December 7, 2025 • 13 mins
We gave NotebookLM our record breaking blog to see what happened when they turned it into a podcast...
We examine how modern time and motion studies expose hidden waste, translate seconds into savings, and protect sustainable pace. From Taylor and the Gilbreths to sensors and benchmarks, we map the methods, the maths, and the immediate actions that cut costs without cutting quality
• Spotting inefficiency in everyday work
• Time versus motion as separate measurements
• Resource planning using standard times and allowances
• Micro savings through layout and sequence changes
• Example maths for staffing and throughput
• Study types: activity, efficiency, role, predetermined
• History of Taylor and the Gilbreths
• Quantifying financial waste from poor scheduling
• Modern tech: video, sensors, software analysis
• Benchmarking click and collect performance
• Practical ergonomic and staffing changes
• Continuous improvement as the new one best way
Not only will our approach to a Time and Motion Study plot out exactly where you stand versus where you could be, but our analysts will provide practical steps on how to help you get there, saving you time, effort and, ultimately, money
More information on Time and Motion Studies can be found in our whitepaper – our experts’ views into how modern techniques are bringing about new productivity insights. Download here >>
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
SPEAKER_00 (00:10):
Welcome to the Deep Dive.
If you've ever walked into aworkplace, maybe a retail store,
or even an office, and you'veseen people taking just slightly
different routes to do the exactsame task.
SPEAKER_01 (00:20):
Or just waiting around.
SPEAKER_00 (00:21):
Exactly.
Or waiting around for somethingto happen.
What you're looking at isinefficiency.
It's this sort of hidden wastethat just eats away at
productivity.
So today we are taking a deepdive into a classic, but, well,
a fundamentally revolutionizedbusiness technique.
It's known as the time andmotion study.
SPEAKER_01 (00:39):
Aaron Powell And our mission here is really to
understand how this idea, whichis, you know, a century old, has
been modernized to unlock justmassive productivity gains in
the economy today.
SPEAKER_00 (00:52):
Aaron Powell It seems so critical because we're
moving so far beyond that oldimage, right?
The person with a clipboard anda stopwatch.
SPEAKER_01 (00:58):
Aaron Powell Oh, absolutely.
At its core, this study, it'slike a forensic examination of
work.
It separates the whole processinto two measurable streams.
You have the time side, whichidentifies exactly how long a
task takes, down to the tenth ofa second, and then you have the
motion side, which meticulouslytracks all the physical activity
involved in actually doing thattask.
SPEAKER_00 (01:17):
So it's not really about judging the employee,
then, it's about dissecting thetask itself.
SPEAKER_01 (01:21):
Precisely.
SPEAKER_00 (01:22):
But I have to ask, why is that unbiased outside
perspective so necessary?
I mean, if I'm making coffeeevery single day, don't I know
the fastest way to frock themilk?
SPEAKER_01 (01:33):
Well, you know a way, maybe even the fastest way
for you.
But the whole goal of anoutsider is to challenge that
established habit.
SPEAKER_00 (01:41):
The thing you do on autopilot.
SPEAKER_01 (01:42):
Exactly.
When you bring in a fresh,quantitative eye, you just
eliminate all the bias that'sbuilt up from months or even
years of routine.
That objective evaluation findsall this extra movement,
unnecessary walking things, theperson doing the work just
doesn't even see anymore.
SPEAKER_00 (01:59):
Aaron Powell And the result isn't just theory, I'm
guessing.
SPEAKER_01 (02:01):
Aaron Powell No, not at all.
It's practical improvements.
Right.
It means less physical movementfor the employee.
And, you know, critically, itmakes the task uniformly quicker
across the entire organization.
SPEAKER_00 (02:12):
I like that.
It's about optimizing theprocess, not criticizing the
person.
And the material we're lookingat today, it really hones in on
how these modern techniques giveus specialized data that unlocks
those gains.
SPEAKER_01 (02:24):
Aaron Powell And understanding how to apply this
is the key.
That's what delivers theimmediate savings, which I mean
that's what we're drilling downinto right now.
SPEAKER_00 (02:32):
Aaron Powell So let's get into that practical
application.
Once a business goes throughthis assessment, what are the
primary outcomes?
