May 13, 2025 • 28 mins
In today’s episode, we’re diving into choice tech — not just the tools businesses use, but how they choose them. Because in a world filled with platforms that promise to boost productivity, streamline collaboration, and automate the busywork, what often gets overlooked is the bigger picture: the long-term impact of those choices on your team, your culture, and your bottom line.
And sometimes, the tools meant to help… end up doing more harm than good.
To unpack all of this, I’m joined by Emily Pabst, founder of RemakeTheRules.com. Emily works with organizations to rethink the systems that shape their work — and that includes making smarter, more human-centered decisions about technology. She’s seen firsthand how the right tech can empower teams — and how the wrong choices can quietly undermine them.
We’ll talk about the decision-making process behind adopting new tools, the warning signs of tech overload, and how companies can align their tech stacks with their actual values — not just their ambitions. Let’s get into it.
www.mentalwealthpod.com
www.pedalmyway.com
remaketherules.com
DISCLAIMER: The views, thoughts, and opinions expressed are the speaker’s own and do not constitute legal, medical, or other forms of professional advice. The material and information presented here is for general information and entertainment purposes only. The "Mental Wealth Podcast" and "Pedal My Way" names and all forms and abbreviations are the property of its owner and its use does not imply endorsement of or opposition to any specific organization, product, or service.
And sometimes, the tools meant to help… end up doing more harm than good.
To unpack all of this, I’m joined by Emily Pabst, founder of RemakeTheRules.com. Emily works with organizations to rethink the systems that shape their work — and that includes making smarter, more human-centered decisions about technology. She’s seen firsthand how the right tech can empower teams — and how the wrong choices can quietly undermine them.
We’ll talk about the decision-making process behind adopting new tools, the warning signs of tech overload, and how companies can align their tech stacks with their actual values — not just their ambitions. Let’s get into it.
www.mentalwealthpod.com
www.pedalmyway.com
remaketherules.com
DISCLAIMER: The views, thoughts, and opinions expressed are the speaker’s own and do not constitute legal, medical, or other forms of professional advice. The material and information presented here is for general information and entertainment purposes only. The "Mental Wealth Podcast" and "Pedal My Way" names and all forms and abbreviations are the property of its owner and its use does not imply endorsement of or opposition to any specific organization, product, or service.
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:05):
How do companies decide on the technology that's driving their business,
and what happens when business decisions are based on faulty data.
This week, we're looking into the world of choice tech
and learning from Emily Paps of remaketh rules dot com
as we explore the active steps that business leaders can
take in choosing systems that support their operational goals and
(00:25):
their teams. We think you're really going to enjoy this, Okay,
let's dive right in. For add free episodes of the
Mental Wealth podcasts, head to mentalwealthpod dot gum Road dot com.
Emilypaps remake the Rules dot com. Thank you so much
for joining us again. We really appreciate your time. It's
great to see you.
Speaker 2 (00:42):
Yeah, my pleasure. It's great to be back. Thank you.
Speaker 1 (00:45):
Today we're talking a little bit more on the business
side of things. We're talking about a term that you
and I have just discussed called choice tech. Could you
explain more about what choice tech is for our audience please?
Speaker 2 (00:55):
Yeah, sure. Thing. Choice tech is a term that I
started to use to kind of of the situation that
so many people are finding themselves in, and essentially, it's
digital tools that are designed to impact a person's decision
making choice tech, and it can span a huge segment
of the digital technologies that we interact with, including dating apps,
(01:18):
social media, and then also the sort of bespoke analytical
tools that a lot of companies, businesses, and institutions are
using to understand their processes and understand their people.
Speaker 1 (01:30):
It's probably one of those questions that a lot of
employees have before they join a company. They get all
these tools and they get told to use them, but
they don't really understand what the value is to the business.
In some cases, maybe the management doesn't understand the value
of the tool itself. It's a list of things that
you can point to where management goes wrong in terms
of the technology that they choose for their business, where
(01:51):
that's sort of taking the wrong track with the kind
of technology they use in It is.
Speaker 2 (01:55):
A very difficult time to be making choices today. We
live in a tremendously challenging and complicated informational environment, and
most people aren't well set up to parse that quantity
of information the quality information that they're encountering. This is
just all new ground for everyone, and the stakes get
really high when you're talking about your own business, about
(02:18):
your livelihood, your job, and maybe even a very large
organization that you are attempting to lead to make strategic
decisions for. And certainly I think that the pressure really
gets to people, and that that is one of the
first things is that there is this very big idea
and sort of sense that there is a need for
(02:40):
more information, more tools, for this faster speed of ingesting
information and being able to have this omniscience about what's
going on, and that that expectation is really hard on
people because it is very difficult to achieve, and the
discrepancy between that expectation of what we should be able
(03:00):
to do, what we should be able to know, and
sort of where we are at now with our tools
and our digital tools and information is really hard on people.
And I think that is something I see everywhere.
Speaker 1 (03:10):
That's a great point you make about that the shift
volume of data that a lot of companies are dealing
with in terms of the amount of effision coming in
and the output they're expected to deliver, is that something
where is that to just do the speed of technology
evolution or is that to do with the fact that,
as you said, it's pressure, it's delivering results, it's delivering outcome.
(03:30):
Is there one thing or another that that's causing that
or is it purely just the environment itself.
Speaker 2 (03:36):
I think that as we integrate or attempt to integrate,
these digital tools, there is a sense that we should
be also thinking like these tools, that we should be
performing like these tools. And as we pull these digital
tools into our decision making, our decision making should be
able to match them, to keep up with them, to
(03:58):
work in the same way that they work. And that
is just not true. Our brains do not work in
the same way that these digital tools do, which can
absolutely be a huge plus, right, And that is a
lot of what I work with people on is where
thinking works best inside of a person, inside of a team, right,
where you sort of delegate certain types of thinking and
(04:19):
problem solving to people, and where you delegate certain types
of thinking and problem solving to digital tools. But if
you have a mismatch of which one like where you
are placing your thinking and your problem solving, it gets
very challenging very quickly, can steer you in the wrong direcsion.
Speaker 1 (04:33):
What's an example of a decision that you would ultimate
that you would give the technology.
