Discussing the Evolving World of Microsoft 365 Analytics w/ Ed Senez

In today’s episode of #O365 Hours, we’re joined by UnlimitedViz Inc. President Ed Senez to discuss how Microsoft 365 analytics have evolved over the years and how they’re being shaken up today. Watch our discussion below or read the full transcript at your convenience!

Guest: Ed Senez, Co-Founder and President of UnlimitedViz Inc. (visit his website here)

Questions Covered:

• What’s currently happening with personal and team analytics within Microsoft 365?
• How can you truly transform your business with these great new technologies like Microsoft Viva?

Transcript

Christian Buckley: Hey, good morning. And thanks for joining this morning’s office hours webcast. My name is Christian Buckley. I am the Microsoft regional director and MVP and the Microsoft go-to-market director for AvePoint, and this office hours broadcast is coming to you every other Wednesday morning at 11:00 AM Eastern. I think that’s right, ed 11:00 AM already providing value. Look at that. Thank you to our guests here. You can subscribe for future news notifications, this show that happens every other Wednesday. If you go to AvePoint or a V E P t.it, I know almost add point there slash oh 3, 6, 5 hours. We’ll share the link there, of course, but I’m joined this morning by ed senators. Who’s the co-founder and president of tie graph and Microsoft partner and ISV. We’ve got a great topic. And so Ed welcome.

Ed Senez: Yes, thank you, Christian. Pleased to be here today and it talks to me about one of my favorite topics, which is analytics.

CB: So let’s jump right into it. The big focus today is on the announcements around Microsoft Viva and specifically insights as part of Viva, which is also kind of an expansion of what’s been going on with my analytics capabilities. So what’s really happening with personal and team analytics inside of Microsoft 365?

ES: Well, I think the direction is really great because currently we kind of have data spread data everywhere and it’s really hard for people to understand which signals they should I pay attention to and what’s important to them. One of the most important things about data is you know, it needs to tell a story. It needs to have a purpose, like what business problem are we trying to solve? So, I think Insights is something that’ll provide focus for that. It kind of comes in three flavors right now, but there are two that are really predominant. One is my analytics insights and for those who have subscribed to it, they may have seen it in their feed and email reminding you that, “Hey, you’re not getting enough sleep.”

ES: And some of those wellbeing things, some markers, you know, the ability to, to coach a person on focus time and things of that nature, right? Looking at people’s calendars and seeing, you know, how much energy are they spending in meetings doing these other various tasks, responding to emails, and then providing some guidance and coaching all to the lens of, of really helping the employee from a wellbeing perspective. So I think Viva really, or Viva insights specifically really starts to drive that home. And, and they’re including other things. So, so the wrapping and things like Headspace, right? So, you know, kind of a meditation app as, as part of that you know, taking breaks prompts, which apparently I need from time to time

CB: Tell people too, that I, so I have when I was, when I used to run more her and but when I go out walking and things, so I have my, my apple watch and, and, and, you know, for those that have an apple watch, they’re aware of this, like, you get the little, the vibrant on your wrist and look down, it says breathe. And I’m just like this jump, this one on. And one of the things that’s happened over the last year, year and a half, and especially with COVID happening, I’m starting to pay attention to those things. I’m like, you don’t, I haven’t stood up in a while. I should stand up, walk around, thankfully I have a dog. So I go and walk, but having that kind of, you know, that kind of, you know, data point and being able to report back and look at, you know, what are my unhealthy practices, because I think that the meeting fatigue screen fatigue is a real thing for people that didn’t think it was a real thing. And then they started working from home like the rest of us and they realized that having some data and being able to go in and monitor and be more self-aware of your own habits and bad habits of how much time you’re sitting and what you’re actually doing with your time is important to your long-term health.

