hello and welcome to datum this is

season 2 episode 6 and today is a byte

and we're talking about the data side

hustle Ravi how are you I'm not too bad

I'm fresh off watching Game of Thrones

so I am medium that's my reaction my pop

culture reaction for today it's not been

a great season I hear I mean it's

basically being like this the soundtrack

and the cinematography and the if you're

a film buff and you quite enjoy like ah

they're sort of angles and all that

stuff it's been great like the

soundtrack the score this sort of

effects and like where the cameras been

and there's some of the shots been

incredible but yeah the storyline just

seems rushed at the everyone's just I

think the star the season I mean some

people is like honestly I just wanted to

finish and be like ah there we go done

and and there was a Starbucks cup and

the water of course - - very uninviting

friendly references in the Middle Ages

or Game of Thrones is that yeah right

exactly

good stuff good stuff so ya know we're

back we're back on the ground after a

short break and we are half the hot off

the heels I don't think we're hot off

the hills but yeah we're following up

from the last episode on behavioral

design which we sit quietly released

along with our new branding yeah yeah

exactly I think the switch over to the

new brand and then we just didn't really

push this episode so hard so those of

you that did listen thank you

it was reading a much feedback on it I

think that that was in in lieu of the

the quieter release of this one yeah but

I think the content recovered and that

was good fun like we had a few like

tangent rants and things like that but

it was good overall over I think we

covered a lot of ground on in the

episode I think that's definitely one we

definitely mentioned to come back to in

about six months time and see what's

changed especially our opinions exactly

I think we did it as a bit as well

because I think it needed that sort of

precursor episode to sort of take you

through yeah the realities of it and

then when we come back to it as a buy it

will be a very different topic where

we'll be talking about the things so

think of it as part one this is

definitely not something that we're done

with we'll come back to it completely

completely and today we're talking about

the data side hustle whatsit danger side

hustle Ravi I think so this is this is

your term right this is your temper

right the hobby ism and the things we do

on the side developes roaring skills are

just a sort of a pet passion project to

follow along with right so for for you I

think that's quantified self right like

that's your thing it is indeed yeah I've

had a very quiet few actually I'm gonna

say years with I haven't put much very

much that the open opens fear compared

to I think three or five three or four

years ago when I was it's pretty hard on

it in the public sense and yours is

football right correct yes football

analytic system was always my route into

into the world of data and tableau and

who I am today in a weird way right

because it's this addiction I had two

football manager they'll champion manage

of the game which then translates into

is like a moment of oh god I can do this

for a living and there is a faction of

the sporting industry that can benefit

from data so that that's definitely my

passion project it's something I don't

do as much as I used to I used to blog

semi actively on a personal side blog of

mine I love my Twitter followers are

from those days and it's sort of tied

down a bit but then I still produce some

visualizations in my opinion a bit

better than I used to and it's quite fun

to see when you scroll down to my the

bottom on my tablet public profile oh

yeah no it's good to see sort of your

progression as you go on will actually

come on to this specifically I have to

say you mentioned something about

football manager I don't know many

people who play that game who armed

addicted yeah

for reference football managers it's

like a football simulation or for the

Americans a soccer simulation game yeah

we you don't actually play the game like

in FIFA night you just simulate the

progression through a season right you

know yeah it's just it's just got more

and more layers to it as you go on but

you can play it as a really simple

player below you just assign the best

players set them up in a formation then

let them play and win all the games but

then you've got like you set your own

challenges like I want a bit of build a

dynasty or build a team that's as

average age of 25 and you basically you

doing all the facet things within a team

you're doing the sort of financial

management the training you then

cut wires it's just good fun you're

getting sacks and fired and all this

stuff I think even they've even got

Briggs it in the game right so brakes

the day comes in and then you can't sign

foreign players it sounds like the hide

side hustle in itself completely you

know completely there's so many people

that have like that could on their CVs

like taking Forest Green Rovers from the

National League to the Champions League

in seven years for example but that's a

lot of time investment okay okay and

it's funny ghost coming back to this

sort of idea of a side house I think we

both we both have these side hustles a

because I think we're passionate about

them but also I think it's because we

have a sort of an inherent interest in

this area so you sort of talked a bit

about champ temperature manager is it

managed its full manager no football

manager net okay great you've talked

about football manager and for me

quantified self and is you know really

started when we we had things like

fitbit's coming to play I kind of

when fitbit's came out I envisioned this

world where you'd walk around with a

sort of health device on your wrist and