Speaker 2 (04:38):
Computers are great at doing math, so like, absolutely, let
them do computational work all day long. That is a
great thing, something that is incredibly routine, great thing for
computers to do. They're great out of humans, very bad
at it, So go ahead and let the computers do
that stuff.
Speaker 1 (04:54):
Yeah, that's a great point. It's sort of increasingly in
the digital marketing industry at least, I've find people are
leaning on a digital tools for creativity, and it's sort
of you can see the blend and the way it's
influencing other people, like you can see how that sort
of bleeds into various creative areas. And as as you said,
it's perhaps not the best way to utilize these technologies.
(05:16):
Although you know, chat, GBT and all these things have
a role to play in creativity. They can create templates,
they can create a foundation for humans to take on
that creative work. They don't perhaps provide the entire solution,
which a lot of businesses are sort of using, as
you said, these technologies, they're sort of using it as
like a catch all for everything. They're saying, we're just
going to give it to the technology to do and
(05:36):
hope for the best. I find that oftentimes it's sort
of the they have to sort of validate their investment
in the technology. Is not the case a lot of
the time. It's sort of they've bought this thing, and
now we have to use it somehow.
Speaker 2 (05:46):
Yeah, certainly, And I love this idea of using it
for creativity and this conversation. It'll be so interesting. We
talked about a life time like it's going to be
out of date in a moment, but here we are.
We still got to process our present day reality. But
I think that there is a big difference between creativity
as an innovation and creativity as in output, and that
(06:08):
that is very important to keep in mind. That the
ability to produce creative work is one thing and certainly
is a whole huge conversation in and of itself, but
then the ability to be innovative and to have innovative
ideas is kind of a totally different beast, and there
are huge discrepancies in between what AI right now can
(06:31):
do in those two fields.
Speaker 1 (06:32):
It's also to do with incentsive structures too, that we've
talked previously about how do we motivate employees to get
this sort of outcome that the business wants, and a
lot of companies that's bringing technology into that area of
the management structure. Right, they're trying to bring technology into
the incentives and hoping that employees can sort of understand
what the business needs, and the employees are sort of
doing get in a way where they think the business
(06:55):
wants within your work. Do you see that a lot
of the time in terms of how people incentive structures?
What is this? What the mistakes people are using when
they implement incentive structure that takes them away from what
the business really needs.
Speaker 2 (07:10):
Going back to the idea, we hit on a little
bit ago of the sheer complexity of operations and the
sheer quantity of information that we now have access to
that are meant to document or mimic or understand those operations.
Is too much right, too much volume. Human brains are
not going to be able to look at a million
data points and be like, Aha, this makes sense to me. Right,
(07:31):
we use computers to help us organize that information in
a way that makes sense to us. And in order
to do that, it, by necessity, is simplified. And that
simplification is not in and of itself a problem, but
where things can go really wrong and about sort of
these incentive structures. If you have a really complicated operations
or the business that you run involves a lot of
(07:54):
people making decisions all day long, right, so maybe they're
customer facing, they are making difficult decisions about interacting with people,
and then that information is being sort of synthesized, simplified
and driven up towards management, towards higher level leadership. Then
(08:14):
there is the possibility that that translation is not being
done very well and potentially can even be done in
a way that is leading to misunderstand what good work
looks like, what good choices look like. And if that occurs,
then you have a really big problem of incentivizing the
(08:35):
wrong types of choices, the wrong types of behavior. And
that is definitely something that these very powerful tools have
the potential to do. Not just to help us make
great decisions to better understand our operations, they can help
us to understand them have of a worse understanding of
them if we are pulling sort of the wrong information
(08:58):
out of it, the wrong meaning.
Speaker 1 (08:59):
Out of it. Yeah, and I guess meaning is a
great way of putting it. I love the idea of
how do you derive meaning from both the technology side
and what your employees are doing on a day to
day basis, you don't really always know what employees are
doing at a certain time. You've got tasks that they
have and they've completed the tasks, but you don't know
whether they've had an issue completing the task or how
(09:21):
they did it. You see the result. How do you
think managers can use this technology to make more meaningful
positive impact on that businesses? Is it simply about communicating
more effectively with employees.
Speaker 2 (09:33):
So I really feel for folks in supervisory and management
positions right now because of the extent of changes that
it's just occurring in the way work is done, in
what counts as work, and even the remote aspect of it,
right is really changing a lot of the ways that
(09:54):
managers and supervisors have been able to measure whether or
not their team is operating well. And I don't think
it means that teams are operating poorly. It just means
that all of the ways, many of the ways in
which we use to determine that don't really work anymore,
don't work in this environment because of artificial intelligence tools,
(10:14):
because of work from home, because of new other digital
tools that that business is using. So trying to and
you know, this is what I work with people on
right is trying to really not just wrap their mind
around what is happening right now and how can I
determine if it's good or not? First and foremost, very
(10:34):
hard to answer right now is what is happening? What
should be happening, or what I would like to happen,
or what would be beneficial for my goals this company's
goals to happen. Very hard to answer right now. And
then once you get through those two big questions, how
can I determine if we are in the right direction
(10:54):
or not? That's the third question. By the time we
actually get to the technology question is the third big,
gnarly question that we get to and the tools we
have absolutely have the capacity to help with that and
to make really good determinations with that, But we have
to get through the first two questions first. So this
is kind of where a lot of it is the
(11:16):
people's stuff that is the first thing that we have
to figure out, and then we can get into the
tech stuff of it all.
Speaker 1 (11:22):
I think for a lot of people, and again I
can only speak from personal experience, it's sort of like
you you show up to work and you just think
the company wants to incentivize profit. They want to incentivize
the result, which is the clients are happy, My customers
are happy. Everyone gets to go home, we make some money.
Is there something that you've got to get employee buy
in for these tools? Sometimes? How do we how we
(11:45):
communicate the benefits of these tools impacts whether employees use
them effectively correct.
