{PODCAST} In-Ear Insights: Technology and Change Management

In week’s episode of In-Ear Insights, Katie and Chris talk shop about change management when it comes to technology. When a new piece of software is introduced, how do you handle the changes? Using the rollout of Google Analytics 4 as an example, what are the steps we must take to ensure as smooth a rollout of new technology as feasible? Tune in to learn more about technology and change management!

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{PODCAST} In-Ear Insights: Technology and Change Management

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Christopher Penn 0:02
This is In-Ear Insights, the Trust Insights podcast.

In this week’s In-Ear Insights, we are continuing our discussions about change management this week talking about technology and to a lesser degree process.

Last week, we talked about those the most difficult part, which are those squishy humans that are involved in change management.

And this is a topic that I think is super relevant right now, because there’s a big set of changes that people are having to do right now that a lot of folks are expressing a lot of hesitation about.

And that is the transition, for example, from Google Analytics, three, the older version to the brand, well, relatively brand new Google Analytics forge came out in October.

And there’s a bunch of big changes, a lot of things have changed in it.

That’s a totally different piece of software, there’s a totally different way of working with it and stuff.

So Katie, when we think about change management, we think about something as big as you’re moving to Google Analytics for, what should people be thinking about in order to not make it a complete and total disaster, which, for some organizations, it very well could be?

Katie Robbert 1:07
Well, for anyone who listens to the podcast frequently, they’ve probably turned it into a drinking game.

And so I would say they know the first thing I’m going to say is you have to have a plan.

You have to have a plan.

And so what does that mean, though? Like us, everybody sits down in like a room for six days straight to map it out? Probably not, you probably don’t need that level of a plan.

But you do need some kind of conversation or more, more likely some kind of documentation to say, on one side, this is what we currently have.

On the other side, this is what we’re going to have.

So what happens in the middle.

And it’s that middle part that people tend to not pay attention to, because it’s like, Okay, well, I just, I started using the system over here, I’m using this system over here.

So on the fifth of the month, I’m just going to shut off the first system.

And we’re going to start using the new system.

And that is definitely part of the plan.

But it doesn’t answer the question of what happens to all of the old data.

What was the communication around people who, who were relying on all of the old data? Does the new system, do a one to one match of all of the different variables and data points that you were looking at? And so those are the kinds of things that you want to factor into that kind of transition planning when you’re moving from system to system or introducing a new system of what am I getting out of this? What can I do? What can’t I do? What are the limitations? And what is my plan to supplement those data limitations? If it’s something that I was relying on before with an older system, have you you’ve been through software transitions before? Chris, what are some of the pitfalls that you’ve run into?

Christopher Penn 2:53
I mean, there’s so many, but I think it actually would be useful.

Let’s use us as the example and Google Analytics three to Google Analytics four, because it’s a transition that everyone will have to make at some point, whether it’s now a year, five years down the road, you will have to do it, because at some point, Google will simply turn the old thing off.

There definitely are things that are missing, right.

So we know, for example, that all the old events, category, action, label and value all that goes away, we know that the framework of how the software makes decisions, like everything’s an event now, there’s no more page users, no more users.

It’s all just events, and big things, things that we rely on as a business and for our clients, like attribution models have gone away.

So there’s a lot of big gaps right now.

So how would how are we going to make this transition? Katie, how, what do we do? Obviously, we know there’s some things like attribution models, kind of important, so that we don’t want to lose, what, what would you say? Is our plan for making that move? And how do you know so that folks listening can go Oh, yeah, I have that problem, too.

Katie Robbert 4:06
Well, let’s start very tactically, one of the first things that you said is that the way in which Google Analytics for is capturing events is different.

And so if you start with just that, so you start to look at your current Google Analytics three, and what decisions you’re making from event data.

And so it’s literally you know, am I looking at pageviews button clicks, you know, what goal conversions by looking at those kinds of things.

list out all of the data points that are on theoretically, ideally on your KPI map.

If you’ve done a KPI map, then you should have all of these things listed out and your KPI map is essentially all of the metrics feed up to your business goals.

So the contract to see if you’re making progress.

And so what you probably want to do with Google Analytics for is redo that KPI map with The data points that Google Analytics four has, as opposed to three, and then you can start to do the comparison of, am I getting all of the same information? Or are there gaps and things that I need to rethink about? It might be just rethinking the context.

And so you could be getting the same type of data, just it looks a little bit different, but you’re still answering the same question.

And so that’s where I would start is figuring out what are my business goals? And then what am I getting from each system in order to help me understand if I’m making progress on those business goals? And you may find that with, you know, Google Analytics three, you haven’t done this exercise in a while.

