Happy Friday everyone! Today, we’re discussing human productivity and the efficiency of an experimental four-day work week.
Earlier this year, a firm in New Zealand ran an experiment where it let its employees work four days a week while being paid for five. Employees chose which day of the week to take off, and the experiment resulted in more well-rested employees, better work-life balance, and limited distractions, with no change in productivity despite the shorter work hours.
The article begs the question as to the efficiency of a 40-hour work week. Of course, everyone is different, but this experiment showed that people were able to recognize inefficiencies and correct them to work smarter, not necessarily harder.
It’s vital for us as employees to recognize times that we’re doing quality work and times when we’re not. It’s difficult (maybe even impossible) to be 100% productive, all day, every day; and it’s also essential for us to take breaks. So what’s the perfect balance?
Honestly, there isn’t one universal answer. Everyone works differently, and this experiment ran well because employees had the ability to choose which extra day they took off, allowing them to optimize their time in the office and take well-deserved breaks when they needed it. But besides being bored or feeling sluggish, how do we know when we’re not productive?
Some may be familiar with the term “flow”: in other words, it’s the state of being in the zone, when one is fully immersed in an activity and has full focus and enjoyment in the process. There are, of course, varying stages between boredom and flow, and we often don’t work at a flow state for eight hours a day. But achieving a flow rhythm might reduce the time it takes to complete a task; for example, a task that might take four hours in a non-flow state might take two in flow.
There’s no real answer to achieving flow since everyone works differently. But the experiment of a four-day work week and the results it produced imply that individuals are able to deduce their own inefficiencies and make themselves better. At Steelray, we continually strive for personal betterment, in and out of the workplace, because we believe that the drive to learn and excel is what makes us remarkable people with really cool software.
Do you think you’d excel with a four-day work week? What day would you take off? How can we measure our productivity to know if we’re getting better or worse?
At Steelray, every employee attends a seminar called “Fierce Conversations,” taught by Larry Hart and based on the book by Susan Scott. We hold all these lessons to heart and firmly believe that effective communication is a pillar to great teamwork, which in turn creates excellent products, and is a baseline for our really cool software.
This TED Talk by Celeste Headlee, a radio show host, outlines the problems that prevent us from having meaningful conversations. She puts our conversational issues in a modern-day context where the polarization of our population means that every conversation can devolve into an argument, and avoiding conversations prevents essential discussions and interpersonal connections.
She points to our lack of listening, our inherent need to talk about ourselves, and our inability to ask the right type of questions, among other issues, and maps out a plan for us to overcome these obstacles. Given that we live in a highly technological society, Headlee recognizes that a significant portion of our interactions are online via a screen, not face-to-face, and this is a primary reason as to why our in-person conversation quality has degraded. However, the points she lists to make us better conversationalists apply not only to in-person conversations but online ones as well. We often subconsciously steer exchanges to our personal experiences, both on and offline, and Headlee combats this by forcing us to recognize that experiences are all individual; we very rarely know exactly how other people feel when they undergo something, and realizing this to be a better listener makes a world of difference.
Catch the video below, and maybe learn something new about conversations that can help both your personal and professional lives.
We discovered another great TED Talk, this time by Reshma Saujani, the founder of the non-profit organization Girls Who Code which supports efforts to increase the number of women in computer science. Saujani draws attention to the tough issue of the gender imbalance in the technology industry. She recognizes aspects of our socialization that affect our inclination to take risks and further describes her efforts to encourage risk-taking and the acceptance of imperfection among young girls as a form of women’s empowerment.
Without sounding too much like a sociology lecture you slept through in college, it’s important to recognize that we don’t make our behavioral decisions (including those around our careers) in a vacuum. Some argue that “there are fewer women in STEM because they choose so,” which negates early experiences where we give young boys toy cars and young girls dolls and subsequently teach that technical skills are a boy’s trait. Girls Who Code combats these early lessons with their program and encourages young girls to embrace imperfections so that the future of the tech industry includes a more balanced gender parity. Here at Steelray, we’re all too aware of the gender imbalance and hope to continue to support women in tech.