Speaker 2 (11:51):
For certain for certain, and some of it has to
do with legitimate concerns about whether or not these tools
are meant to support the employee as well. Right if
they are designed to be like a holistic system that
is sort of bringing the entire organization up or not,
And that is a very important question that folks should
(12:14):
be asking, and it's something that can be difficult to
do right again, where we are designing a lot of
these tools for the first time. Individual organizations can have
vastly different operations, so they are literally building these bespoke,
unique systems for understanding their own operations, their own administration,
And it takes a lot of labor, but it is
(12:34):
absolutely labor that's worth doing well, and it's absolutely something
that should be considered on a very large system scale
and considering every aspect of operations and administration, including every
layer of employment empolee.
Speaker 1 (12:49):
Is that something that a lot of businesses miss out on?
Is it just sort of the too focused on the
end goal when they're choosing this technology, or is it
the fact that they've got to sort of start from
how how can I best help my team get to
where we need to be as a business? How can
business owners make that decision effective for the entire organization.
Speaker 2 (13:08):
Part of the challenge here is really how complicated these
questions are. And there are a ton of concerns about
implementing digital tools that are not just about usability. Security
is another big concern, right, So you are going to
have often layers and layers and layers of considerations and
questions about how to move forward, which absolutely sounds daunting
(13:31):
and I understand that, but it can also be managed right.
And I think that it is a very challenging balance
to get the operational considerations right, and that that is
really the goal what an organization, what a leader is
attempting to achieve, is an effective balance moving towards likely
(13:55):
a primary or several primary goals.
Speaker 1 (13:58):
Do you define whether the tool itself is working, how
it's a success, Like who gets to define that. That's
another question that I guess a lot of business owners
have got to sort of look into. If you're the
one that picked the tool, and you know you're speaking
to maybe if it's a piece of software, for example,
you're speaking to the developers behind it. There of course
of course going to say, yeah, it's working great, look
at this arbitrary result we've decided it's giving you. Is
(14:21):
that something that business owners have got to look into too,
is like, how do you before you even implement it,
how do you define the success of that implementation.
Speaker 2 (14:28):
Hopefully, when a tool is researched and purchased and implemented,
it is for a greater goal that presumably there is
a problem that they're looking to solve, and they were
hoping that this tool will solve it. And certainly a
continuing to say sort of grounded in that perspective of
how does this work on this discrete problem and then
(14:50):
how does it also impact every other part of operations
outside of this discrete problem is the perspective from which
it should really get evaluated, Yes, with that sort of
foundational question, but then also making sure that it is
expansive to the entire operations because That's really what I'm
seeing with many of these information tools is that they
(15:10):
never stay in the box you want them to, right,
They just don't, especially when you're looking at measuring productivity
and how people are performing. That is going to start
impacting the choices that people make in their day to days,
and not necessarily just in sort of these small discrete boxes.
Speaker 1 (15:28):
That's a great point about the day to day experience too, because,
for example, I think about time management tools. You talk
about remote work. A lot of companies now have time
management tools where they track what someone's doing on a
day to day basis, and really the result you want
is the employee doing the work for the customer or
whatever is they're doing. You can sort of measure that
(15:49):
outside of the time management aspects of it, whether they
actually did nine to five or whatever else they're supposed
to do. Is that an example of a tool that
is being used where companies are looking at it from
the wrong point of view? Or do you see value
in those sort of I guess monitoring and time management products.
Speaker 2 (16:05):
We're often solving problems that can be pretty complicated in
and of themselves, right, So there's going to be lots
of choices lots of behaviors, lots of interaction that's happening,
and with the tools that we have currently, only so
much and certain types of information can be documented well
and easily. And here's where the meaning making comes in again, right, Like,
(16:29):
what of the things that we are able to document,
what meaning can we actually extrapolate from those things? Like
if I can see that somebody is logged into their
computer for X hours every day, am I able to
accurately extrapolate from that that they are a hard working employee?
Probably not right, because we all know that you can
(16:49):
be in front of a screen being the opposite of productive, Right,
that's well within our capabilities. So it's that sort of
logical understanding of what we are making from what we
are documenting is where this sort of critical questions and
that breakdown can start to happen. Here's an example of
(17:10):
the broken down incentive structures that i'd see using your example, Say,
we've got somebody who's logged into their computer for ten
hours a day, which is more than everyone else. You're
only expected to be logged in for eight hours a day.
So because this person's electrics are so high and they're
so quote unquote dedicated their job or whatever, we are
going to throw them a party and let everybody know
(17:31):
that their employee at the quarter. But it's possible that
everyone else knows that that person is actually not working
during those ten hours and that they are doing whatever else. Right,
So you have totally, unnecessarily, as leadership, put yourself in
a situation where you are publicly throwing a party for
the employee that everyone else knows doesn't do any work.
(17:54):
And that is going to be very problematic for you
and for morale.
Speaker 1 (17:59):
Yes, alienated the ones that are actually doing the hard
work for you.
Speaker 2 (18:03):
Precisely, And like you know, that's like a pretty basic,
potentially obvious experience or example. But this is the danger
of sort of creating incentive structures that don't actually get
the outcomes that you want because of the monitoring that
you're doing of productivity and about personal time and effort.
Speaker 1 (18:24):
Yeah, and you can see just by your example the
knock on effect of that kind of poor decision making,
because all of a sudden that employee are throwing parties for.
You may give them a promotion over another employee. You
may give them more money and more power and more responsibility,
and then they're making bad decisions for the organization, so
it can sort of have a continuing effect on that.
It just speaks to the power of what you're talking
(18:45):
about in terms of getting those decisions about technology right
from the get go and getting buy in from people
and finding out is this the right Am I making
a decision based on actual tangible data or are we
just choosing arbitrary metrics to sort of define our goals.
That's such an important thing to do.
Speaker 2 (19:03):
With all these, you know, choice tech tools that we have.
I like to talk to folks where it's essentially like,
we don't have any neighborhood streets anymore, right, we don't
have any surface streets. We exclusively have super highways. So
if you use this technology, right, we don't go anywhere slowly.
We go in these huge leaps and bounds. We go
(19:23):
there at one hundred miles per hour. So you better
be pointed in the right direction because that is the
potential of these tools.