How does this data actuallytranslate into measurable
action?
SPEAKER_01 (02:43):
Okay.
So we generally see the outcomesused in two killer ways.
First up, and this is justcrucial for budgeting in HR, is
resource planning.
SPEAKER_00 (02:52):
Resource planning.
SPEAKER_01 (02:52):
This is where you perfectly match the actual
workload requirements to yourstaffing levels.
It just takes all the guessworkout of deployment.
SPEAKER_00 (02:58):
Okay, give us a quantitative example.
How does the math actually workin a store?
SPEAKER_01 (03:03):
Sure.
Imagine a service counter.
A study finds that serving onecustomer from the greeting all
the way to finishing thetransaction takes exactly 60
seconds.
SPEAKER_00 (03:12):
One minute.
Simple enough.
SPEAKER_01 (03:14):
Right.
But if your store is ahigh-volume hub that gets, say,
120 transactions every hour,well, you can't just rely on one
person.
That means you need 120 deployedminutes of labor every single
hour.
SPEAKER_00 (03:26):
So you need two people.
SPEAKER_01 (03:27):
You need two full-time colleagues right
there, just to manage thethroughput.
And if the study shows it takes90 seconds per transaction,
suddenly you need threecolleagues.
It's hard data guiding staffing.
SPEAKER_00 (03:38):
That's so powerful, it just quantifies the labor
need instantly.
But hang on, if we staffperfectly to that maximum speed,
doesn't that remove any buffer,you know, for glitches or just
people getting tired?
Does the modern study factor inhuman sustainability?
SPEAKER_01 (03:52):
That is a critical question.
And that's where this wholeanalysis moves beyond uh old
school tailorism.
Modern studies absolutely factorin allowances.
Aaron Powell Allowances forwhat?
Things like personal needs,recovery from fatigue,
unavoidable delays.
The goal isn't a continuousmaximum pace, it's a continuous
optimized pace, one that'ssustainable.
SPEAKER_00 (04:12):
Okay, understood.
So resource planning is thefirst big application.
What's the second main use forthis data?
SPEAKER_01 (04:17):
Aaron Powell The second is about focusing
improvement efforts, wherethey'll give you the biggest
return.
Think about it like compoundinginterest, but for time.
SPEAKER_00 (04:26):
Okay.
SPEAKER_01 (04:26):
You know, eliminating some rare 10-minute
task you do once a quarter mightfeel good.
But the real financial leveragecomes from shaving just two or
three seconds off a processthat's done fifty times a day,
every single day.
SPEAKER_00 (04:40):
Those micro savings.
SPEAKER_01 (04:41):
Those micro savings compound so fast into hours
saved every week.
SPEAKER_00 (04:45):
Can we make that concrete with the coffee shop
example?
SPEAKER_01 (04:48):
Absolutely.
Let's think about making alatte.
The analysis might break it downinto what, maybe seven distinct
micro tasks?
SPEAKER_00 (04:54):
Okay, so taking the order and payment, step one.
SPEAKER_01 (04:57):
Right.
Getting the cup, the lid, thesleeve, step two.
Running the espresso shot isthree, frothing the milk, four,
assembly five, handing it oversix.
SPEAKER_00 (05:09):
And where do those tiny savings hide in all of
that?
SPEAKER_01 (05:12):
They hide in the layout.
Is the cup dispenser three feetaway from the espresso machine
or is it six feet away?
Does the barista have to turntheir back on the customer to
use the register?
SPEAKER_00 (05:20):
That tiny rotation of the body?
SPEAKER_01 (05:22):
Yes.
If the frothing station ispoorly laid out, maybe they
spend two extra seconds reachingfor a cloth.
Seconds that, repeated hundredsof times a day, turn into hours
of wasted motion and delayedservice.
SPEAKER_00 (05:35):
It really shows how specialized this feel has
become.
I mean, we're zooming in soclose, you're looking at
milliseconds.
I understand the analysisusually starts by classifying
the scope of the problem first,right?
SPEAKER_01 (05:46):
Aaron Powell Exactly.
The approach is versatile.
You have the activity study,which is that fundamental how
long does this take question.
SPEAKER_00 (05:53):
Aaron Powell Then the broader one.
SPEAKER_01 (05:54):
Aaron Powell That's the efficiency study.