I was always fascinated about the data

that you could sort of get from these

devices is taking a while to get to

where we are today with Apple watches

that can you know do ECG readings off

your wrist and but what's been

fascinating is that I discover this

world of people who are doing way more

interesting analysis than just step

counting and using data some of it

probably mostly manually collected but

it's been a really interesting kind of

subject because it's involved a lot of

technical skills and soft skills so

that's the sort of would draw me drew me

into the quantified stuff I was I was

getting familiar with data

I found his hobby that was data oriented

and at the same time I was seeing sort

of different soft sides to data are

seeing the kind of you know

psychological effects of monitoring

yourself and in viewing the quality of

your life now that's very interesting in

terms of being drawn into Footwear lytx

it's it's it was always money ballers

the concept but then the second you

started figuring out and looking at the

data that actually was collected from

for matches by companies like op tarrant

all these other data providers you

realize that they're the granularity was

so important and then you start thinking

about like hang on can I spot players

that people were aren't no I do I do I

can I start looking at Teamsters can I

see patterns that

you might not be able to see because

you're watching one match and there's

all the anecdotes about Scouts going to

watch players right you're going to

watch a single planned during a 90

minute match you'll basically focus on

that one player and what they're doing

whereas data then allows you to watch a

hundred thousand players at one time and

just say set KPI star saying if they're

hitting this consistently then you know

we look up and listen and start looking

at the video behind that exactly exactly

and but there's something to be said

about sort of the aggregate nature of

that right you find people who are on

paper technically good but actually when

you go see them there's a softer sides

to the finesse of the way they do it

that Christgau I think gives you an edge

over sort of the big the big data

approach right it's yes that they're

making those tackles and you know

scoring those goals it's the way they're

doing it that maybe lead you to believe

it they can do it at a higher standard

in in a more sort of competitive play so

you mentioned your sort of English

starting with Fitbit yeah and and going

from there like I remember we had a

conversation recently where you were

like oh man step , so Bush Lee that's

old-school stuff no one looks at stepka

anymore have you seen that development

like how you understand a look at

wearables or yes it's interesting

because wearables themselves are trying

to do more as well so there's this big

push at the moment to do with well being

in healthy healthy mind and yeah in

mindfulness exactly and the only thing

that these devices can really do is

remind you to do them and sort of nudge

you to kind of do them more often and

but in in in real terms the technology

hasn't really developed to really sort

of advance State I think if you take an

Apple watch or a Fitbit at their heart

they're just doing what they did you

know three years ago they're doing it at

better doing it a lot better at more

increasing levels of a granularity if

that makes sense

yeah the other thing is accuracy as well

so where as a step counter three years

ago was a guesstimate and today step

counts are a little bit more nuanced

they can detect things like swimming

running cycling and so on and so forth

so they can more accurately detect

activities at your up tee but the

classic example I always give is that

let's say you took your Apple watch off

and you you left it in a drawer for a

day and then the next day you put it

back on it would probably nod you and

say hey yesterday was really

unproductive day yeah do you want to do

stuff today

has no awareness of the fact that you

weren't wearing it and the prompts they

give you kind of punish you like the

classic one is you know ten o'clock you

get a notification from the Apple watch

saying stand up yeah yeah or go for a

short brisk walk you know this is kind

of like hey you're not doing what I've

been programmed to tell you to do do you

want to do it right now there's no

there's no context say hey you know I'm

sitting on the sofa maybe now isn't the

right time but the next time I get up

maybe that's when you should notify me

and tell me to go on a brisk walk could

do something because you know that's

probably a better time right on the sofa

I'm not going to get up I always find it

funny when you're sat in the room with

Apple watch users and it's like 10 to

the next hour and everyone sort of look

so their watch yeah exactly exactly it's

like everyone's part of the same sort of

machine and yeah there's not really much

sort of customization but I could be

sort of digress I think going back to

sort of you know the value I found from

it is that kind of tackling these soft

questions in and understanding how the

data doesn't necessarily tell the full

picture

now that's something I've really found

valuable in my professional life it's

something that I learned purely through

qsm I learnt it quite simply because

what I did is one of my sort of things I

do all the time is track my music say

since 2009 I'm coming up to a decade

last.fm exactly exactly in July I'll

have a decade's worth of music listening

history available to me through a

service called last defense and about

three years ago I did a very basic vis

joined up all the dots it's just bad

before Tablo is really kind of you know

as big as it is now I guess and I used

all tricks to bring the day together I

could probably use tablet prep for that