Speaker 1 (19:31):
Yeah, even tools that most people use every day, something
like Slack for example, of productivity. It's all a messaging
so everyone sort of you know, they sign in, they
log in all the time. We know that it brings
people together. But a lot of the time what I'm
doing outside of slack is sort of creative work. A
lot of my work is content creation and design, and
(19:54):
we have these messages in the background that take you
away from what you're actually doing. You have this sort
of messaging system, which is crucial to the running of
the business. It has to be there, but a lot
of what happens is you sort of focus more of
your time on communication than actually doing that. The work
is itself, So it just sort of speaks to the
idea of how to help employees make better use of
(20:14):
that time, first of all, but also making better use
of the tools available.
Speaker 2 (20:18):
Yeah, and that like another example, right if you're essentially
and I've certainly seen this where teams are strongly incentivized
based on availability. So the quicker that a person can
respond to me texting them, calling them, emailing them, chatting them,
all of the above, the higher I consider that employees
(20:39):
work to be right that they are. They're the ones
that are working really hard. And it's definitely an easy
thing to measure, and it definitely feels good in the
moment when you want something, you have a question and
it gets answered roadway totally get it, but it is
tremendously disruptive to that deeper thinking work that people often do,
(20:59):
to the content centration that a lot of workers need
to do the actual core parts of their job. So
that's another really good example of how these digital information
tools are sort of disintegrating some of the actual core
processes that we need from folks.
Speaker 1 (21:16):
I'm just thinking about the soft data that companies get
into their systems in terms of client satisfaction and things
like that. Is there a way to sort of use
these tools to access that kind of data, that sort
of soft data that has significant value over the long
term growth of a business, And is there a sort
of a way that companies can do that more effectively
or more easily.
Speaker 2 (21:36):
There absolutely already exists a way to incorporate that, and
then it just kind of depends on whether or not
it is digitally available information. And once it is digitally
available information, then it's just a question of how it
is being incorporated into the bigger meaning making analytics. Right.
(21:57):
If it is how it is, how that meaning making
is happening with sort of a combination of a lot
of data about productivity or what have you, you absolutely
can still learn a lot about a process without having
all the information. We're never going to have all the information.
But even if you have these sort of big areas
where information is not digitally available, that's just something that
(22:20):
needs to be understood about the limitations of what you'll
be able to learn from your digital information. And I
say digital information because we are kind of talking about
creating these analytical processes, computational analytical processes, but also there
are almost certainly systems in place of these team dynamics
right where you have supervisors, managers, leadership in place to
(22:45):
have relationships with folks to understand the work that they do,
to see what is happening, and being able to make
sure that that information is not ignored over the digital information.
That's really important too.
Speaker 1 (22:59):
Great. Do you think that the technology has a role
to play in team building because team building seems to
be one of the most important aspects of sort of
growth for a lot of different companies now because we're
not we're sort of working in silos, we're sort of
working separately a lot of the time. Do you see
this kind of analytical technology having being used in a
way that can help in the team building elements?
Speaker 2 (23:21):
Yeah, it's an interesting question. I mean, I think what
technology does best on its face is connection. Right, Like
the fact that we're talking right now is not something
that would be feasible about this technology. That being said,
there's a limitation to what it can achieve. I am
sure that there are some smart, creative, capable people who
are working to solve exactly that problem right now.
Speaker 1 (23:43):
That might be something that these sort of tools eventually
evolved to become.
Speaker 2 (23:48):
Right, kind of going back to a question from earlier
that I think for the team to be on board
in how and why certain metrics are being measured. Right,
So this idea that there are overarching goals that the
team has that people are a part of that, that
there is investment on what you are working on and
(24:09):
what you are trying to achieve and move forward, and
that if that investment exists, then tools that accurately and
reasonably support those goals would also be something for a
team to potentially rally around. Right that it is showing
the extent to which everyone is achieving these benchmarks moving forward,
(24:31):
creating new and innovative ideas, and that that can be
part of a positive incentive structure that sort of everyone
has buy in on.
Speaker 1 (24:42):
Yeah, it's a great point. It's also to do with recognition, right,
if people are being recognized through the technology through that
prism of it's not just about judgment, it's about we're
going to say we see what you're doing through these systems.
And that's that's a great point from my previous experience.
In a few other industries outside of digital, the technology
is more used from a management top down point of view.
(25:02):
It wasn't really used to sort of support. It's more
of a sort of like how can we best get
the result, which obviously has its place, but perhaps thisdirects
a lot of the resources that you would have at
the staff level too.
Speaker 2 (25:13):
A lot of these analytics are built to essentially feed
information up to a top level, right, and then it
would be decisions would be made at that level that
would presumably kind of push their way down. And I
think that what I've certainly seen is that that understanding
of communication amongst an organization it just doesn't work anymore,
(25:34):
is untrue. And it is because of these analytical structures
that we have all levels of people who are directly
or incidentally adding data in information to them and then
it maybe is being used sort of on a viewer standpoint,
exclusively from high level leadership, but because that leadership is
(25:54):
making decisions based on it, creating incentive structures based on it,
and the folks who are inputting data into it are
daily participates in it, and they realize that and it
is actually sort of not information making its way down
from on high. It is sort of like immediately getting
to all levels of an organization. So while you have
(26:16):
information from all levels of an organization that are very
quickly going up, it is the exact same way going
in the opposite direction. And I think a lot of people,
a lot of leaders, misunderstand that it is a two
way stream.
Speaker 1 (26:29):
That's a great point, and that sort of brings me
to the next question, which is sort of to do
with how leaders are choosing the technology and how they're
making these decisions. What is one thing that every organization
and leader can do when choosing a tool to measure people.
Speaker 2 (26:45):
I think that a really great question is for them
to ask themselves what their current relationship and use is
of their analytical tools. Do they feel like they understand it?
Are they comfortable with it? Can they ask difficult questions
about how it operates and what it means, and if
(27:07):
that is something that you struggle to do, then I
would absolutely pause and develop a stronger understanding, a stronger
relationship with the information tools that are currently at your disposal.
Speaker 1 (27:20):
That's a great point. I really appreciate that sort of
solidifying what we're talking about in terms of what is
the meaning behind the decision that you're making, What are
you getting from this decision. That's such a great point.