A macro view looking at how timeis spent by an entire team over,
say, a whole week.
SPEAKER_00 (06:03):
Aaron Powell And then there are two highly
specialized types, I believe.
SPEAKER_01 (06:05):
Aaron Powell Yes.
The role study, which quantifieshow specific roles, say a
manager versus an associate,spend their time.
It's invaluable for structuringyour management.
SPEAKER_00 (06:15):
Aaron Powell And the most granular one?
SPEAKER_01 (06:17):
That's a predetermined study.
It's highly technical.
It breaks a task down not justinto skeps, but into individual
elemental movements.
So not pick up a pen, butreaching, grasping, and
positioning.
Analysts can literally calculatethe optimal combination of
movements to eliminate strain.
It's how experts design aperfect workstation before a
single brick is even laid.
SPEAKER_00 (06:37):
That history is fascinating.
Let's transition to the originstory.
This whole field feels so deeplyrooted in the industrial age.
When did this all start and whyas two separate things, time and
motion?
SPEAKER_01 (06:50):
Well, the field actually began with two really
influential but distinctmovements that eventually
emerged.
The time studies side thatoriginated in the U.S.
in the 1880s with Frederick W.
Taylor.
SPEAKER_00 (07:01):
Taylor, the famous scientific management guy, what
was really driving him?
SPEAKER_01 (07:05):
Taylor was obsessed with productivity.
He coined the term soldiering,the idea that workers were
intentionally working slowly.
His goal was to replace thatguesswork with precise science.
His time studies were all aboutfinding a standard time for a
task, mostly to set fairwaytrades.
SPEAKER_00 (07:21):
Right.
He was famous for maximizingphysical output.
I remember the story about himstudying men shoveling pig iron.
SPEAKER_01 (07:26):
That's the classic example.
He observed workers at BethlehemSteel shoveling all sorts of
materials, heavy iron ore, lightcoal dust, using the same
shovel.
SPEAKER_00 (07:35):
Which makes no sense.
SPEAKER_01 (07:36):
Right.
He timed them and realized theload was inconsistent, which led
to fatigue.
So by experimenting, he figuredout the optimal load for a man
to shovel all day was about 21pounds.
SPEAKER_00 (07:47):
21 pounds, no matter the material.
SPEAKER_01 (07:50):
Exactly.
So he introduced custom shovelsof different sizes.
Whether the material was lightor heavy, the worker was always
lifting that optimal 21 poundload.
Productivity shot up, and workerstrain went down.
All based on timing.
SPEAKER_00 (08:03):
So Taylor was all about speed and time.
What about the motion half?
The efficiency of movement.
SPEAKER_01 (08:08):
That's where we meet Frank and Lillian Gilbreth.
They were pioneers in industrialpsychology, and their focus was
on improving the methods ofwork.
They knew speed was useless ifthe method itself was clumsy or
exhausting.
SPEAKER_00 (08:20):
Their work in construction is famous, isn't
it?
SPEAKER_01 (08:22):
The bricklaying study is their hallmark.
Before them, a bricklayer usedmaybe 18 separate motions to lay
one brick.
Bending, picking up the brick,getting mortar, tapping it.
SPEAKER_00 (08:32):
All that wasted movement, what did they
discover?
SPEAKER_01 (08:35):
Using early motion picture cameras, they analyzed
it frame by frame and managed toreduce those 18 motions down to
just five.
SPEAKER_00 (08:42):
Wow.
SPEAKER_01 (08:43):
By standardizing the working height, pre-stacking
bricks, things like that, theycut the labor effort by
two-thirds and massivelyincreased the rate of
bricklaying.
They were always striving forthat one best way.
So that's the key distinction.
Tailor speed, the Gilbrethsminimizing effort.
When those two ideas finallymerged, you got the powerful
(09:04):
synthesis we see today, findingthe fastest, most consistent,
and lowest effort way to do anytask.
SPEAKER_00 (09:10):
Okay, so let's unpack the value here.
Beyond just feeling efficient,why is this so essential for
companies today?
I mean, let's talk real money,because the research provides a
very compelling financialscenario.
SPEAKER_01 (09:21):
It is purely about finding money that is currently
being lost.
