest library(randomForest) #mlbench for Glass dataset – load if not already loaded #library(mlbench) #load Glass data(“Glass”) #set seed to ensure reproducible results set.seed(42) #split into training and test sets Glass[,”train”] <- ifelse(runif(nrow(Glass))<0.8,1,0) #separate training and test sets trainGlass <- Glass[Glass$train==1,] testGlass <- Glass[Glass$train==0,] #get column index of train flag trainColNum <- grep(“train”,names(trainGlass)) #remove train flag column from train and test sets trainGlass <- trainGlass[,-trainColNum] testGlass <- testGlass[,-trainColNum] #get column index of predicted variable in dataset typeColNum <- grep(“Type”,names(Glass)) #build model Glass.rf <- randomForest(Type ~.,data = trainGlass, importance=TRUE, xtest=testGlass[,-typeColNum],ntree=1000) #Get summary info Glass.rf Call:
randomForest(formula = Type ~ ., data = trainGlass, importance = TRUE, xtest = testGlass[, -typeColNum], ntree = 1001) Type of random forest: classification Number of trees: 1000 No. of variables tried at each split: 3 OOB estimate of error rate: 23.98% Confusion matrix: 1 2 3 5 6 7 class.error 1 40 7 2 0 0 0 0.1836735 2 8 49 1 2 2 1 0.2222222 3 6 3 6 0 0 0 0.6000000 5 0 1 0 11 0 1 0.1538462 6 1 2 0 1 6 0 0.5000000 7 1 2 0 1 0 21 0.1600000

The first thing to note is the out of bag error estimate is ~ 24%.  Equivalently the hit rate is 76%, which is better than the 69% for decision trees. Secondly, you’ll note that the algorithm does a terrible job identifying type 3 and 6 glasses correctly. This could possibly be improved by a technique called boosting, which works by  iteratively improving poor predictions made in earlier stages. I plan to look at boosting in a future post, but if you’re curious, check out the gbm package in R.

Finally, for completeness, let’s see how the test set does:

#accuracy for test set mean(Glass.rf$test$predicted==testGlass$Type) [1] 0.8372093 #confusion matrix table(Glass.rf$test$predicted,testGlass$Type) 1 2 3 5 6 7 1 19 2 0 0 0 0 2 1 9 1 0 0 0 3 1 1 1 0 0 0 5 0 1 0 0 0 0 6 0 0 0 0 3 0 7 0 0 0 0 0 4

The test accuracy is better than the out of bag accuracy and there are some differences in the class errors as well. However, overall the two compare quite well and are significantly better than the results of the decision tree algorithm.

Variable importance

Random forest algorithms also give measures of variable importance. Computation of these is enabled by setting  importance, a boolean parameter, to TRUE. The algorithm computes two measures of variable importance: mean decrease in Gini and mean decrease in accuracy. Brief explanations of these follow.

Mean decrease in Gini

When determining splits in individual trees, the algorithm looks for the largest class (in terms of population) and attempts to isolate it first. If this is not possible, it tries to do the best it can, always focusing on isolating the largest remaining class in every split.This is called the Gini splitting rule (see this article for a good explanation of the rule).

The “goodness of split” is measured by the Gini Impurity, I_{G}. For a set containing K categories this is given by:

I_{G} = \sum_{i=1}^{K} f_{i}(1-f_{i})

where f_{i} is the fraction of the set that belongs to the ith category. Clearly, I_{G}  is 0 when the set is homogeneous or pure (1 class only) and is maximum when classes are equiprobable (for example, in a two class set the maximum occurs when f_{1} and f_{2} are 0.5). At each stage the algorithm chooses to split on the predictor that leads to the largest decrease in I_{G}. The algorithm tracks this decrease for each predictor for all splits and all trees in the forest. The average is reported  as the mean decrease in Gini.

Mean decrease in accuracy

The mean decrease in accuracy is calculated using the out of bag data points for each tree. The procedure goes as follows: when a particular tree is grown, the out of bag points are passed down the tree and the prediction accuracy (based on all out of bag points) recorded . The predictors are then randomly permuted and the out of bag prediction accuracy recalculated. The decrease in accuracy for a given predictor is the difference between the accuracy of the original (unpermuted) tree and the those obtained from the permuted trees in which the predictor was excluded. As in the previous case, the decrease in accuracy for each predictor can be computed and tracked as the algorithm progresses.  These can then be averaged by predictor to yield a mean decrease in accuracy.

Variable importance plot

From the above, it would seem that the mean decrease in accuracy is a more global measure as it uses fully constructed trees in contrast to the Gini measure which is based on individual splits. In practice, however, there could be other reasons for choosing one over the other…but that is neither here nor there, if you set importance to TRUE, you’ll get both. The numerical measures of importance are returned in the randomForest object (Glass.rf in our case), but I won’t list them here. Instead, I’ll just print out the variable importance plots for the two measures as these give a good visual overview of the relative importance of variables. The code is a simple one-liner:

#variable importance plot varImpPlot(Glass.rf)

The plot is shown in Figure 1 below.

 Variable importance plots

Figure 1: Variable importance plots

In this case the two measures are pretty consistent so it doesn’t really matter which one you choose.

Wrapping up

Random forests are an example of a general class of techniques called ensemble methods. These techniques are based on the principle that averaging over a large number of not-so-good models  yields a more reliable prediction than a single model. This is true only if models in the group are independent of  each other, which is precisely what bootstrap aggregation and predictor subsetting are intended to achieve.

Although  considerably more complex than decision trees, the logic behind random forests is not hard to understand. Indeed, the intuitiveness of the algorithm together with its ease of use and accuracy have made it very popular in the machine learning community.

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