ES: And, and it’s, you know, they they’ve thrown it at even another layer, like the concept of a virtual commute. So, you know, I, I used to have this decompress time for about 20 minutes or so in the car. And, and, you know, by the time you get home, you’ve kind of divorced yourself a little bit from, from that Workday, even though, you know, the portable stress as I like to call it your mobile phone, continuous to T to taunt you, if you will to, to come back to work on a continual basis. But, but, but that those, those types of things are, are really, they’re, they’re using data for good, if you will you know, really making sure that people are starting to pay attention to these things, because as we transformed to this more digital economy, these things become really important. You know, we’ve seen it with social media and people getting consumed by those platforms, you know I think Microsoft’s taken a very healthy position if you will, to, to really, you know, get people subscribed and understanding that well,

CB: That’s how I interpreted the Veeva announcements in general is that, you know, we have, and there’s been an evolution again, going back to kind of our SharePoint routes. And if you look at kind of the evolution of that SharePoint started off being a very dev centric and it pro centric solution. And then as it got you know, the, the technology got better and we got the broader adoption, we had more end-user topics into. Now, you go to an event when we used to have those,

ES: The good old days.

CB: More than half of the audience would be end users and power users, but we get to a point where we have the broad adoption and where we’re not spending our time worrying so much about keeping servers up and lights on. If you have a lot of questions that people ask, it helps highlight, you know, not a clear understanding of what the out-of-the-box capabilities are. You should master the out-of-the-box before you move on to the advanced capabilities, but now people are starting to ask, and this kind of gets to my point around Veeva you know, we, so we have all these great technologies, like what’s next? How do we truly transform our business? And we’ve talked about, we’ve talked about transformation for years. And yet I think most people that thought of transformation as well, just swapping out, upgrading the technology. It’s like, no, the transformation has less to do with the technology and more to do with, you know, the people process, the business processes and then changes. Are we getting the most out of the technology and our processes and our people and doing it in a well-rounded way. Exactly.

ES: And a lot of organizations have con kind of gone to this organizational change management or in, in the Microsoft fear or the adoption change management programs. Microsoft has employed hundreds of customer success managers across the globe to really help organizations through those transformational journeys and, and let them understand, you know, it, you raise a great point, right? SharePoint, we saw it well, I’ve deployed SharePoint, so it’s good. We’re done right. Yammer, same deal, right. W we deployed it, we turned it on and, you know, nobody really used it. And, and, you know, teams was, was going down that same road though with, you know Skype dissolving, if you will, and teams coming in and, and the, the pandemic, you know, certainly the communications channel of, of teams you know, just took off like a rocket you know, as, as you would expect.

ES: But so, so, you know, it’s no longer just turning it on it’s, it’s sitting, you know, it’s the side-by-side with the employees and understanding what business problems they need to solve. And then in structuring your, your environment around that, and, and data can really feed those. Right. So, so let’s say we run a lunch and learn, and, and we have, you know, information going out to employees. Well, we’ll finding out, you know, kind of what’s happened downstream. Do you, did it, did it affect the telemetry? Right. Do people start using the products in the way that we asked them to use it? And if not, do we need to do some course correct. If they are great. And then we also have, I call it the 12 step program, people that fall off the wagon. So, so the, you know, that churn, right?

ES: So people, oh, we started using the program, but we decided not to and being able to identify those earlier in, in the, in the business cycle really gives a good lens to people that are running those organizational change management, because they, they can have the interview and really, you know, get down to the root of the problem. We had a great example, a customer was trying to get off of Skype. And what it turned out was it had nothing to do with internal comms. It was the supply chain on the supply chain was still using Skype. So, so once they discovered what that problem was through the data analytics, they were able to quickly get in there and, and course correct. And, you know, within a very, very short period of time, they, they managed to shut down Skype about four to five months earlier than they had predicted just because they were able to see what was going on organizationally. Well,