Let's use that retailer examplefrom the source material.
Imagine a store that schedulesfive colleagues for an
eight-hour shift.
SPEAKER_00 (09:30):
Okay, so that's 40 deployed hours they're paying
for, standard scheduling.
But after a comprehensive timeand motion study, they discover
something powerful.
The actual tasks, customerservice, stocking, everything,
only required 33 hours ofoptimized labor.
A seven-hour gap in a singleshift.
That's that's shocking.
SPEAKER_01 (09:50):
Seven extra hours.
Every single day that thebusiness is paying for but
aren't contributing to anything.
If you annualize that, you'relooking at over 2,500 wasted
hours a year.
SPEAKER_00 (10:00):
And in money terms.
SPEAKER_01 (10:01):
Well, if the wage is, say, 10 pounds an hour, that
single inefficiency is costingthat business a whopping 25,000
pounds a year.
SPEAKER_00 (10:08):
25,000 pounds.
Just from a mismatch betweenscheduled heads and the actual
workload?
That's a clear, quantifiableloss.
SPEAKER_01 (10:15):
And that is the primary driver.
These studies provide theactionable info that lets
businesses, as they say,discover opportunities.
It's turning lost time directlyinto savings.
SPEAKER_00 (10:24):
That brings us to the present day.
We have this image of Taylorwith his stopwatch producing
piles of paper.
It sounds so slow, so prone toerror.
How do modern methods leveragetechnology to move beyond that?
SPEAKER_01 (10:35):
Well, the meticulous attention to detail is still
there, but the execution isentirely digital now.
Instead of a manual stopwatch,modern studies use sophisticated
tech, often high-speed videocapture and sensor-based
tracking.
SPEAKER_00 (10:50):
And how does that tech change the game?
SPEAKER_01 (10:52):
It's about accuracy and scale.
The software can analyzemicropauses and unnecessary hand
rotations that a human observerwould completely miss.
Productivity experts then applytheir deep operational knowledge
to that data.
SPEAKER_00 (11:05):
So it's not just some generalist timing things,
it's a specialist who reallyunderstands, say, a fast food
environment.
SPEAKER_01 (11:12):
Precisely.
The expertise is layered righton top of the technology.
And crucially, the outcome isn'tjust a data dump.
The suggestions are practicaland immediate.
SPEAKER_00 (11:21):
Like what?
SPEAKER_01 (11:22):
It could be simple ergonomic changes, like moving
ingredients closer to aworkstation, or it could be
major changes, like adjustingstaff numbers down during proven
low demand periods.
SPEAKER_00 (11:31):
I imagine having industry benchmarks must be an
incredible differentiator here,knowing exactly where you stand
and how much better you couldbe.
SPEAKER_01 (11:38):
That benchmarking power is immense.
Take, click, and collect, whichis so critical now.
The best in class retailersprocess those orders in under 30
seconds.
SPEAKER_00 (11:48):
30 seconds.
SPEAKER_01 (11:48):
But studies show that many average retailers are
taking three to four minutes.
SPEAKER_00 (11:52):
Three minutes versus thirty seconds.
A customer absolutely feels thatdifference.
SPEAKER_01 (11:56):
And the efficient retailer gets there not through
faster employees, but through anoptimized process.
The orders are pre-picked andstored right by the counter.
The IT system is slick.
The difference is design, andit's informed by data-backed
insight.
That's fascinating.
It really underscores theultimate promise here.
Using real-world data to deliverthorough insight, not just an
(12:19):
overload of information.
The aim is to make a tangibledifference.
SPEAKER_00 (12:22):
Absolutely.
SPEAKER_01 (12:23):
The modern methodologies, they go way
beyond just documenting what youalready do.
They plot where you stand versuswhere you could be, and most
importantly, the analystsprovide the practical steps to
help you get there.
You save time, effort, and yousave significant money.
SPEAKER_00 (12:36):
So for anyone listening who sees that kind of
financial potential in their ownorganization, exploring these
modern techniques seems like theobvious next step.
SPEAKER_01 (12:44):
It is.
And the deep reviews, the newproductivity insights, and these
methodologies we've been talkingabout are all readily available.
If you're ready to actuallyapply these techniques, we
really encourage you to accessthe white paper online.