So we've talked quite a lot now about the different
decision making technology and the choice tech is the word
you've coined. There is the sort of a final summary
you can give for business owners, maybe the choosing a
(27:42):
new technology they just about to make that investment. Is
there sort of a piece of advice you can give.
Speaker 2 (27:47):
Yeah, certainly. You know, I think simplistically, what we measure
is what makes us, So be very consider it, be
very cautious, very thoughtful about what you choose to measure,
because it will what is prioritized within your business, within
your organization.
Speaker 1 (28:04):
Yeah, that's a great point. As always, Emily really appreciate
you educating me on a lot of these topics, and
it's always great to have someone with your experience and
background to sort of guide us on some of these
more complex issues, and I wanted to thank you again
for your time. It really means a lot. Thank you.
Speaker 2 (28:20):
Yeah, thank you so much. It's always wonderful talking to
you guys.
Speaker 1 (28:23):
Thank you again, Emily Perhaps remaketh rules dot com. Thank you.
A quick reminder, if you're enjoying this conversation, please subscribe
to the Mental Wealth podcast on your favorite platform. It's
a small action that can make a big, big difference
to us. Thank you.
How do companies decide on the technology that's driving their business,
and what happens when business decisions are based on faulty data.
This week, we're looking into the world of choice tech
and learning from Emily Paps of remaketh rules dot com
as we explore the active steps that business leaders can
take in choosing systems that support their operational goals and
(00:25):
their teams. We think you're really going to enjoy this, Okay,
let's dive right in. For add free episodes of the
Mental Wealth podcasts, head to mentalwealthpod dot gum Road dot com.
Emilypaps remake the Rules dot com. Thank you so much
for joining us again. We really appreciate your time. It's
great to see you.
Speaker 2 (00:42):
Yeah, my pleasure. It's great to be back. Thank you.
Speaker 1 (00:45):
Today we're talking a little bit more on the business
side of things. We're talking about a term that you
and I have just discussed called choice tech. Could you
explain more about what choice tech is for our audience please?
Speaker 2 (00:55):
Yeah, sure. Thing. Choice tech is a term that I
started to use to kind of of the situation that
so many people are finding themselves in, and essentially, it's
digital tools that are designed to impact a person's decision
making choice tech, and it can span a huge segment
of the digital technologies that we interact with, including dating apps,
(01:18):
social media, and then also the sort of bespoke analytical
tools that a lot of companies, businesses, and institutions are
using to understand their processes and understand their people.
Speaker 1 (01:30):
It's probably one of those questions that a lot of
employees have before they join a company. They get all
these tools and they get told to use them, but
they don't really understand what the value is to the business.
In some cases, maybe the management doesn't understand the value
of the tool itself. It's a list of things that
you can point to where management goes wrong in terms
of the technology that they choose for their business, where
(01:51):
that's sort of taking the wrong track with the kind
of technology they use in It is.
Speaker 2 (01:55):
A very difficult time to be making choices today. We
live in a tremendously challenging and complicated informational environment, and
most people aren't well set up to parse that quantity
of information the quality information that they're encountering. This is
just all new ground for everyone, and the stakes get
really high when you're talking about your own business, about
(02:18):
your livelihood, your job, and maybe even a very large
organization that you are attempting to lead to make strategic
decisions for. And certainly I think that the pressure really
gets to people, and that that is one of the
first things is that there is this very big idea
and sort of sense that there is a need for
(02:40):
more information, more tools, for this faster speed of ingesting
information and being able to have this omniscience about what's
going on, and that that expectation is really hard on
people because it is very difficult to achieve, and the
discrepancy between that expectation of what we should be able
(03:00):
to do, what we should be able to know, and
sort of where we are at now with our tools
and our digital tools and information is really hard on people.
And I think that is something I see everywhere.
Speaker 1 (03:10):
That's a great point you make about that the shift
volume of data that a lot of companies are dealing
with in terms of the amount of effision coming in
and the output they're expected to deliver, is that something
where is that to just do the speed of technology
evolution or is that to do with the fact that,
as you said, it's pressure, it's delivering results, it's delivering outcome.
(03:30):
Is there one thing or another that that's causing that
or is it purely just the environment itself.
Speaker 2 (03:36):
I think that as we integrate or attempt to integrate,
these digital tools, there is a sense that we should
be also thinking like these tools, that we should be
performing like these tools. And as we pull these digital
tools into our decision making, our decision making should be
able to match them, to keep up with them, to
(03:58):
work in the same way that they work. And that
is just not true. Our brains do not work in
the same way that these digital tools do, which can
absolutely be a huge plus, right, And that is a
lot of what I work with people on is where
thinking works best inside of a person, inside of a team, right,
where you sort of delegate certain types of thinking and
(04:19):
problem solving to people, and where you delegate certain types
of thinking and problem solving to digital tools. But if
you have a mismatch of which one like where you
are placing your thinking and your problem solving, it gets
very challenging very quickly, can steer you in the wrong direcsion.
Speaker 1 (04:33):
What's an example of a decision that you would ultimate
that you would give the technology.
Speaker 2 (04:38):
Computers are great at doing math, so like, absolutely, let
them do computational work all day long. That is a
great thing, something that is incredibly routine, great thing for
computers to do. They're great out of humans, very bad
at it, So go ahead and let the computers do
that stuff.
Speaker 1 (04:54):
Yeah, that's a great point. It's sort of increasingly in
the digital marketing industry at least, I've find people are
leaning on a digital tools for creativity, and it's sort
of you can see the blend and the way it's
influencing other people, like you can see how that sort
of bleeds into various creative areas. And as as you said,
it's perhaps not the best way to utilize these technologies.
(05:16):
Although you know, chat, GBT and all these things have
a role to play in creativity. They can create templates,
they can create a foundation for humans to take on
that creative work. They don't perhaps provide the entire solution,
which a lot of businesses are sort of using, as
you said, these technologies, they're sort of using it as
like a catch all for everything. They're saying, we're just
going to give it to the technology to do and
(05:36):
hope for the best. I find that oftentimes it's sort
of the they have to sort of validate their investment
in the technology. Is not the case a lot of
the time. It's sort of they've bought this thing, and
now we have to use it somehow.