CB: That’s a great, great point. Is that, so you’ve, you’ve talked about a couple different things. I mean, we have the personal analytics, like what I’m doing with my day, how I’m spending my time. You have the, you know, the workload-specific analytics, you have the team project analytics, you’ve got the analytics you have. And I, and I know that, that you, as different partners in ISD that provide solutions out there and add point has data as well, that is able to look at, you know, anonymized data across multiple customers and learn things from that as well. But I, I, so I’m interested in, so we’re, we’re talking more and more about data. In fact, Microsoft has made this a major, a major shift. I’m trying to remember how long ago it was six, seven years ago where they, they slowly kind of cleared out the formal, like a lot of the testers, the testing functions, and, and said, well, everybody should be testing to some degree, but they built up around the telemetry, the telemetry and analytics within every product area, every project team, there was somebody that owned the analytics and doing data-driven analysis and development.

CB: So there’s a lot that’s happening. That’s changing, hence the name via evolving, you know, 365 analytics but in the ecosystem. So kind of what are the segments? What are the, the areas of analytics that Microsoft is now formally like focusing on and what should it pros and managers be focused on?

ES: Sure. yeah. Great question. So Viva specifically, with Viva insights, we talked about personal analytics, then there’s another layer of manager analytics. So, so think of a roll-up of information to a managerial position, because candidly employees don’t always do what they’re supposed to do, and that’s why we have managers. So from a well-being perspective you know, re really understanding kind of what’s going on with, with their staff and, and being able to coach and monitor. And if it’s not really, you know, don’t think about it as kind of a big brother at a staff level, it’s more, you know, departmentally, you know, how are things going? Are we, are we trending in the right direction? You know, more, more like C-SAT scores with, with customer satisfaction, right. You know, those types of things that, that drive programs. And, and so maybe it’s, you know, it’s reminders, maybe it’s, you know, let’s have a, let’s have a joint session, et cetera, et cetera.

ES: So all sorts of things that managers do to, to move the needle. And then there’s kind of this concept of advanced tools. So what they’ve done is they’ve basically created a platform if you will, that you can plug other tools into there, there was you know, you can use our, if you’re really a propeller heads, like some of our data scientists get into, into that level of, of analytics and, and doing you know, all sorts of different things, but, you know, a bunch of pre-baked KPIs and so forth, but really trying to get a better handle on, on what’s going on organizationally is really where it’s at. So that I would suggest would be more of the I’ll call it outside of it, type of perspective. Because really we’re, we’re talking about kind of that HR lens on, on the world from an analytics perspective.

ES: And I think that’s really where insights is going with, with the whole announcement and trajectory that they’re going down. But having said that, as I mentioned earlier, data everywhere we also have the, kind of the three pillars beyond the product analytics, which you’ve already mentioned the other three pillars of analytics in the Microsoft ecosystem. There’s, there’s, what’s called the admin center. So if you log in, if you are the administrator, you have the admin center, you can go in and see telemetry data on each one of the workloads kind of how it’s going. That’s really more of an it lens. So, that would be, an IT pro type of lens then there’s usage analytics, which is kind of a, an extract it’s, it’s very call it high level. So, so pretty aggregated data, again, giving you some good telemetry on what’s going on, on workload by workload basis. It does pull in some telemetry around HR information like departments and divisions and so forth. If that’s populated accurately in Azure active directory, which is a whole 30 topic

CB: Partner solutions that have been developed just around that area.

ES: Right. and then finally, there’s the audit logs right in the compliance center w where you can prescriptively go in and, run a search query and pull back those audit level data extracts and pull that back. And, and, and then finally, there’s the, the root of all that, which is the graph and the graph has a plethora of data in it that you can pull in and go in and, and make hay with, if you will, which is candidly what we do. We, we get at that audit level perspective stuff.