It gives a complete view of howthese studies are being used
right now.
And finally, a thought for youto mull over as we conclude.
If Taylor was searching for theone true standardized time, and
(13:07):
the Gilbreths were searching forthe one best way.
Well, does the speed of moderntechnology and AI mean that the
one best way is now constantlyevolving?
Hmm, a moving target.
SPEAKER_00 (13:20):
Exactly.
Does it require continuous,almost immediate reassessment?
That's a dynamic challenge worthexploring.
We recommend you head to thewebsite to continue this deep
dive and access those detailedinsights on how to apply these
powerful techniques.
Welcome to the Deep Dive.
If you've ever walked into aworkplace, maybe a retail store,
or even an office, and you'veseen people taking just slightly
different routes to do the exactsame task.
SPEAKER_01 (00:20):
Or just waiting around.
SPEAKER_00 (00:21):
Exactly.
Or waiting around for somethingto happen.
What you're looking at isinefficiency.
It's this sort of hidden wastethat just eats away at
productivity.
So today we are taking a deepdive into a classic, but, well,
a fundamentally revolutionizedbusiness technique.
It's known as the time andmotion study.
SPEAKER_01 (00:39):
Aaron Powell And our mission here is really to
understand how this idea, whichis, you know, a century old, has
been modernized to unlock justmassive productivity gains in
the economy today.
SPEAKER_00 (00:52):
Aaron Powell It seems so critical because we're
moving so far beyond that oldimage, right?
The person with a clipboard anda stopwatch.
SPEAKER_01 (00:58):
Aaron Powell Oh, absolutely.
At its core, this study, it'slike a forensic examination of
work.
It separates the whole processinto two measurable streams.
You have the time side, whichidentifies exactly how long a
task takes, down to the tenth ofa second, and then you have the
motion side, which meticulouslytracks all the physical activity
involved in actually doing thattask.
SPEAKER_00 (01:17):
So it's not really about judging the employee,
then, it's about dissecting thetask itself.
SPEAKER_01 (01:21):
Precisely.
SPEAKER_00 (01:22):
But I have to ask, why is that unbiased outside
perspective so necessary?
I mean, if I'm making coffeeevery single day, don't I know
the fastest way to frock themilk?
SPEAKER_01 (01:33):
Well, you know a way, maybe even the fastest way
for you.
But the whole goal of anoutsider is to challenge that
established habit.
SPEAKER_00 (01:41):
The thing you do on autopilot.
SPEAKER_01 (01:42):
Exactly.
When you bring in a fresh,quantitative eye, you just
eliminate all the bias that'sbuilt up from months or even
years of routine.
That objective evaluation findsall this extra movement,
unnecessary walking things, theperson doing the work just
doesn't even see anymore.
SPEAKER_00 (01:59):
Aaron Powell And the result isn't just theory, I'm
guessing.
SPEAKER_01 (02:01):
Aaron Powell No, not at all.
It's practical improvements.
Right.
It means less physical movementfor the employee.
And, you know, critically, itmakes the task uniformly quicker
across the entire organization.
SPEAKER_00 (02:12):
I like that.
It's about optimizing theprocess, not criticizing the
person.
And the material we're lookingat today, it really hones in on
how these modern techniques giveus specialized data that unlocks
those gains.
SPEAKER_01 (02:24):
Aaron Powell And understanding how to apply this
is the key.
That's what delivers theimmediate savings, which I mean
that's what we're drilling downinto right now.
SPEAKER_00 (02:32):
Aaron Powell So let's get into that practical
application.
Once a business goes throughthis assessment, what are the
primary outcomes?
How does this data actuallytranslate into measurable
action?
SPEAKER_01 (02:43):
Okay.
So we generally see the outcomesused in two killer ways.
First up, and this is justcrucial for budgeting in HR, is
resource planning.
SPEAKER_00 (02:52):
Resource planning.
SPEAKER_01 (02:52):
This is where you perfectly match the actual
workload requirements to yourstaffing levels.
It just takes all the guessworkout of deployment.
SPEAKER_00 (02:58):
Okay, give us a quantitative example.
How does the math actually workin a store?
SPEAKER_01 (03:03):
Sure.
Imagine a service counter.