A hunter was injured when a bear landed on top of him after he shot it on a hilltop. I am not making light of this happening, and I hope the hunter makes a full and quick recovery, but this story is a perfect metaphor for the habit we sometimes have of shooting problems and at the same time accidentally creating bigger ones.
I think they like to call it “unintended consequences,” and I’ve had my share of them.
The only upside to making mountain-sized messes out of mole-sized problems with decisions is when we:
learn from them
figure out how our decision process failed us
train ourselves to spend more thinking time on the potential side effects and future problems.
It’s definitely a process, and one I’m not finished with. When was the last time a bear you shot landed on you?
As of October 1st, 2018, we no longer sell “full” and “maintenance” licenses to our products. We only sell subscriptions.
Prior to October 1st, 2018, we sold our viewer as a perpetual license. On October 1st, 2018, we switched to a subscription model, which means that all new sales are sold as subscriptions.
For Perpetual License Holders
If you are a perpetual license holder, you may continue to use the product perpetually (as the name implies). The only change will be how you are covered under maintenance. Until your maintenance period expires, you are covered under your current maintenance period; nothing changes.
Should you choose to renew maintenance when it expires, you would be switching to a subscription license at that time.
When your maintenance expires, should you choose to not renew maintenance, you may continue to use the product but will not be eligible for technical support and new versions.
We are excited to announce the availability of Steelray Project Analyzer 2018.5, a major release of Analyzer! This is the biggest release of Analyzer in many years.
What’s new in 2018.5?
DoD DCMA EVAS Metrics
Analyzer 2018.5 includes support for all of the latest schedule metrics that DCMA is using on their EVAS schedule assessments.
DCMA 14-Point Enhancements
Analyzer’s DCMA 14 Point Assessment is enhanced as well. With the 2018.5 release, all 14 tests are executed without changing the source schedules, including schedules with master and subproject files.
As always, we include two versions of the report: one which runs strictly according to DCMA guidelines and one that can be customized and configured to suit your needs. The custom report is renamed to “Configurable DCMA Assessment” in this version.
Our Entirely New Project Data Extractor for Microsoft Project
With Microsoft Project files, when you click the Analyze button, the longest part of the processing is extracting the necessary data from Project. When the extraction takes a while, the whole analysis takes a while. There are generally two technologies used for this, and both come with technical baggage (i.e. compromises): accuracy and speed.
Speed + Accuracy
We’ve written a new project data extractor optimized for blazing speed with perfect accuracy, giving you the best of both worlds, and Analyzer is our first product to use this technology. The extractor is called Steelray Project Add-In and (as the name implies) it installs as a very lightweight add-In to Microsoft Project. Once installed, Steelray Project Analyzer connects to the add-in to grab the data it needs, in less time than ever before. But that’s not all it does.
Better Error Handling
Because Analyzer and the Project Add-In can talk to each other, we’re better able to detect when something goes wrong with Project. This allows us to better communicate and handle the issue.
Support for Future Products
Future products that Steelray will build may use Steelray Project Add-In as well, reducing their installation footprint.
Improved User Interface
In 2018.5, we addressed dozens of usability items to make for a better user experience.
Settings Where They Belong
In previous versions, some reports would have a sidebar which would allow you to change settings related to the project or the report. You could only access those settings after running the report, which was clunky. We’ve moved those settings out of the report to where they belong: project settings and report settings.
New Project Settings
There’s a stark difference between the old and new project settings. With the new settings, you make changes in one place and the changes apply wherever used in a report. For Microsoft Project files, there is a new link which allows you to open the project file directly from Analyzer.
New Report Settings
Similarly, we’ve taken settings out of the output of some reports and added them to our enhanced report settings.
Direct Editing of Criteria From the Scorecard
The first generation of Analyzer had a feature where you could edit any criteria on a scorecard with one click; a great shortcut that we missed when it went away in the next version.