CB: So I want to ask this just because I know that I’ve seen several of your requests hit and so your CTO, John White—a fellow MVP—commented within the MVP circles on wanting to see an expansion of the API capabilities. And there’s always those assets that are out there from partners. And a lot of that, you know, for, for customers that are wondering about this you know, that what this visibility is, you know, as, as ISV has providers, that point tie graph the, exactly the same, where we’re being asked by our clients, they want certain capabilities that we go and try and do either if we can’t do out of the box that we try to do within the API APIs, the capabilities, the partner capabilities that Microsoft provides us, but there’s constantly a list of asks that around there. What do you think are the, what, what do you feel are the gaps that are still out there from an analytics telemetry standpoint?

ES: So, you know, SharePoint had their analytics and whatnot, and what were the, the graph was kind of that unifying engine. So, so what’s happening now is we now have kind of this common data platform to right. Things to, so, so no longer are we putting things into other buckets and repositories all, you have to go to the SharePoint administration console to go get that SharePoint data, and then you, you, you know, et cetera, et cetera. So, so what we’re seeing now is a little bit of more homogenous [inaudible] there, there are all sorts of, you know, individual use cases where we could really make that better. But, but, but really that, that’s kind of the w what we’re seeing you know, w what we’re doing is a lot of harmonization across the platforms as well.

ES: So, so even though these, these signals are coming in, if you think about teams, right? So, so teams sounds simple until you start unraveling it. So now I’ve got call data, I’ve got meeting. If we record this meeting, I’ve got a meeting, recording data, that’s going into a one drive. I’ve, I’ve got data around the files that are being shared in teams. So, so that’s another different vector. Then I’ve got teams and channel chat messages, and people responding and liking and so forth. So that’s another set of data and all of that persists in, in kind of different repositories behind the scene. So, so, you know, that, that harmonization of that data set is really kind of you know, the vector, I think we’re traveling down, but we’re certainly not down that road yet.

CB: Yeah. There’s a, one of the other kind of areas or gaps. I mean, so going back to like the, my analytics and I get those, you know, those emails every morning that says, you know, here’s how you’re spending your time. And, and one of the major gaps, and this is this is a little thing, but I work within multiple tenants. I work across multiple cloud environments. And so it doesn’t capture everything. It’s great for all the things that I’m doing within my tenant, within my primary chemo right there. But like, I still have still all of my community activities, the MVP things that I participate in there’s calls every week around product announcements and things that are going on, other things that are in between Yammer and teams and just, you know, online that aren’t picked up and captured in those analytics. So it often will tell me that I have much more free time to collaborate that I actually like, it didn’t feel like I had all that free time. Yeah,

ES: Let’s see my personal calendar. I’m, I’m golden there issue with analytics

CB: As well, because increasingly, I mean, how many companies are out there that only work within one OEM, one ecosystem, like we’re like, we’re a Microsoft shop and that’s all we do. If it doesn’t have Microsoft involved in it, like we don’t touch it kind of thing. The reality is that whether it’s their sales platform, their CRM platform, whether they’re working in other ERP platforms, they’re part of other networks working cross this, and then there’s tools. They may be passionate teams, users, but still I’ll be running the other competing solutions as well. I know it’s shocking that that happened, but you know, it’s, it’s what we don’t talk about openly, but you know, so from the catalytic standpoint, yeah,

ES: That’s a good perspective workplace analytics as example, which is the other so there, there’s a kind of that personal mine analytics and workplace analytics, which is more the manager analytics. Those are key very much on exchange signals. So what they’re doing is they’re looking at calendar, they’re looking at free time, free space and calendar to calibrate that focus, time calculations and so forth. And, and, and then also, you know, how busy, you know, from a send, receive perspective on emails and so forth you know, it’s, it’s, it’s as good as they can do right now with, with the tooling that they have. And, and, and the, the other thing to be cautious of because, you know, one of the big topics was this whole productivity score that got a little bit of a fanfare.