Speaker 2 (05:46):
Yeah, certainly, And I love this idea of using it
for creativity and this conversation. It'll be so interesting. We
talked about a life time like it's going to be
out of date in a moment, but here we are.
We still got to process our present day reality. But
I think that there is a big difference between creativity
as an innovation and creativity as in output, and that
(06:08):
that is very important to keep in mind. That the
ability to produce creative work is one thing and certainly
is a whole huge conversation in and of itself, but
then the ability to be innovative and to have innovative
ideas is kind of a totally different beast, and there
are huge discrepancies in between what AI right now can
(06:31):
do in those two fields.
Speaker 1 (06:32):
It's also to do with incentsive structures too, that we've
talked previously about how do we motivate employees to get
this sort of outcome that the business wants, and a
lot of companies that's bringing technology into that area of
the management structure. Right, they're trying to bring technology into
the incentives and hoping that employees can sort of understand
what the business needs, and the employees are sort of
doing get in a way where they think the business
(06:55):
wants within your work. Do you see that a lot
of the time in terms of how people incentive structures?
What is this? What the mistakes people are using when
they implement incentive structure that takes them away from what
the business really needs.
Speaker 2 (07:10):
Going back to the idea, we hit on a little
bit ago of the sheer complexity of operations and the
sheer quantity of information that we now have access to
that are meant to document or mimic or understand those operations.
Is too much right, too much volume. Human brains are
not going to be able to look at a million
data points and be like, Aha, this makes sense to me. Right,
(07:31):
we use computers to help us organize that information in
a way that makes sense to us. And in order
to do that, it, by necessity, is simplified. And that
simplification is not in and of itself a problem, but
where things can go really wrong and about sort of
these incentive structures. If you have a really complicated operations
or the business that you run involves a lot of
(07:54):
people making decisions all day long, right, so maybe they're
customer facing, they are making difficult decisions about interacting with people,
and then that information is being sort of synthesized, simplified
and driven up towards management, towards higher level leadership. Then
(08:14):
there is the possibility that that translation is not being
done very well and potentially can even be done in
a way that is leading to misunderstand what good work
looks like, what good choices look like. And if that occurs,
then you have a really big problem of incentivizing the
(08:35):
wrong types of choices, the wrong types of behavior. And
that is definitely something that these very powerful tools have
the potential to do. Not just to help us make
great decisions to better understand our operations, they can help
us to understand them have of a worse understanding of
them if we are pulling sort of the wrong information
(08:58):
out of it, the wrong meaning.
Speaker 1 (08:59):
Out of it. Yeah, and I guess meaning is a
great way of putting it. I love the idea of
how do you derive meaning from both the technology side
and what your employees are doing on a day to
day basis, you don't really always know what employees are
doing at a certain time. You've got tasks that they
have and they've completed the tasks, but you don't know
whether they've had an issue completing the task or how
(09:21):
they did it. You see the result. How do you
think managers can use this technology to make more meaningful
positive impact on that businesses? Is it simply about communicating
more effectively with employees.
Speaker 2 (09:33):
So I really feel for folks in supervisory and management
positions right now because of the extent of changes that
it's just occurring in the way work is done, in
what counts as work, and even the remote aspect of it,
right is really changing a lot of the ways that
(09:54):
managers and supervisors have been able to measure whether or
not their team is operating well. And I don't think
it means that teams are operating poorly. It just means
that all of the ways, many of the ways in
which we use to determine that don't really work anymore,
don't work in this environment because of artificial intelligence tools,
(10:14):
because of work from home, because of new other digital
tools that that business is using. So trying to and
you know, this is what I work with people on
right is trying to really not just wrap their mind
around what is happening right now and how can I
determine if it's good or not? First and foremost, very
(10:34):
hard to answer right now is what is happening? What
should be happening, or what I would like to happen,
or what would be beneficial for my goals this company's
goals to happen. Very hard to answer right now. And
then once you get through those two big questions, how
can I determine if we are in the right direction
(10:54):
or not? That's the third question. By the time we
actually get to the technology question is the third big,
gnarly question that we get to and the tools we
have absolutely have the capacity to help with that and
to make really good determinations with that, But we have
to get through the first two questions first. So this
is kind of where a lot of it is the
(11:16):
people's stuff that is the first thing that we have
to figure out, and then we can get into the
tech stuff of it all.
Speaker 1 (11:22):
I think for a lot of people, and again I
can only speak from personal experience, it's sort of like
you you show up to work and you just think
the company wants to incentivize profit. They want to incentivize
the result, which is the clients are happy, My customers
are happy. Everyone gets to go home, we make some money.
Is there something that you've got to get employee buy
in for these tools? Sometimes? How do we how we
(11:45):
communicate the benefits of these tools impacts whether employees use
them effectively correct.
Speaker 2 (11:51):
For certain for certain, and some of it has to
do with legitimate concerns about whether or not these tools
are meant to support the employee as well. Right if
they are designed to be like a holistic system that
is sort of bringing the entire organization up or not,
And that is a very important question that folks should
(12:14):
be asking, and it's something that can be difficult to
do right again, where we are designing a lot of
these tools for the first time. Individual organizations can have
vastly different operations, so they are literally building these bespoke,
unique systems for understanding their own operations, their own administration,
And it takes a lot of labor, but it is
(12:34):
absolutely labor that's worth doing well, and it's absolutely something
that should be considered on a very large system scale
and considering every aspect of operations and administration, including every
layer of employment empolee.
Speaker 1 (12:49):
Is that something that a lot of businesses miss out on?
Is it just sort of the too focused on the
end goal when they're choosing this technology, or is it
the fact that they've got to sort of start from
how how can I best help my team get to
where we need to be as a business? How can
business owners make that decision effective for the entire organization.
Speaker 2 (13:08):
Part of the challenge here is really how complicated these
questions are. And there are a ton of concerns about
implementing digital tools that are not just about usability. Security
is another big concern, right, So you are going to
have often layers and layers and layers of considerations and
questions about how to move forward, which absolutely sounds daunting
(13:31):
and I understand that, but it can also be managed right.
