Coming up we take a look at Workplace Analytics that uses the power of Office
365 to provide rich actionable insights into how your organization spends its
time as well as the ways that people network internally and externally and
the effectiveness of collaboration across teams will also share how it works
including how you can correlate Workplace Analytics data with other
business information generate powerful models and best practices to drive
positive business outcomes
Microsoft Mechanics
I'm joined once again by the general manager of
Microsoft Workplace Analytics Ryan Fuller welcome it's great to be back
so I know a lot of people are using MyAnalytics to really get insights as to
how they spend their own time to help improve personal productivity we covered
that a few months back on Microsoft Mechanics but now you and the team are
really delivering insights of the organizational level with something
called Workplace Analytics what's that all about so it's about knowledge
workers right and it's about help helping them do their jobs more
effectively that's tricky right it's tricky to understand what makes a
knowledge worker more effective it's it's hard
unlike in maybe manufacturing where it's how many widgets per hour can somebody
produce knowledge work is much more complex it's hard to understand what
makes a legal team better than a different legal team or how does a
certain product team always deliver on time but a different one doesn't right
and so we think about that as a data problem like lots of people have a lot
of hypotheses about what might be good or bad but very few very little data
exists to solve this problem Office 365 provides us data to do that right when
you think about all the meetings and emails and documents and chats and all
that stuff that sits inside the Office 365 cloud it really is the largest data
set ever created for how people spend time at work so Workplace Analytics is a
product that harnesses the insights that can be pulled from that enables our
customers to create whole new levels of engagement and productivity for their
employees right now I remember a really great example that you gave last show
where you highlighted all the hidden costs of really planning for executive
meetings and that was really spiraling out of control
just for the prep that goes into one of those
and just the visibility to what's actually happening and how much time is
spent can radically change how people operate their business but meeting
productivity like just just reducing the amount of time of meetings is just the
tip of the iceberg we have customers using this in all sorts of different
ways which we'll talk about that drive both engagement and productivity I can
really see how this becomes super compelling for example if your may be
managing a merger and acquisition or other business initiatives and you
really want to see how that progress is going that's right people use this for
M&A as you described to see our organizations actually being absorbed
into the parent and integrating or not we use it a lot of times for sales
productivity we use it for manager quality we use it for transformation
efforts there's all kinds of different ways that this thing gets delivered so
your teams then built all the tools to be able to generate these types of
insights but can we see it in action so of course Workplace Analytics is
really easy to use we make it simple to get started and get value quickly let me
let me show you okay so it's a web-based application so you can get at it from
anywhere within Office 365 start with the home page here where you get a view
into how large of a population you're looking at so in this case the demo is
again 902 employees we've got six months worth of Office 365 data in here and
it's just giving us a couple little stats about about it that says that
those people spent three hundred and forty three thousand hours collaborating
over that six month period so these numbers get get fairly large I've got a
number of different tools that I could go into but where I like to start is
some of these visualizations that we have at the bottom or we've got a
handful of categories that help you kind of get your arms around the data and get
get some quick insight into what you're looking at so I'll start with week in a
life okay so a week in life is just that it allows you to pick any group of
people any team any function geography etc and understand what a typical week
in their life looks like so this team has an average of twenty five point six
hours per week between meetings and email right and I'm twenty three point
four of those hours are during their work days two point two or after hours
and I can begin to look at the breakdown of meetings and email by all those
things you can see views of different organizations within that company that's
right you can see as I scroll down because I've loaded in HR data
I can I can have some good context as to how does the HR function compare to the
marketing function or the sales function etc and I've got all kinds of different
views if I were to scroll down of looking at After Hours or total
collaboration or internal versus external etc now let's have a trendline
over to the right side of each of these metrics I can look at the trend or I can
look at distributions sometimes the overall average doesn't tell the whole
story because some people are really burning really hot and some people are
not and you can you can get a sense of what that distribution looks like so
lots of different things you could look at here instead why don't we take a look
at one of this the next categories maybe I look at this and I say well gosh 16.2