now and what was it one hopes their

hopes there I didn't connect to the API

to I can't connect to the API but I

could use it to sort of connect the

datasets together which is a

predominantly allocating say I'm

downloading lots of different datasets

from different services in all tricks on

once I have them I have what so

essentially like a music metadata

library so each track has its own

metadata and I'm basically just joining

that daystrom to my music listening

trends over time and then visualizing

and tablet I tell you one way I'll tell

you one of my big bugbears with

just a lot of qsr data in general yeah I

think I just goes back to when I had my

Fitbit HR so my my main two motivated

for buying a Fitbit was first of all I

wanted to track my heart rate and step

count and third of all I wanted to sleep

now when I had a Fitbit now but when I

had my Fitbit it was like notoriously

difficult to get your super granular

second-by-second data out like never

disgustingly know exactly and it's like

I'm buying this wearable I'm tracking my

data I want to know at the lowest level

of granularity what I can get but I

can't even see like how many steps I did

in a minute I can't go into granular and

bring it back up only thing I can do is

look at the Fitbit dashboards and I

think this is where going back to your

earlier point about the data collection

and the development of wearables one of

the big things I've seen parsley is the

slowly gained better at visualizing this

data right I think Apple do this quite

well I think we've seen a few people who

have criticized the use of rings but I

think the rings work well because you're

not looking at that granular number

you're looking at whether you're hitting

your target and the completion to goal

is like am I at that completion to go am

i at 100% yeah and you can see that with

the ring that's fine but when you look

at the actual visitors behind it you can

actually find out whether or not it's

able to you know pick up those

visualizations so if you look at the

actual app itself the the chart the bar

charts and whatever the distance to go

on giving that over you at the last 7

days etc they're actually pretty good I

think and that's getting better as well

alongside the the granularity of data I

think you've actually pulled some of the

Apple data out using altars right I have

I have it so this is this comes down to

philosophy right so Fitbit they don't

really have much they don't have an

ecosystem to lock you into so that's one

of the reasons they're not prepared to

just easily give you the intraday data

intraday data is minute by minute below

of what's happening on these trackers

they actually do collect it at that

level but what they do is they aggregate

it up to the minute because if you think

about it from a second point of view the

databases would be humongous humongous

yeah absolutely so they they aggregate

it to the minute and they store it away

and in the apps you see kind of readouts

based on a minute-by-minute glow but

in reality when you export it I think

the easiest form to get is a day-by-day

bleh now what's interesting about the

Apple ecosystem is that because it uses

a previously first model I think it's

actually one of the best systems because

essentially what happens is your device

is the database

mm-hm and when I export a data from

Apple health the it collects data at the

most granular level that the device

that's tracking the information collects

it at so if I think about my phone my

phone will count things like steps as

granular as every second so it will say

okay for this second Tim did this many

steps okay hmm

I'll use a heart rate monitor that's

capable of recording multiple readings

per second again the heart rate monitor

will record to Apple health at multiple

readings per second and but something

else might only do it per minute so

there's no sort of specified level of

aggregation in Apple health because of

that my Apple health library is about

three and a half gigabytes when I export

it it comes out as a JSON readout so

it's it's a good thing that this is

synced to the iCloud because it media

across devices you can kind of carry on

but it's an enormous wealth of

information and most of the stuff on

there is heart rate readings because my

Apple watch has been tracking that and

then I also do a lot of sports and my

chess track has been tracking that so

this is something that's getting better

and better over time going back to my

earlier point about accuracy and

fidelity depending on the platform you

choose they have various reasons to give

you as much binary information as they

can and at least an apple sense I know

so to an extent Google as well they're

actually pretty good at giving you

access to the raw data because what

they're providing is a platform that

other apps can hook into and in order to

do that you need to kind of be as open

as you possibly can now the downside is

that you know this stuff is on your

device it's actually incredibly hard to

get it out of your device and that's

what you're doing and like any sort of

yeah I've always criticized exports from

services they're never that useful

because they come in formats that the

everyday but just as one yeah yeah has

no clue what to do with like XML JSON

and CSV you might be at a push should be

able to do that but then you get

ridiculously size CS vizsla q no gig and

a half that you can't parse in Excel or

something you know so this is a really

nice

I think this is nice that good back in

syphilitic so one of the reasons I

picked up on this as a side hustle is so

providers like Opta and more recently

got pros own and stats both prisons no

stats as a company so all of these

companies do collect all this data so

for example if you look at track AB