CB: My next question, anyway, but maybe let me ask the question. Yeah, totally. A lot of concerns from parts of the community or individuals within the community about the data that Microsoft was capturing as part of the productivity stores scoring and who actually had access to this. I believe that fundamentally that the people that were complaining the loudest about that understood it, the least yeah. Like how it was being used. Maybe you could kind of enlighten us of, you know, what it was and what it wasn’t.

ES: Yeah. So where Microsoft did a bit of a course correct, was around the anonymization component of it. And, and, and they have on December 1st Jared had, had made a formal announcement that, you know, we’re going to office gate this data. So from a collection perspective, but it’s really important for managers to have those signals, right? Like, so, you know, if your employees are burning out and we can tell that from the data, it’s really important for the manager to understand that and to be able to, to take action on it. So I don’t think Microsoft in any way, shape or form stepped over the line. And, and now they’ve even, you know, with their slight course, correct. They’ve even been more tolerant to, to, to those scenarios where, where people might feel it’s, it’s a little bit too creepy, but, but let’s talk about, you know, the productivity score.

ES: It’s a good attempt. All of these data signals are just that they’re, they’re singles, they’re pointers, they’re, they’re saying, you know, so for example, we do sentiment analysis, right? So, so, so we’re looking at, you know, message signals and so forth. And, and, you know, some customers will come to us and say, well, you know, Hey, this message was scored low, but it’s really high or vice versa. And, and, you know, notoriously help desk score super low. So they deal with, they deal with problems, right? So that’s in the context, but, but it’s more around aggregating the signals and looking for trends and patterns. Right. And, and, and that’s really the important part. These, you know, productivity score is a direction signal, right? So if I’m looking at an income statement or a sheet, I mean, if I, if I go to the financials, right.

ES: And I look at, you know, expenses as the only form of telemetry around how my organization is doing, I would have a completely different context than looking at, oh, well, look at revenue relative to expenses, you know, either good or bad, right. So, so it’s, it’s aggregating these signals and, and making intelligent business decisions. So what we’re saying with organizations and, and, and really the data platforms are really starting to support this. And I think that’s why we’re, we’re starting to hit a real good stride. If you look at tools like Power BI, and Synapse creating data lakes Microsoft snaps, or Azure snaps rather to create a data lake and, you know, put all this data together. I mean, we’re creating repositories and, and areas where we can aggregate and more quickly analyze candidly better than Excel. I mean, you know, a great tool, but, but, you know, tools like power BI lend themselves to bring in all these other data or so.

ES: So even ourselves, we’re finding that, you know, w we provide very distinct business problems that people solve around communications, community management, you know, HR, a little bit of it. So, so we solve those for those problems, but they’re taking these signals and they’re solving for other problems in the organization. So, so when we say productivity score, treat it with a grain of salt, right. I mean, it is productivity in a lens, in a context, if I’m really responsive in email, is that good? Or is that bad? Right. Depends on what my job is. Well, that, that

CB: Was like one of the complaints in this scenario, like if you’ve got, if your manager is going in and say, you know, you were invited, or, or you’re part of you have 57 different chats last week, and you only actively participated in 23 of them,

I mean, the fundamental problem, I think you called it out too, is that it’s about trends to seeing patterns within the data, and it should inform you about what’s going on. And I mean, I’ve had for years, and I’ve spoken about, written about, and said concerned of, of managers, people, managers who manage by spreadsheet without then having conversations. And I always use an example, a former organization operations and support organization, where they looked at the number of tickets closed and judge the value of support personnel by the number of tickets they closed in a month. And so the person that was consistently at the bottom of the list as closing the fewest, usually like three or four tickets in a month where the average was, you know, two or three tickets in an hour by comparison and a manager who was just like global, we need to, obviously this person needs to go.