hours in meetings per week that feels like a lot let's look a little bit
deeper at meetings so we have this other view called meetings overview and this
helps to get a sense of meeting quality so first thing out of the gates we have
these few different meeting quality indicators so multitasking that's a big
one how many how often are people just sending lots of the emails during
meetings that they're in they're doing that it's a sign of a low quality need
conflicting hours this is what we mean by that is how often are people double
triple booked during the same time periods and that's hard because you
don't know if you can expect people to actually attend what the nine million
represent yes so the nine million is an aggregation of looking at all these
different quality indicators how much time and time is money is spent in what
looks to be low quality meetings and so nine million dollars in people's time is
going to meetings that appear to be low quality right this can be a good call to
action for people to get an idea of just how big the opportunity might be to dig
into this stuff so that's a lots of different stuff we could look at for
meetings another good category to start with is management and coaching so this
gives you a lot of insight into how managers spend their time with their
teams so let's graph at the top is how many hours do people actually get with
their direct manager present right and you can then you can begin to look at
how much time our manager is spending in one-on-ones with people and how does
that vary by function like a lot of companies will will have a rule that
managers should be spending at least a half hour every two weeks in one-on-ones
near this you can kind of see if that's happening or not right I can be a
positive or negative thing depend on the company that's absolutely right
I mean you can get indications of micromanagement or you can get
indications of awesome mentor ship and training right right networks
in collaboration is another piece here when we talk about networks we talk
about them in context of how many people are you actively interacting with on a
regular basis across the company we have found time and again that top performers
or people who have the best business outcomes have much larger and broader
networks across their companies and so that's highly correlated with with
things like sales positive sales outcomes or positive performance ratings
the opposite is also true as networks shrink to make it smaller and smaller
it's a hot it's a good predictor of attrition and you can totally tell
because maybe your manager can unblock things for you help you out can't
because their networks too small absolutely these are things that really
can contribute to the overall work health of an employee at well said right
and we talked about all that power of the data inside the Office 365 graph
this is the kind of thing that's just really isn't measurable in any other way
but the way the knowledge workers work is through networks and is through
interacting with other people so this allows you to measure it can I create
custom queries of the data absolutely so a lot of the time the visuals that we've
built get you the answer you're looking for when they don't we have the ability
to build your own query and it's extremely flexible I won't go into it in
depth because you can you can get quite fancy with it but I can I could do a
query around people or meetings or groups of people I've got a number of
different templates here so maybe I maybe I want to open up my meetings our
meeting hours by attendee template which has a few metrics already calibrated for
me like meeting hours with at least two attendees or meeting hours with people
in level three and an LP member or different things like that so I can I
can calculate these things in very granular ways and then if I want to I
can add filters to them so maybe I only care about looking at people and
marketing etc and I can run the query and then come back and see all of the
different queries that I've run which are available for me to to download put
in power bi put in some kind of data science package and basically do further
analysis down that's going out put a table of data effectively that you can
visualize with some other tools and I can imagine there's a lot of value in
terms of combining Workplace Analytics with maybe some information that you
collect externally maybe in CRM systems or in HR systems performance ratings
engagement scores those types of things right
that's absolutely right I mean what you saw in their HR data is always part of
it just so you can slice and dice and group and categorize people but it
really comes to life when you put in outcomes data so I could take you
through a real-world example to bring this to life a little bit more so we
worked with one fortune 100 retailer that was working with us and they had a
big problem of low engagement scores high attrition and they just people were
complaining all the time about being burnt out in too many meetings too many
Gmail's etc so they used workplace analytics and they saw a lot of evidence
that people were constantly double-booked people were constantly
multitasking people were doing too much after-hours work but nobody quite
believed that those were the right problems to focus on right the
management team said yeah sure but I need to be double booked because I need
to know what else is happening in any given time slot and then I just decide
at the moment which is the most important thing for me to do which may
be one of your directs might not know if you're going to turn off it's exactly