which is tracking data of a player which

is using multiple cameras on a stadium

and they look at the number on the back

of a player's shirt and mapping it back

to the database that's taking data at

every point zero to five of a second so

it's like every quarter or a second it's

taking so you get four data points per

second and it's funny when you whinny

and that comes in a format which is dot

dot and an XML and then you can opt to

data at the F 24 or which is the event

level data they've got a new one which

is event plus a few other metrics that

comes in XML format so if you think

about the people that work in analysis

of clubs until more recently it's

generally been sports scientists right

so people have done physiology they've

done sports science but they're never

really been people that use computers

like yes they've done coding because as

part of sport science they do some

coding on matches someone to help to do

it where they tag events and clip videos

together to say okay here's where we had

a good shot a fast attack here are the

key events in a game so when you're

playing back a 19-minute matched is to

your teammates or the players and all

the staff they would just quickly see

what's going on now when I start working

with the public data I saw again it was

aggravated because you know opt arose

selling this as a business like it's

it's a couple of thousand multiple

thousands of pounds to buy the the

access to the data either by API or

exports whatever you want able to

service that and one of the most

interesting things we found was like

well these people who are working clubs

yes they've the idea they have the the

grounding in the game they understand

the technical aspects but they're not

really day to people right I've been

going to the October Oh forum now this

was my third or fourth one this year and

it's it's fascinating to see like the

amount of statistical analysis that goes

on people using R and Python and they're

combining all these events together and

finding patterns and telling stories

with with the datasets but well they're

fundamentally no one ever talks about is

the

Kent yeah how are you passing the data

how are you bringing all these things

together what is the function what's the

best way to show this back to a coach or

a player to get them to get that insight

and this is the sort of the ground that

I find myself in like increasing

thinking like building that platform the

clubs that I've worked with or know of

there's only a few doing it in the right

way where they've got a database they've

got a data processing platform that

they're doing in-house it's not a second

secondary company and then they're also

doing some bespoke things on the front

end

that's the club's doing that a few and

far between but I think that that is

changing given that you know that the

game is changing right exactly exactly

exactly and just going back now to a

high level it's funny because our side

hustles have actually given us this sort

of unique ability to take this data and

it's allowed us to sort of dig into this

discussion so from your perspective I

think that's one of the things you bring

to the op2 forum when you go and you go

there because you actually critique the

backend systems you know a lot of a lot

of people buy the data but don't

necessarily you know they have the data

in Excel that you know they're kind of

working it hard and working at the

hardware sorry and in contrast you know

by doing what you've done you've

actually been able to go and critique

this this this process exactly and

that's exactly what my overarching point

it's like this the this sort of

surrounding way we're just sort of an

interest and now I can sort of I feel

like it's being a bit more intelligently

not just about the data and how to pass

it and the issues that there are

infinite but also saying well what

happens if you go beyond counting stats

one was before you go beyond saying we

took seven shots in this match like when

did you take them was the game state

where you two goes up or one go down

like how does how is the team impacted

by those things and then with the

tracking data fascinating because this

is such granular data and if you think

about football as a sports or soccer as

a sport it's a game of spaces and when

you start being able to quantify those

spaces and say and detect patterns and

spot things that players do or teams do

or you know and then tag that to events

that's when you start getting really

insightful stuff and that's what's

exciting for me at least when you start

bringing those things together and

getting that insight in you start having

those really interesting conversations

with coaches on a level that they

understand then they can see beyond just

like what

people generally get out tracking data

all they do is plot the X and the Y's

and watch the games but with scatter

plots basically which which defeats the

object in some way right right exactly

and but I think that's one of the things

I think side hustles do is they because

you're more passionate about the subject

let's take football analytics yeah

naturally football about it naturally

football about analytics you're not

passionate about football analytics here

yeah and so that passion actually drives

you to a deeper level understanding

within that area maybe more so than

let's say you know some of the sort of

the dryer stuff we do on my day to day

work you know you know with clients or

or with our own businesses right because

shrink your own business can kind of

suffer from this several issues first of

all access you don't get as much access

to data internally sometimes because of

governance and bureaucracy and so when

you have ideas it's really hard to run

with them because you have to make sure

you've got everything in place right