We’re happy to announce that it’s back in 2018.5! Simply click on the criteria name and you’ll be in the Criteria Manager with the criteria loaded and ready to edit. An example:
Enhanced Project Sets Make Comparing Schedules a Breeze
We’ve greatly enhanced project sets in Analyzer 2018.5 with a new feature called snapshot sets. Before, to select two or more schedules for a comparison report, you had to load and select them individually. You may have had 12 schedules, one for each reporting period, cluttering up your Projects list.
In 2018.5, a project set has a checkbox setting that tells Analyzer that the list of projects in the set are snapshots of the same schedule — a snapshot set. For reports like Schedule Comparison that required you to select all of the projects to be compared, the process is much easier, Select the snapshot set and you’re good.
Enhanced Connection Diagnostics for Microsoft Project Server, Project Online, and Oracle Primavera P6
We’ve added features to make it much easier to diagnose connection problems with Microsoft Project Server, Project Online, and Oracle Primavera P6. For P6, we check to make sure the necessary permissions are correct after the connection.
Alan begins early by checking his news feed, noting that dock workers in Brazil are threatening to strike in January. He sends an alert to the risk analyst, checking to see if the strike has been accounted for, how the risk would be mitigated, and whether a “Plan B” exists.
In other market news, new oil industry projections indicate a price dip in the coming months. Alan assesses near-term projects and calculates some schedule shifts to take advantage of lower prices before they go back up. He pings the PMs via email and highlights the schedule changes.
Later that morning a PM named Beth checks a Slack feed from Alan; he’s cross- referenced her project data with HR and reports that a key assigned resource has scheduled vacation during a critical activity. He also notes that a small shift in the project path will avoid overtime rates. Beth adjusts accordingly.
Near lunch, Alan reports back to Stephen, who’s looking to update forecasts for the OmniCorp project. Alan has been anonymously polling the participants on activities and projections, and informs Stephen that their sentiments, combined with previous project data and external factors, indicate the project will complete two weeks later than the original projection.
That afternoon, Alan detects an unusual materials charge expensed to the DOT project. The items are appropriate for the job, and the total fits into the budget, but a high one-time cost is an anomaly. He shoots a text message to Purchasing and the PM?might this be a red flag?
Before close of day, Travis, director of sales, has Alan weigh in on a new project proposal, since Alan’s access to almost unlimited data points, coupled with his machine learning capabilities, allow him to eliminate much of the guesswork in cost and timeline estimation. Travis reviews the three project scenarios offered by Alan and feels prepared for tomorrow morning’s sales meeting.
Sound like fantasy?
For the moment, it is. But not as far from reality as you might think.
Some people are hesitant about the role of AI in the future, but we see a landscape of neural nets, algorithms and bots that enable people to reach higher degrees of excellence.
And, as we continue to experience a revolution in AI?in medical diagnosis, driverless cars, stock trading, marketing, business strategy?project management won’t be far behind.
In fact, we’re planning on it.
Steelray is incorporating AI into our flagship products?to continue providing greater depth of knowledge and actionability so our clients know the truth in their data and can do something about it.
Recently a recruiter reached out to me about a three-month Scrum Master role. Was I interested? No, I love my job at Steelray. Did I know of anybody? Well, maybe, but…three months?
A Scrum Master’s core objective is to foster highly aligned, high-performing development teams, which takes time?certainly longer than a few months. Here’s why:
The Team Competency Model
I?d invite you to consider that the specific skill sets of teamwork are acquired through the ?Four Stages of Competence? ? a learning model that applies to teams just as much as individuals:
The team doesn?t understand team skills and doesn?t recognize the deficit.
They don’t understand team skills, but know they need them and want to do something about it.
Conscious competence The team is actively acquiring skills, but it takes a lot of attention and intention to apply them.
The team has had so much practice together that?being?a team has become “second nature.”
It?s been my experience that most teams are Stage Two, some are Stage Three, many (too many) are Stage One, and a rare few make it to Stage Four.
How About You?
Considering the huge benefits of great teamwork, it’s worth taking stock to and looking at your own competencies. Where are you on the model? Not just your developers, but sales, marketing and operations? Even senior management?
The litmus test is pretty simple:
To what degree is everyone on the same page with the work?
To what degree is everyone on the same page with how they work together?