A study finds that serving onecustomer from the greeting all
the way to finishing thetransaction takes exactly 60
seconds.
SPEAKER_00 (03:12):
One minute.
Simple enough.
SPEAKER_01 (03:14):
Right.
But if your store is ahigh-volume hub that gets, say,
120 transactions every hour,well, you can't just rely on one
person.
That means you need 120 deployedminutes of labor every single
hour.
SPEAKER_00 (03:26):
So you need two people.
SPEAKER_01 (03:27):
You need two full-time colleagues right
there, just to manage thethroughput.
And if the study shows it takes90 seconds per transaction,
suddenly you need threecolleagues.
It's hard data guiding staffing.
SPEAKER_00 (03:38):
That's so powerful, it just quantifies the labor
need instantly.
But hang on, if we staffperfectly to that maximum speed,
doesn't that remove any buffer,you know, for glitches or just
people getting tired?
Does the modern study factor inhuman sustainability?
SPEAKER_01 (03:52):
That is a critical question.
And that's where this wholeanalysis moves beyond uh old
school tailorism.
Modern studies absolutely factorin allowances.
Aaron Powell Allowances forwhat?
Things like personal needs,recovery from fatigue,
unavoidable delays.
The goal isn't a continuousmaximum pace, it's a continuous
optimized pace, one that'ssustainable.
SPEAKER_00 (04:12):
Okay, understood.
So resource planning is thefirst big application.
What's the second main use forthis data?
SPEAKER_01 (04:17):
Aaron Powell The second is about focusing
improvement efforts, wherethey'll give you the biggest
return.
Think about it like compoundinginterest, but for time.
SPEAKER_00 (04:26):
Okay.
SPEAKER_01 (04:26):
You know, eliminating some rare 10-minute
task you do once a quarter mightfeel good.
But the real financial leveragecomes from shaving just two or
three seconds off a processthat's done fifty times a day,
every single day.
SPEAKER_00 (04:40):
Those micro savings.
SPEAKER_01 (04:41):
Those micro savings compound so fast into hours
saved every week.
SPEAKER_00 (04:45):
Can we make that concrete with the coffee shop
example?
SPEAKER_01 (04:48):
Absolutely.
Let's think about making alatte.
The analysis might break it downinto what, maybe seven distinct
micro tasks?
SPEAKER_00 (04:54):
Okay, so taking the order and payment, step one.
SPEAKER_01 (04:57):
Right.
Getting the cup, the lid, thesleeve, step two.
Running the espresso shot isthree, frothing the milk, four,
assembly five, handing it oversix.
SPEAKER_00 (05:09):
And where do those tiny savings hide in all of
that?
SPEAKER_01 (05:12):
They hide in the layout.
Is the cup dispenser three feetaway from the espresso machine
or is it six feet away?
Does the barista have to turntheir back on the customer to
use the register?
SPEAKER_00 (05:20):
That tiny rotation of the body?
SPEAKER_01 (05:22):
Yes.
If the frothing station ispoorly laid out, maybe they
spend two extra seconds reachingfor a cloth.
Seconds that, repeated hundredsof times a day, turn into hours
of wasted motion and delayedservice.
SPEAKER_00 (05:35):
It really shows how specialized this feel has
become.
I mean, we're zooming in soclose, you're looking at
milliseconds.
I understand the analysisusually starts by classifying
the scope of the problem first,right?
SPEAKER_01 (05:46):
Aaron Powell Exactly.
The approach is versatile.
You have the activity study,which is that fundamental how
long does this take question.
SPEAKER_00 (05:53):
Aaron Powell Then the broader one.
SPEAKER_01 (05:54):
Aaron Powell That's the efficiency study.
A macro view looking at how timeis spent by an entire team over,
say, a whole week.
SPEAKER_00 (06:03):
Aaron Powell And then there are two highly
specialized types, I believe.
SPEAKER_01 (06:05):
Aaron Powell Yes.
The role study, which quantifieshow specific roles, say a
manager versus an associate,spend their time.
It's invaluable for structuringyour management.
SPEAKER_00 (06:15):
Aaron Powell And the most granular one?
SPEAKER_01 (06:17):
That's a predetermined study.
It's highly technical.
It breaks a task down not justinto skeps, but into individual
elemental movements.