yeah you just want to prove the value of

something by experimenting and

innovating but that you don't

necessarily get that in business now the

other thing is that it naturally

develops your skills to be able to

communicate the challenges you're having

I think one of the first things I

learned when I was working with

quantified soft data was that bringing

these things together wasn't a simple

thing like I had to really understand

that if I was going to make my music

data and my moves location data work

well together I had to understand at a

very granular level you know what I was

doing in each minute so I built at this

minute level data set and then I was

able to say okay in this minute I was

generally here and this is what I was

listening to and then I was able to sort

of map those two on to each other and

then and go from there and it's gotcha

it's a really really important thing to

start to understand and having that

passion allows you to ask deeper and

deeper and deeper questions to the point

where you realize that actually there is

no end to what you can ask there is no

end to how you can interrogate something

and when you apply that back to you

everyday you suddenly realize there's so

much more you can do with you everyday

data agreed agreed and I think you

mentioned this earlier when you were

looking at your quantified self

attentive through Alteryx yeah it sort

of exposed you to the download tool and

things like this and

that definitely how about something I've

done so when I started using ultrix I

learned so much about things like with

detour to like control parameters like

having the basically the painful things

when you're trying to combine and pivot

and pass XML from a really ugly thing

and try and create this repeatable

process which is a macro that does it

what works I think one of these this was

like one of my train projects either an

hourish commute I'd spend an hour in the

morning just like tinkering with this

sort of thing and getting getting as far

as possible and basically ended up with

this working prototype until I got to a

match where it was nil nil so basically

I I had one of my pastors saying if

there's a goal pass out but then it was

a nil nil there were no girls and there

were no assists so basically it was like

well I can't do I can't pass as much so

I decreed it exactly so I did a detour

tool to be like is there a goal is there

an assist and then if not do a detour to

go like this way or this way and it's

like so many of those small nuances

about working with data I was able to

work out through a passion like if I was

working with I don't know website

visitor data and trying to figure out

how to pass those I would have been

asleep and I would have moved on really

quickly like I'd have basically good at

working and left it I wouldn't have

tried to make this read perfect

efficient macro that does it

automatically I wouldn't have thought

about it in such a way where I'm like I

really want to get this done because of

X Y and Zed and and then the finally I

think you're at your point on wanting to

do better because it's a pet passion and

trying to drive the other people around

you further that's definitely something

I've done like I think I mentioned my

crusade on long for long scanned Y

scatter plots right that would never

have happened if I wasn't like getting

angry at people posting wide scatter

plots on Twitter right like we've never

written that I wouldn't have thought I'd

educate these people about why it's

wrong because three years ago I probably

would done the same but now I'm bit more

getting a bit more formalizing database

breast practice and the reasons behind

doing things I feel I'm on a place to

educate that back to people and that's

the thing and it's funny because that in

itself is is another skill that you pick

out of it's a you you learn actually you

kind of become humbled by the experience

right you go you

and I think you go in with this sense of

confidence when you're passionate about

something yeah I know I know everything

about football I know everything about

quantified self I've got a Fitbit you

know and as you go into it you slowly

start to realize oh wait I can't just

export this data and you can then use

someone tells you are there's an API and

you go okay API I wasn't expecting to

have to do this this way and you start

working with it and it humbles you kind

of shows you it kind of teaches you to

give these challenges the right level of

respect and that in itself is portrayed

by the way you then communicate it to

people you you treat you treat the topic

with respect and therefore you your

mooring encompassing about bringing

people into your sort of your your skill

your fold and kind of making them

understand the challenges that you go

through completely and I think that's

that's definitely fueled my recent like

M change in tone has been about a lot

about like actually does matter a lot

about who the player is like what

they're doing and all this stuff like

you can't just purely base something on

you know statistics or numbers you can't

just say one of my favorite players and

Cole skews is the most pivotal player in

the team but you can see that you can

see that without him and the team in

Ipswich he's a lot the team a lot worse

off but also you gotta take into account

his fitness data which we don't have

access to do you don't see him in

training you don't see his attitude

don't see how he changes and the things

he brings to the team like all of these

different things you can't really

quantify it's a lot harder to quantify

and that's what coach brings to the

table again going back to our day-to-day

we go into companies and we try and

solve their problems with limited to no

knowledge of the field we don't have