And the way that you’re thinking about it has probably changed as well, you know, and so that way, as you have both systems running in parallel, you can be focusing on the same types of data in each system to see what the differences are having two different sets of data is not the worst thing in the world doesn’t exactly have to match one to one.

But you have to be able to answer the question being asked, regardless of if it’s Google Analytics through your Google Linux for so that’s where I would start is, can I answer the question being asked with this new system? And if not, how do I get to those answers with, you know, supplemental data or something else?

Christopher Penn 6:19
Right.

So in ga four, for example, one of the things that is missing is there are no attribution models, there’s not even last, last touch, right? It’s, it’s just not in there.

I don’t know whether Google’s ever plans on putting it back or not, I would imagine somebody would probably have asked for that.

But the data is available.

So one of the things that you could do is write your own code, to build your own attribution model on the raw data that you’re collecting in the BigQuery database.

That is feasible for us as a company, it’s less feasible if you don’t have developers on staff that you can dedicate towards that test.

So in that case, you’ve got a big feature, that you’re very reliant, should be very reliant on nga 30.

If you’re doing attribution modeling, and it’s gone, with no likely replacement, and ga for so when we’re talking about change management, how do I navigate? Hey, this thing’s out? Like I know, for us, it’s gonna be right, the software, build it? What if you don’t have me on staff?

Katie Robbert 7:28
Then you hire Trust Insights? Easy, I don’t even know why we’re talking about it.

Um, no, if in a very realistic scenario, which is where a majority of a lot of these marketing agencies are going to find themselves is they don’t have that replacement.

And so there are other tools that do some kind of attribution modeling, a lot of the CRM is have their own built in.

And so really, the first question you have to ask is, what am I doing with this attribution model? Am I using it to resource? Am I using it to budget? Am I using it to, you know, do the following five things? And if you’re not, it’s probably not the worst thing in the world if you don’t have that feature moving forward.

But if you’re heavily heavily reliant, like we are on figuring out, you know, okay, where do we put our money this month, we only have so much money, we need to put more money towards social media, or we need to put more money toward email, then we need to figure out that alternative plan.

And so, you know, obviously, we want what we’re getting from the attribution modeling data now.

But if you don’t have that, it may be time to rethink what you can do with Google Analytics data.

So you know, how, what channels are bringing in the most traffic or what channels are bringing in, you know, the most goals, it’s not a one to one as an attribution, but it’s at least a starting place to work with the data that you have.

I mean, obviously, if you can, if you have the time to dedicate to learn how to, you know, code, your own model, great, do that, but I’m guessing the majority of companies will not have that capability.

Christopher Penn 9:12
Right.

So let’s say a company is reliant on the attribution modeling built in, and they don’t have a feasible replacement right away.

What How do you plan for that change? Do you just hold on for as long as possible and hope that you know, a third party writes the software and you can you can buy from the what, what do you do when you run into a breaking change to your technology, that there isn’t an obvious easy solution for other than, you know, again, praying and wait.

Katie Robbert 9:47
So this is where that transition planning comes into place.

So definitely just like holding out until the very end until they cut you off is not the best solution.

So what you should start to do is take a look at what is available through The new system that you’ll be using, in this example, Google Analytics four, and see how much of that question you can answer with the data that you have available, and so it may not look exactly the same.

But can you get close? And so it will take a lot of exploratory data analysis to figure out, can we even get close to figuring out? Can we answer the question of resourcing and budgeting with the existing data? And if not, you know, then you should start looking at, you know, third parties and consultancies for support, but really digging in and, you know, bringing in, you know, people from a bunch of different teams, because if you think about it, who relies on this data, so you have, the marketing team relies on this data, they need to know, the sales team probably relies on this data as well, your you know, product teams probably rely on this data as well, your financial teams probably rely on the state as well.

So bringing almost kind of like a steering committee together to talk through, okay.

We’re currently using attribution modeling to resource and budget, but that’s going to go away.

So here’s the data that we do have available, what kinds of decisions can we make from that information? And take it as far as you can, until you get to that point of like, we can’t answer this question.

And that’s when you start to look for outside help.

Christopher Penn 11:19
So actually, there is a way to build a kinda, okay, attribution model with the data nga, for up to your point there is a a subpar but functional substitute.

It’s not great.

It’s not.

It’s certainly something I would bet the bank on.

But it also is better than nothing.

Maybe we should do that for like this week’s livestream show people how to build that because it’s it’s not difficult.

It just requires knowing what’s in the GA for API, which is not the best documented.

It’s this gap.

Katie Robbert 11:55
Yeah, we should absolutely do that.

Because, you know, to your point, Chris, you know, you were asking me, like, what do people do? And you’re saying that there is a solution?