So not pick up a pen, butreaching, grasping, and
positioning.
Analysts can literally calculatethe optimal combination of
movements to eliminate strain.
It's how experts design aperfect workstation before a
single brick is even laid.
SPEAKER_00 (06:37):
That history is fascinating.
Let's transition to the originstory.
This whole field feels so deeplyrooted in the industrial age.
When did this all start and whyas two separate things, time and
motion?
SPEAKER_01 (06:50):
Well, the field actually began with two really
influential but distinctmovements that eventually
emerged.
The time studies side thatoriginated in the U.S.
in the 1880s with Frederick W.
Taylor.
SPEAKER_00 (07:01):
Taylor, the famous scientific management guy, what
was really driving him?
SPEAKER_01 (07:05):
Taylor was obsessed with productivity.
He coined the term soldiering,the idea that workers were
intentionally working slowly.
His goal was to replace thatguesswork with precise science.
His time studies were all aboutfinding a standard time for a
task, mostly to set fairwaytrades.
SPEAKER_00 (07:21):
Right.
He was famous for maximizingphysical output.
I remember the story about himstudying men shoveling pig iron.
SPEAKER_01 (07:26):
That's the classic example.
He observed workers at BethlehemSteel shoveling all sorts of
materials, heavy iron ore, lightcoal dust, using the same
shovel.
SPEAKER_00 (07:35):
Which makes no sense.
SPEAKER_01 (07:36):
Right.
He timed them and realized theload was inconsistent, which led
to fatigue.
So by experimenting, he figuredout the optimal load for a man
to shovel all day was about 21pounds.
SPEAKER_00 (07:47):
21 pounds, no matter the material.
SPEAKER_01 (07:50):
Exactly.
So he introduced custom shovelsof different sizes.
Whether the material was lightor heavy, the worker was always
lifting that optimal 21 poundload.
Productivity shot up, and workerstrain went down.
All based on timing.
SPEAKER_00 (08:03):
So Taylor was all about speed and time.
What about the motion half?
The efficiency of movement.
SPEAKER_01 (08:08):
That's where we meet Frank and Lillian Gilbreth.
They were pioneers in industrialpsychology, and their focus was
on improving the methods ofwork.
They knew speed was useless ifthe method itself was clumsy or
exhausting.
SPEAKER_00 (08:20):
Their work in construction is famous, isn't
it?
SPEAKER_01 (08:22):
The bricklaying study is their hallmark.
Before them, a bricklayer usedmaybe 18 separate motions to lay
one brick.
Bending, picking up the brick,getting mortar, tapping it.
SPEAKER_00 (08:32):
All that wasted movement, what did they
discover?
SPEAKER_01 (08:35):
Using early motion picture cameras, they analyzed
it frame by frame and managed toreduce those 18 motions down to
just five.
SPEAKER_00 (08:42):
Wow.
SPEAKER_01 (08:43):
By standardizing the working height, pre-stacking
bricks, things like that, theycut the labor effort by
two-thirds and massivelyincreased the rate of
bricklaying.
They were always striving forthat one best way.
So that's the key distinction.
Tailor speed, the Gilbrethsminimizing effort.
When those two ideas finallymerged, you got the powerful
(09:04):
synthesis we see today, findingthe fastest, most consistent,
and lowest effort way to do anytask.
SPEAKER_00 (09:10):
Okay, so let's unpack the value here.
Beyond just feeling efficient,why is this so essential for
companies today?
I mean, let's talk real money,because the research provides a
very compelling financialscenario.
SPEAKER_01 (09:21):
It is purely about finding money that is currently
being lost.
Let's use that retailer examplefrom the source material.
Imagine a store that schedulesfive colleagues for an
eight-hour shift.
SPEAKER_00 (09:30):
Okay, so that's 40 deployed hours they're paying
for, standard scheduling.
But after a comprehensive timeand motion study, they discover
something powerful.
The actual tasks, customerservice, stocking, everything,
only required 33 hours ofoptimized labor.
A seven-hour gap in a singleshift.
That's that's shocking.
SPEAKER_01 (09:50):
Seven extra hours.
Every single day that thebusiness is paying for but
aren't contributing to anything.