And I think that it is a very challenging balance
to get the operational considerations right, and that that is
really the goal what an organization, what a leader is
attempting to achieve, is an effective balance moving towards likely
(13:55):
a primary or several primary goals.
Speaker 1 (13:58):
Do you define whether the tool itself is working, how
it's a success, Like who gets to define that. That's
another question that I guess a lot of business owners
have got to sort of look into. If you're the
one that picked the tool, and you know you're speaking
to maybe if it's a piece of software, for example,
you're speaking to the developers behind it. There of course
of course going to say, yeah, it's working great, look
at this arbitrary result we've decided it's giving you. Is
(14:21):
that something that business owners have got to look into too,
is like, how do you before you even implement it,
how do you define the success of that implementation.
Speaker 2 (14:28):
Hopefully, when a tool is researched and purchased and implemented,
it is for a greater goal that presumably there is
a problem that they're looking to solve, and they were
hoping that this tool will solve it. And certainly a
continuing to say sort of grounded in that perspective of
how does this work on this discrete problem and then
(14:50):
how does it also impact every other part of operations
outside of this discrete problem is the perspective from which
it should really get evaluated, Yes, with that sort of
foundational question, but then also making sure that it is
expansive to the entire operations because That's really what I'm
seeing with many of these information tools is that they
(15:10):
never stay in the box you want them to, right,
They just don't, especially when you're looking at measuring productivity
and how people are performing. That is going to start
impacting the choices that people make in their day to days,
and not necessarily just in sort of these small discrete boxes.
Speaker 1 (15:28):
That's a great point about the day to day experience too, because,
for example, I think about time management tools. You talk
about remote work. A lot of companies now have time
management tools where they track what someone's doing on a
day to day basis, and really the result you want
is the employee doing the work for the customer or
whatever is they're doing. You can sort of measure that
(15:49):
outside of the time management aspects of it, whether they
actually did nine to five or whatever else they're supposed
to do. Is that an example of a tool that
is being used where companies are looking at it from
the wrong point of view? Or do you see value
in those sort of I guess monitoring and time management products.
Speaker 2 (16:05):
We're often solving problems that can be pretty complicated in
and of themselves, right, So there's going to be lots
of choices lots of behaviors, lots of interaction that's happening,
and with the tools that we have currently, only so
much and certain types of information can be documented well
and easily. And here's where the meaning making comes in again, right, Like,
(16:29):
what of the things that we are able to document,
what meaning can we actually extrapolate from those things? Like
if I can see that somebody is logged into their
computer for X hours every day, am I able to
accurately extrapolate from that that they are a hard working employee?
Probably not right, because we all know that you can
(16:49):
be in front of a screen being the opposite of productive, Right,
that's well within our capabilities. So it's that sort of
logical understanding of what we are making from what we
are documenting is where this sort of critical questions and
that breakdown can start to happen. Here's an example of
(17:10):
the broken down incentive structures that i'd see using your example, Say,
we've got somebody who's logged into their computer for ten
hours a day, which is more than everyone else. You're
only expected to be logged in for eight hours a day.
So because this person's electrics are so high and they're
so quote unquote dedicated their job or whatever, we are
going to throw them a party and let everybody know
(17:31):
that their employee at the quarter. But it's possible that
everyone else knows that that person is actually not working
during those ten hours and that they are doing whatever else. Right,
So you have totally, unnecessarily, as leadership, put yourself in
a situation where you are publicly throwing a party for
the employee that everyone else knows doesn't do any work.
(17:54):
And that is going to be very problematic for you
and for morale.
Speaker 1 (17:59):
Yes, alienated the ones that are actually doing the hard
work for you.
Speaker 2 (18:03):
Precisely, And like you know, that's like a pretty basic,
potentially obvious experience or example. But this is the danger
of sort of creating incentive structures that don't actually get
the outcomes that you want because of the monitoring that
you're doing of productivity and about personal time and effort.
Speaker 1 (18:24):
Yeah, and you can see just by your example the
knock on effect of that kind of poor decision making,
because all of a sudden that employee are throwing parties for.
You may give them a promotion over another employee. You
may give them more money and more power and more responsibility,
and then they're making bad decisions for the organization, so
it can sort of have a continuing effect on that.
It just speaks to the power of what you're talking
(18:45):
about in terms of getting those decisions about technology right
from the get go and getting buy in from people
and finding out is this the right Am I making
a decision based on actual tangible data or are we
just choosing arbitrary metrics to sort of define our goals.
That's such an important thing to do.
Speaker 2 (19:03):
With all these, you know, choice tech tools that we have.
I like to talk to folks where it's essentially like,
we don't have any neighborhood streets anymore, right, we don't
have any surface streets. We exclusively have super highways. So
if you use this technology, right, we don't go anywhere slowly.
We go in these huge leaps and bounds. We go
(19:23):
there at one hundred miles per hour. So you better
be pointed in the right direction because that is the
potential of these tools.
Speaker 1 (19:31):
Yeah, even tools that most people use every day, something
like Slack for example, of productivity. It's all a messaging
so everyone sort of you know, they sign in, they
log in all the time. We know that it brings
people together. But a lot of the time what I'm
doing outside of slack is sort of creative work. A
lot of my work is content creation and design, and
(19:54):
we have these messages in the background that take you
away from what you're actually doing. You have this sort
of messaging system, which is crucial to the running of
the business. It has to be there, but a lot
of what happens is you sort of focus more of
your time on communication than actually doing that. The work
is itself, So it just sort of speaks to the
idea of how to help employees make better use of
(20:14):
that time, first of all, but also making better use
of the tools available.
Speaker 2 (20:18):
Yeah, and that like another example, right if you're essentially
and I've certainly seen this where teams are strongly incentivized
based on availability. So the quicker that a person can
respond to me texting them, calling them, emailing them, chatting them,
all of the above, the higher I consider that employees
(20:39):
work to be right that they are. They're the ones
that are working really hard. And it's definitely an easy
thing to measure, and it definitely feels good in the
moment when you want something, you have a question and
it gets answered roadway totally get it, but it is
tremendously disruptive to that deeper thinking work that people often do,
(20:59):
to the content centration that a lot of workers need
to do the actual core parts of their job. So
that's another really good example of how these digital information
tools are sort of disintegrating some of the actual core
processes that we need from folks.
