Don’t fear the machines: Information worker productivity

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As part of the keynote at ESPC 2015, a little more detail around the vision and functionality in the Delve Analytics area was shown. These are the first forays into organizational analytics in soft measures, such as productivity.Microsoft bought a company, called Volometrix, in September 2015, who have been pioneering analytics in productivity measures and processes, such as sales, across organizations.

I wanted to take a moment to cue up the thinking behind this. One of the first questions people ask when they see the productivity dashboards, for example the amount of time spent in meetings and when people are reading emails, is ‘will my manager see this?’.

For me, this conversation around organizational analytics brings up four areas:

  • What actions can I drive from these productivity measures?
  • How can we ensure these actions are the right ones for our teams and organizations?
  • Digital privacy at work.
  • The future of managing the flood of information, in our personal and work lives, especially as the intertwining of those becomes closer and closer.

Bill Baer Keynote ESPC 2015

Death by Meetings

Digital Helpers

Every organization I have ever consulted with, and implemented collaboration technologies for, complains about their corporate culture…about too many meetings. The agility of startups and small businesses is often attributed to rapid iteration; meetings are literally carried out in minutes, with decisions made and feedback received almost immediately.

But, in larger organizations, we have meetings for status updates, regular standups for projects, meetings for opinions & feedback, meetings for consensus building. Rarely do we position meetings to actually action a decision. It’s almost scary to do this, because we are concerned about the risk of irrevocability, as well as the risk of potential new information that might change the decision.

But too many meetings is a productivity drain. Meeting with internal stakeholders and collaborators is often redundant, and we schedule 30 or 60 mins as convenient blocks. We then spend 5 mins waiting for people to arrive from their last meeting, at which point we deal with any teleconference issues.

More recently, we’ve seen that microstatus applications arose, first in our consumer lives, with Twitter (140 characters is all it takes on a regular basis to establish what a person is thinking about), and then inside organizations, with Yammer and other enterprise collaboration networking systems that provide a similar experience, while actually extending and archiving the conversational experience.

Many organizations, however, fail to make the transition from the meeting culture to using collaboration systems for more productivity. Why is this? I’d challenge that this is partly because of the lack of visibility into the costs. Soft costs are always hard to compute and, most importantly, the hardest to make realistic in your organization.

With the advent of new dashboards to help us visualize how time inside our companies is spent on an organizational, as well as personal, basis, I’m excited about focusing people on having productive conversations in a dedicated time (notice how I’m broadening the definition of meetings).

Peter Drucker famously said ‘that which isn’t measured, isn’t managed’, and now we’ll have some analytics to help us manage the soft costs in our organizations. But I want to be clear about how to action these insights in your organization. Blunt force measures, such as 10% reductions in meetings across an org, or limiting yourself to only 4 hours per work day in meetings, can help with initial awareness in how we are using our time. However, the real trick is realizing that actioning productivity metrics is a lot like your collaboration social journey. The metrics that get you to the first stage are not the same metrics that are useful to progress to later stages.

Effectively, we are talking about changing the culture of your organization. Here’s the rub – as with all things important, what works at someone else’s company may not work for yours. Just as success with adopting a social technology such as Yammer, or Office 365 more generally, actually has little to do with the technology features and functionality and, instead, is all about how the scenarios and use cases in your organization, that drive adoption and engagement, are actually implemented.

Change requires you to become a hacker, if you will. You need to hack your corporate culture to understand how your company works. Inserting productivity tools into your corporate DNA, via effective scenarios and use cases, is critical to adoption and, in this case, actioning the insights into productivity. You’ll need people who are willing to model the new behaviors – whether that’s using Outlook Groups, Yammer, or SharePoint – to show how project team member status reporting and collaboration can be done better, in order to avoid additional meetings. Change always begins with motivated individuals. Looking at your own dashboard can help to understand where to effectively redistribute time.

For sustainable change in productivity in your organization, you must exhibit demonstrable benefits at 3 levels – individual, team, organizational. Doing only one of these is not enough – yet, it’s often the trap I see people fall into.

It’s also really important to define the goals behind these productivity measures. Statistics, and reporting on how many meetings, is not a goal. Reducing the amount of the meetings is also not a goal, it is a tactic to achieving a goal. Your goal is to drive better decision quality for your organization, projects and individual work. Make sure your success metrics are geared around both the quantitative and qualitative in this respect.

Digital Privacy at Work

Death by Meetings

People may be intimated by the idea of being measured in this new way. What does it mean to be tracked in regards to when emails are responded to, when and how meetings happen, what teams talk to other teams. But this benign Big Brother only shows cumulative data to your manager. It rolls up data of teams with 5+ people in them. Only you see your own individual data.

Beyond this, at the workplace, there are always more concerns about making sure employees have the right to opt out at work, which will be true for the Microsoft variations of this technology, at the least.

Digital Helpers

Digital Privacy at Work

Let’s take a moment to talk about the wider experience that we can expect as part of our digital workplaces going forward.

You might have noticed the rise of digital assistants, such as Cortana, for example, which is now built into Windows desktop; and you’re used to having Siri help you with reminders and directions.

During the ESPC 2015 keynote, Bill Baer showed how technology can help remind us of the importance of personal connection as we transition our organizations away from matrices and hierarchical structures, to more network and community driven models, connectivity inside your organization and ongoing networking/relationship building is essential. A tangible facet of this, is reminding you to keep up relationships that could be important, and keeping track of who you might be losing touch with.

ESPC 2015 Machine Learning Microsoft

I want to emphasize that the notion of machine learning and digital assistance, in our work lives, is not to be feared. The Hollywood stereotypes of cyborgs and AI that runs rogue are not how the singularity will occur. Instead, think of these early forays into making your work life better, as an exploration into eventually having a digital companion who works for you, on your behalf, and who actually helps you action activities that are important to your professional life, as well as to your organizational goals.

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