Christopher Penn 12:06
There is, but it’s not documented anywhere, like, literally, it’s just google put these things in the API, and then kind of expects you to figure it out and put an assembler for yourself in Data Studio.

There’s no directions, there’s no, no one said, here’s how this works.

They don’t there’s not even really good definitions it took Someone was asking me on Twitter, like, you know, what’s the difference between this metric and this metric? I had to go dig through the API like, Oh, look, that’s actually the hints of an attribution model.

It’s just that it’s not called that nobody knows it’s there.

Katie Robbert 12:34
So you’re making a lot of assumptions, you know, so first of all, it’s someone needs to know that there is an API.

Yep.

The second is someone needs to know how to connect to and extract data from the API.

And so I think those are some of the things that, you know, again, we need to think about sort of your average, you know, majority marketing team where that’s not necessarily going to be a thing.

So that is definitely a solution.

But I’m not going to count on, you know, someone being able to access an API, if you asked me, if you’re like Katie, go set up an API for Google Analytics, I’d be like, I’m sorry, you want me to what now? Because I’m fortunate that I have you that I don’t necessarily need to know how to how to do that.

I know what they are.

I know how they work.

I know, you know, the ins and outs of it.

But I’ve never myself personally built one.

So I would struggle with that, if I was tasked with that.

And I would imagine a lot of other marketing teams would know, I could be wrong.

And I would love for people to respond to this podcast, and let me know, you know, sort of your level of expertise with API’s, but I’m assuming majority, just don’t either have the time or the resources to be able to do that.

Christopher Penn 13:48
Right? Well, in this case, it’s it’s the way Data Studio talks to GA, it uses the API like everybody else.

So it’s something that you can do in Data Studio with no other coding.

But in terms of change management, again, it’s one of those things that because Google has not done a great job of documenting or explaining any of this.

When you’re talking about requirements gathering, and you know, technology parallels, if you don’t know those things are there because Google doesn’t know those things.

They didn’t explain it as that, then you’re kind of left in the lurch.

Like you’re really is a Hey, if you don’t know the difference between like session medium and a user medium and how these things relate to each other, and how you can build it in Data Studio.

You don’t know that that is an attribution model.

And so what does somebody do if they’re, you know, if you’re trying to do a change management plan, a transition plan, and you don’t know what’s in the box, it’s a lot harder out imagine to build an effective transition plan because you may end up having to buy things or, or stuff that you may not even need.

Katie Robbert 14:50
And there’s really no getting around that.

I mean, if you don’t have the resources on your team to be able to dig into that deep technical side of things, then you are where you are.

And that’s okay.

That doesn’t mean that you’re doing it wrong, it means that you’re just doing it differently.

You’re doing it in a way that’s custom to what you need, given what you have to work with.

You know, and so you may decide to bring in a third party to help you create that transition plan.

Someone like a Chris Penn, who does know more of the ins and outs of the technical side.

But if you don’t have the opportunity to do that, then you work with what you have.

And so you start to document out, okay, here’s what we have to work with.

Let’s start to put together some kind of reporting.

And month over month, we’re gonna run our old report and our new report side by side, do what we normally do with the old report, make our decisions, but then also play out the scenario of what does it look like to make decisions with a new report so that you’re not suddenly just making that switchover? But you’re starting to get people used to that new set of data of, you know, what they have to work with? What decisions they can make with it, and see where the deficit? Where are the limitations? And again, do we need to bring in other data to supplement in order to make this report and decision making work?

Christopher Penn 16:11
What are the things that we talk about in our j four? conference presentation is finding some easy wins early on, so that you can get adoption a little bit easier if you can find something that the new software does that the old software doesn’t, that’s valuable.

People might be more inclined to at least be willing to give it a try and be a little bit less resistant to the change.

When you’re doing change management, how much does that factor into like your formal change management plan, how much to those easy wins to the extent that they exist? ease adoption.

Katie Robbert 16:49
It helps when people are getting that instantaneous feedback and that motivation.

And so one of the things we talked about on last week’s episode around change management was, when you think about the people side of it, you have to focus on two things, you have to focus on the greater good of the team and the company.

But you also have to focus on the individual, because it’s the individuals collectively that make up the team.

And so if you have one or two people who just are not on board with the change, the change isn’t going to happen.

And so I absolutely feel like those easy wins, we’re you know, we’re putting in quotations, easy wins.

But these are things that, you know, calling the low hanging fruit, call whatever you want, but there are things that help people see, okay, this might work, I can move this thing forward.

Here’s how I personally contribute to making this change happened.

And so, you know, in the event of moving from ga three to ga four, it’s helpful to have representatives or even just all of those different teams to say, or have a conversation, how does this affect you? How do you factor into us moving from this system to this system, so that people have number one an opportunity to raise their concerns that you can start to address so that they don’t feel like they’re blindsided by a new set of data.