If you annualize that, you'relooking at over 2,500 wasted
hours a year.
SPEAKER_00 (10:00):
And in money terms.
SPEAKER_01 (10:01):
Well, if the wage is, say, 10 pounds an hour, that
single inefficiency is costingthat business a whopping 25,000
pounds a year.
SPEAKER_00 (10:08):
25,000 pounds.
Just from a mismatch betweenscheduled heads and the actual
workload?
That's a clear, quantifiableloss.
SPEAKER_01 (10:15):
And that is the primary driver.
These studies provide theactionable info that lets
businesses, as they say,discover opportunities.
It's turning lost time directlyinto savings.
SPEAKER_00 (10:24):
That brings us to the present day.
We have this image of Taylorwith his stopwatch producing
piles of paper.
It sounds so slow, so prone toerror.
How do modern methods leveragetechnology to move beyond that?
SPEAKER_01 (10:35):
Well, the meticulous attention to detail is still
there, but the execution isentirely digital now.
Instead of a manual stopwatch,modern studies use sophisticated
tech, often high-speed videocapture and sensor-based
tracking.
SPEAKER_00 (10:50):
And how does that tech change the game?
SPEAKER_01 (10:52):
It's about accuracy and scale.
The software can analyzemicropauses and unnecessary hand
rotations that a human observerwould completely miss.
Productivity experts then applytheir deep operational knowledge
to that data.
SPEAKER_00 (11:05):
So it's not just some generalist timing things,
it's a specialist who reallyunderstands, say, a fast food
environment.
SPEAKER_01 (11:12):
Precisely.
The expertise is layered righton top of the technology.
And crucially, the outcome isn'tjust a data dump.
The suggestions are practicaland immediate.
SPEAKER_00 (11:21):
Like what?
SPEAKER_01 (11:22):
It could be simple ergonomic changes, like moving
ingredients closer to aworkstation, or it could be
major changes, like adjustingstaff numbers down during proven
low demand periods.
SPEAKER_00 (11:31):
I imagine having industry benchmarks must be an
incredible differentiator here,knowing exactly where you stand
and how much better you couldbe.
SPEAKER_01 (11:38):
That benchmarking power is immense.
Take, click, and collect, whichis so critical now.
The best in class retailersprocess those orders in under 30
seconds.
SPEAKER_00 (11:48):
30 seconds.
SPEAKER_01 (11:48):
But studies show that many average retailers are
taking three to four minutes.
SPEAKER_00 (11:52):
Three minutes versus thirty seconds.
A customer absolutely feels thatdifference.
SPEAKER_01 (11:56):
And the efficient retailer gets there not through
faster employees, but through anoptimized process.
The orders are pre-picked andstored right by the counter.
The IT system is slick.
The difference is design, andit's informed by data-backed
insight.
That's fascinating.
It really underscores theultimate promise here.
Using real-world data to deliverthorough insight, not just an
(12:19):
overload of information.
The aim is to make a tangibledifference.
SPEAKER_00 (12:22):
Absolutely.
SPEAKER_01 (12:23):
The modern methodologies, they go way
beyond just documenting what youalready do.
They plot where you stand versuswhere you could be, and most
importantly, the analystsprovide the practical steps to
help you get there.
You save time, effort, and yousave significant money.
SPEAKER_00 (12:36):
So for anyone listening who sees that kind of
financial potential in their ownorganization, exploring these
modern techniques seems like theobvious next step.
SPEAKER_01 (12:44):
It is.
And the deep reviews, the newproductivity insights, and these
methodologies we've been talkingabout are all readily available.
If you're ready to actuallyapply these techniques, we
really encourage you to accessthe white paper online.
It gives a complete view of howthese studies are being used
right now.
And finally, a thought for youto mull over as we conclude.
If Taylor was searching for theone true standardized time, and
(13:07):
the Gilbreths were searching forthe one best way.
Well, does the speed of moderntechnology and AI mean that the
one best way is now constantlyevolving?
Hmm, a moving target.
SPEAKER_00 (13:20):
Exactly.
Does it require continuous,almost immediate reassessment?
That's a dynamic challenge worthexploring.
We recommend you head to thewebsite to continue this deep
dive and access those detailedinsights on how to apply these
powerful techniques.
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