Speaker 1 (21:16):
I'm just thinking about the soft data that companies get
into their systems in terms of client satisfaction and things
like that. Is there a way to sort of use
these tools to access that kind of data, that sort
of soft data that has significant value over the long
term growth of a business, And is there a sort
of a way that companies can do that more effectively
or more easily.
Speaker 2 (21:36):
There absolutely already exists a way to incorporate that, and
then it just kind of depends on whether or not
it is digitally available information. And once it is digitally
available information, then it's just a question of how it
is being incorporated into the bigger meaning making analytics. Right.
(21:57):
If it is how it is, how that meaning making
is happening with sort of a combination of a lot
of data about productivity or what have you, you absolutely
can still learn a lot about a process without having
all the information. We're never going to have all the information.
But even if you have these sort of big areas
where information is not digitally available, that's just something that
(22:20):
needs to be understood about the limitations of what you'll
be able to learn from your digital information. And I
say digital information because we are kind of talking about
creating these analytical processes, computational analytical processes, but also there
are almost certainly systems in place of these team dynamics
right where you have supervisors, managers, leadership in place to
(22:45):
have relationships with folks to understand the work that they do,
to see what is happening, and being able to make
sure that that information is not ignored over the digital information.
That's really important too.
Speaker 1 (22:59):
Great. Do you think that the technology has a role
to play in team building because team building seems to
be one of the most important aspects of sort of
growth for a lot of different companies now because we're
not we're sort of working in silos, we're sort of
working separately a lot of the time. Do you see
this kind of analytical technology having being used in a
way that can help in the team building elements?
Speaker 2 (23:21):
Yeah, it's an interesting question. I mean, I think what
technology does best on its face is connection. Right, Like
the fact that we're talking right now is not something
that would be feasible about this technology. That being said,
there's a limitation to what it can achieve. I am
sure that there are some smart, creative, capable people who
are working to solve exactly that problem right now.
Speaker 1 (23:43):
That might be something that these sort of tools eventually
evolved to become.
Speaker 2 (23:48):
Right, kind of going back to a question from earlier
that I think for the team to be on board
in how and why certain metrics are being measured. Right,
So this idea that there are overarching goals that the
team has that people are a part of that, that
there is investment on what you are working on and
(24:09):
what you are trying to achieve and move forward, and
that if that investment exists, then tools that accurately and
reasonably support those goals would also be something for a
team to potentially rally around. Right that it is showing
the extent to which everyone is achieving these benchmarks moving forward,
(24:31):
creating new and innovative ideas, and that that can be
part of a positive incentive structure that sort of everyone
has buy in on.
Speaker 1 (24:42):
Yeah, it's a great point. It's also to do with recognition, right,
if people are being recognized through the technology through that
prism of it's not just about judgment, it's about we're
going to say we see what you're doing through these systems.
And that's that's a great point from my previous experience.
In a few other industries outside of digital, the technology
is more used from a management top down point of view.
(25:02):
It wasn't really used to sort of support. It's more
of a sort of like how can we best get
the result, which obviously has its place, but perhaps thisdirects
a lot of the resources that you would have at
the staff level too.
Speaker 2 (25:13):
A lot of these analytics are built to essentially feed
information up to a top level, right, and then it
would be decisions would be made at that level that
would presumably kind of push their way down. And I
think that what I've certainly seen is that that understanding
of communication amongst an organization it just doesn't work anymore,
(25:34):
is untrue. And it is because of these analytical structures
that we have all levels of people who are directly
or incidentally adding data in information to them and then
it maybe is being used sort of on a viewer standpoint,
exclusively from high level leadership, but because that leadership is
(25:54):
making decisions based on it, creating incentive structures based on it,
and the folks who are inputting data into it are
daily participates in it, and they realize that and it
is actually sort of not information making its way down
from on high. It is sort of like immediately getting
to all levels of an organization. So while you have
(26:16):
information from all levels of an organization that are very
quickly going up, it is the exact same way going
in the opposite direction. And I think a lot of people,
a lot of leaders, misunderstand that it is a two
way stream.
Speaker 1 (26:29):
That's a great point, and that sort of brings me
to the next question, which is sort of to do
with how leaders are choosing the technology and how they're
making these decisions. What is one thing that every organization
and leader can do when choosing a tool to measure people.
Speaker 2 (26:45):
I think that a really great question is for them
to ask themselves what their current relationship and use is
of their analytical tools. Do they feel like they understand it?
Are they comfortable with it? Can they ask difficult questions
about how it operates and what it means, and if
(27:07):
that is something that you struggle to do, then I
would absolutely pause and develop a stronger understanding, a stronger
relationship with the information tools that are currently at your disposal.
Speaker 1 (27:20):
That's a great point. I really appreciate that sort of
solidifying what we're talking about in terms of what is
the meaning behind the decision that you're making, What are
you getting from this decision. That's such a great point.
So we've talked quite a lot now about the different
decision making technology and the choice tech is the word
you've coined. There is the sort of a final summary
you can give for business owners, maybe the choosing a
(27:42):
new technology they just about to make that investment. Is
there sort of a piece of advice you can give.
Speaker 2 (27:47):
Yeah, certainly. You know, I think simplistically, what we measure
is what makes us, So be very consider it, be
very cautious, very thoughtful about what you choose to measure,
because it will what is prioritized within your business, within
your organization.
Speaker 1 (28:04):
Yeah, that's a great point. As always, Emily really appreciate
you educating me on a lot of these topics, and
it's always great to have someone with your experience and
background to sort of guide us on some of these
more complex issues, and I wanted to thank you again
for your time. It really means a lot. Thank you.
Speaker 2 (28:20):
Yeah, thank you so much. It's always wonderful talking to
you guys.
Speaker 1 (28:23):
Thank you again, Emily Perhaps remaketh rules dot com. Thank you.
A quick reminder, if you're enjoying this conversation, please subscribe
to the Mental Wealth podcast on your favorite platform. It's
a small action that can make a big, big difference
to us. Thank you.
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