But also, you’re getting those different perspectives.

Because if you’re focusing only on how the marketing team is going to use this data, then you’re missing out on all of these other opinions and different walks of life that are using it in a slightly different way.

And so the sales team might be looking at this attribution data and go, Okay, I need to send out more emails.

Whereas the marketing team might be looking at it as I’m sending too many emails, and you need to sort of come together on those two things.

And then you need to break it down to the individual level of, okay, Chris, if we start changing the data that we’re using, what does that do for you in terms of either your decision making, in terms of resource and or you as the resource? What concerns do you have about how your daily tasks will change? Because it’s still at the core of it, change management comes down to the people, you can change the systems, you can change the process.

But when you integrate the people into it, though, that’s where you’re going to hit some of those road bumps.

Christopher Penn 19:08
Gotcha.

So for Google Analytics for adoption, things when we’re looking at them, many, many road bumps that are on the way, it sounds like you got to do your homework, it sounds good to spend an awful lot of time doing your homework, because unlike the typical vendor selection process, where you have time to evaluate, and essentially you have control over the decisions, this is a case where a lot of the decision making is kind of out of your control, it’s you know, you’re unless you’re paying for analytic software, we all kind of just use it for free and kind of have to take what we get.

Katie Robbert 19:44
So, you know, you brought up the vendor decision making process, and I would, I would argue that you don’t always have a lot of time.

So if you’re if you work in a large organization or any organization, sometimes what happens is either all Features change, or they raise the price, and you need to go find something else really quickly because you can’t afford it.

And so it’s always something that you want to be mindful of, I guess all the time, it’s sort of a consistent process that you want to continue to evaluate, not just when you’re looking to make a switch, because sometimes the switch is forced upon you, and you don’t have the opportunity to really sit down and plan it out.

So always being aware of, here’s what I’m getting currently from the system.

And that comes back to those business requirements.

And so before you bring in any new system, whether you it’s been forced upon you, or you were thinking about it, you know, a few months in advance, taking at least, you know, a couple of hours to do that due diligence of like, what am I getting? What’s in the box? What do I do with this information? And that will help you if, let’s say, for example, you know, tomorrow Google goes under, and we all have to find a new Analytics tracking system, you know, just as an example, well, oh, my God, we’re all going to be in a panic.

But the people who will be panic and police are the people who have some sort of documentation of what do I currently do with this thing that helps me have the conversation with other vendors of, here’s my list of requirements, here’s what I need, can you do this for me? Does your software do this, and that helps with that transition.

And it’s something that, you know, maybe once a year, when you’re doing your, you know, yearly audits and your annual reviews, you include those business requirements of all if you’re different systems in that conversation, just to make sure that they’re up to date that you’re getting what you need from them.

And then that way, when change does happen, it goes a little bit smoother change management, never, there is no such thing as smooth, change, management changes are hard across the board, big changes, small changes, it doesn’t matter.

They’re hard.

They take time.

And I think that that’s the other thing to remember is you can just like flip a switch on new software.

But that doesn’t mean that you’re getting everything you need.

And people getting used to a new system takes time, people getting used to new data takes time, people saying, well, I used to do it this way.

And why can’t I still do it this way, that conversation will happen multiple times.

So you also have to have some patience.

So if you’re changing people, if you’re changing process, if you’re changing your platform, it takes time.

Christopher Penn 22:22
It sounds like an analytics, annual checkup would be a healthy thing for everybody be doing?

Katie Robbert 22:27
Absolutely.

I think that it’s here’s the problem, we are all juggling so many multiple things, we are all feeling like we’re overworked and understaffed, that taking the time to do that, that’s what gets crossed off the list of like, I don’t have time to do that the system is working as I need it.

That’s where we’re all gonna get burned ourselves included.

So you have to actively and thoughtfully make the time to evaluate what your people are doing, what your systems are doing, what your processes are doing.

In order to not be caught off guard when something suddenly changes, you can still be caught off guard, but then you can go Oh, wait, I have all this great documentation to tell me, here’s what I need to do next.

And here’s what I need to go find to replace the thing.

Christopher Penn 23:15
All right.

So that is the technology side of change management.

Maybe next week, we’ll cover a process who knows.

But either way, we know that particularly with things like Google Analytics, big changes are afoot already.

And you definitely need to spend some time getting ready for the changes before the change has happened.

And you don’t keep up with them.

So if you got questions about this or anything else we’ve talked about in today’s show, hop on over to Trust insights.ai slash analytics for marketers, our free slack group with over 1700 folks who are chatting about all things analytics, plus other fun stuff like you know photos of our pets.

Thanks.

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