right meeting yeah so people were really frustrated because I didn't know if the
manager would show up and they had to schedule it three times to get a
decision right so what we did is we took all those Workplace Analytics metrics
and merge it with the employee engagement survey that they had already
run and what came out of it was that the behaviors that we had identified as
problematic like the double-booking and other things really strongly correlated
with disengaged employees so now all of a sudden there was evidence in context
that those set of behaviors were causing this kind of negative 5 and negative
engagement with employees and so they put together a change program they
trained people to actually use my analytics to help people keep score and
after a few months of working to change those behaviors they had some really
impressive results so it's really great in terms of being able to take two
different data sources and pull them together really prove something out it
sounds like a really powerful tool in those types of circumstances but what's
under the hood well how does all this actually work sure yet so we start with
exchange calendar and email metadata coming out of Office 365 we find that
email and calendar alone typically provide around 20 hours of time per week
for each knowledge worker that gets that's even more for managers and more
collaborative functions and we map that with organizational data coming from
many HR systems so things like roles and hierarchies geographies etc and
allows us to aggregate at all those different levels and once that data is
in context we create all this very large library of behavioral metrics that
describe a wide range of behaviors related to productivity engagement
networks time use etc the data very frequently gets combined with other
business data so think think stuff coming from Dynamics CRM or workday for
HR data can also pull in a lot of outcomes data so maybe quota attainment
in a sales organization so you can see what your top performing salespeople do
differently with customers all kinds of different things that you can enrich it
with and what's cool is it's not all just looking at it and deciding how to
interpret it you can do some real data science here so you can you can really
build those models that are highly predictive of outcomes that you're
trying to drive as you said it's such a big data set I know a lot of people
watching are wondering what this means though from a privacy perspective seeing
that it's looking at data they in exchange my calendar etc absolutely and
that's super important first thing on that this is all customer data right
this is your data you have full control over how it gets used and deployed and
what visibility it has across the organization also you should know that
Workplace Analytics only looks at header level metadata so it's not it doesn't
touch content of emails or attachments or any of that that stuff that's often
considered a lot more sensitive and of course we default to the identified data
that's aggregated so kind of like an employee engagement survey you typically
can only see result sets that include at least five people in them etc so you're
never you're not looking at personal identifiable levels of course that's all
entirely up to each customer how they want to configure that but we have a lot
of different toggles that are built to cater to a number of different privacy
scenarios you can also choose which population of employees are part of
whatever analysis you're doing so if you wanted to exclude you know the legal
team or the M&A team or parts of different geographies you can do that as
well so we have a lot of IT professionals
that watch Microsoft Mechanics what I need to do actually light this up if I
was running the IT for my organization so from a tech perspective it's pretty
easy you know we work with you to help
identify the scope of employees the right privacy settings etc then we have
a dedicated team that helps with onboarding and Training analysts on how
to use this then the admin will assign licenses to whichever analysts will have
access to it typically is a small number of analysts especially to start
mechanically very sensitive data but once we do that you know the data
usually right out of the gates you can get at least six months of historical
data so you can you can start to get to real insight very quickly so it's really
compelling in terms of the progress and how we're actually leveraging
behavioural insights for for the workplace but what else are you and the
team focus on what's what's coming next sure yeah I mean so we started with
email and calendar as I said and that gives a very robust signal but of course
we're very excited to add more signals from across Office 365 so Skype and
Yammer and onedrive SharePoint all these different signals that'll make it even
richer we'll also be doing new use cases so it's not just analysts that can do
whatever we'll have it very targeted solutions around things like sales
productivity or collaboration overload etc and then deeper analytics
capabilities making this thing smarter with natural language processing machine
learning all kinds of network analytics etc so where can people go to learn more
about how to start using this well you can request more info about website
analytics at the link below or by contacting your Microsoft representative
so thanks for a great overview and thanks trance again Ryan and of course
keep watching Microsoft Mechanics the latest tech updates across Microsoft
good bye for now
you
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