It was like, wait a second. This person is working on the ugliest problems and is the go-to person with the product team to solve the issue. So from looking at it from data of your analytics, in that myopic view of what you think that means without fully understanding of what’s actually happening, and then using that to inform you to go and find out more about what’s going on with this individual, you know, that’s the mistake that’s made with analytics far too often. And so it’s, it should inform it should help with pattern recognition. But at the end of the day, you know, it’s just, it’s, it’s just a, it’s just another data input to be part of your overall decision. It might be the biggest data input to be part of the decision. But it’s just, it’s one indicator

ES: And, and a plug for well-run companies out there. You know, we we’ve been, what’s been interesting through the last year is understanding how people where, you know, the, the shift in usage data and, and, you know, this time last year, people were saying, you know, are people working and it wasn’t whether or not they, they were working, they were genuinely concerned about the welfare of their staff. I mean, I mean, it was, it was a, it was a very interesting, I think, I think the one thing that’s happened with all of this is, is the, the employees become more human to the, to the corporation because they’re starting to see the kids in the background. And there’s a humanity that has evolved from this. So of all the garbage that has gone on in the last year, I think that’s one thing corporately that that’s really interesting.

And, and then we also got asked around, you know, how are people feeling right? And, you know, we did some sentiment analysis, keyword analysis, things of that nature, and, and were able to kind of derive some signals. And again, correlation isn’t causation, but we were seeing things where there was direct impacts, right? The CEO would make a statement, make a message, land that communication out to the, to the digital water cooler, if you will, and, and, and see the impact to the organization. So I think, you know again, it’s a signal it can be used for, for, for good or bad. But, you know, good managers will do good things, right. And, I think, you know, empowering people with more data is just going to help them on those journeys.

CB: Well, and I’ll put the marketing hat on here for a second, too, to understand how your campaign is landing. Great example of the CEO wants to get out to the, you know, the 10,000 employees of the organization and going and looking at how after an announcement went out there or a, a town hall internally and going and looking at the metrics and seeing how people are consuming, especially if you put, and there’s always good to have like a call to action in any market initiatives internally do the same thing, but to go and look at how many people clicked on this. And so that will then help inform you, like, are we doing a good enough job of getting the word out even internally? And that will get you thinking about, are we using the right tools? Why is it that overwhelmingly in the same time zone, these two different groups in two different cities, one did better than the other different about that what’s happening within the culture of that office, that location or not.

So you can start to have those discussions say, what is, what is the, the, the best way for our organization that we collaborate, that we communicate and we share knowledge and information, and so that you can improve upon those things. I, I I’m of that mindset that it’s like, there’s, there’s, it’s a process of continual improvement. Of course, we’ve, we’ve heard that it’s Deming said we’re constantly optimizing that. So look for opportunities. That’s what analytics affords us. It’s not the answer, the answer to those questions, but it will help you then to go in and refine and improve, improve, iterate, and improve, and constantly fine-tune those systems.

ES: Yeah. Yeah. And if you look at the proceed methodology for adoption change management, organizational change management, it’s all about that. Right. It’s build, measure, and learn those types of programs where we’re continually taking a look at how we, how, how are we landing? How are we, what’s the outcome look like? So,

CB: Yeah. Yeah. You cannot improve something if you’re not measuring it, that’s for sure. Right. Well, ed really appreciate your time today. People want to find out more about you and your company, where do they go?

ES: Ty graft.com is our destination point. Yeah. Pleased to talk to anybody. Who’s more interested in data and analytics. Thanks for having me, Christian.

CB: Thanks again for joining me. And again, once for the people that are watching the show, so we’re back every other Wednesday at 8:00 AM, Pacific 11:00 AM Eastern and it’s so we’re every other week, it starting next month, it’ll be the first and third Wednesdays of each month. But of course you can subscribe if you go to look for AF point out on LinkedIn. And so that’s where the primary broadcast is happening, and you can see this, but you can actually get notifications to when all these shows happen. It’d go and sign up. It’s at a V E P t.it whack oh 3, 6, 5 hours. And so just take a look for add point office hours. You’ll find us well, thanks a lot. And thanks everybody for watching.

Note: This episode originally aired on March 10th, 2021.

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