that depth of knowledge company and I

think those pet passions these data side

hustles really help you to realize like

you're not an expert in those things and

you know it's you're really what you're

doing with these things is continuing

your learning based on something you're

passionate about and seeing what else

you can pick up along the way I think

that's there's one thing I remember an

experience where I I presented to the

London quantified staff London group the

first time I presented I really didn't

know what to expect

and say I just I just you know did a

classic talk about music and I talked a

lot about ultrix I kind of felt like I

was selling tableau nautics at the time

I was a year into my journey so I was

trying to kind of showcase that a little

bit and I know the first few questions I

got my first question just just knocked

me off the floor and someone just asked

me like so why are you doing this

um at the time I was like in my head I

was like because it's cool okay yeah

exactly

I'm a what I've been listening to for

the last eight years like that's cool

and in my head I could hear myself

saying now that's not that's not the

right response to come on like wow and

and what I realize is okay so why do I

think it's cool so I drilled into that

question in my head and I just started

talking out loud here okay so this is

cool and then I explained like listen

you you have this idea of listen to

music and there's a really simple thing

I always say yeah someone what do you

listen to you they come back with two or

three artists okay

in reality you listen to like a plethora

of artists you're not the sum total of

two artists two or three artists and the

exact opposite someone goes on I'm

really eclectic right and more often

than not when someone says that and I'm

able to look at their data and something

that last.fm they're actually not bad

eclectic there's like a hidden secret

between what they listen to and I'm only

able to see this through the attributes

of the individual tracks that they

listen to it actually arrived at sin na

you don't you're not a collector at all

you happen to listen to all these songs

but here's the thing they have in common

they're all acoustic they'll have the

same level of energy and all these

attributes are measured by other

companies but I'm actually able to sort

of draw the common the commonalities

between what they think is eclectic and

what is actually the same so what you've

described this eclectic is actually one

thing it's not at all and so just just

having that discussion that in public

was was the cool thing and I'd realized

yes okay that is actually why I do it

you know understanding it underneath the

skin what's going on yeah yeah I think

it's the quantified self is really

interesting like intersection of you

sort of sit there me like you know why

am I doing this like it's funny like

everyone's like yeah but why are you

collecting all this Fitness data about

yourself yeah exactly and so well in

some ways it's actually it's changing my

behaviors because you start looking at

these things in LA I did less than last

week or you start doing these like you

compete with yourself and others but

also it's it's and I think that one

the key things you mentioned that's

really interesting is like the patterns

between people and the insights you can

find with that and that that then goes

back to like if you're able to do this

within an organization like you're

saying right we're not gonna look at x

y&z we're actually gonna be actually

only care about this week what you're

doing outside of work right yeah let's

let's focus on that and then we I want

you all to come back to use the tools

that using your workplace and show me

something interesting okay exactly and

it's like my almost like this five to

ten percent time right a five percent

time whatever you might call it where

you able to give back to someone and

because inherently you're giving someone

time back to develop something which is

relevant and you're saying use these

tools because you're using the tools

that you'd use every day anyway it would

just end up being like a benefit in kind

no maybe not today or tomorrow but in a

month's time you're like oh I worked on

that because I had to change this data

set from this ugly thing to something

else and then I visualize it like this

maybe I can use a similar visual to

portray this finance data when we're

trying to compare seven different

products right and and that's and that's

that's one of the that's what also one

of the sort of unique aspects about it

is that I always called quantified self

as digital narcissists because that's

totally what you guys are it is exactly

that but I hate gnosis the term gnosis

because it sounds so negative yeah but

it's funny because like why wouldn't you

take an interest in who you are and what

makes you you right and yes at a high

level you have no you think you know

what's going on Randy like you think you

know what you did yesterday an

incredible amounts of data but actually

you're very transit humans very transit

beings we focus about them now and the

future we have although we like to think

we reflect on the past we don't actually

keep that much in the past apart from

painful experiences that's the current

that's what we that's what we carry

forward and say the good stuff just kind

of blows on by and so you know it's

having this understanding of how you

work and the transition I think is

really interesting and I think in a

business context this is absolutely the

same skill that you need to have but

you're a play and not to yourself but to

your own business and so it's the same

sort of

quizzes of nature that you'd applying to

yourself if you apply it to your

business and you create a culture where

people can do the same thing then people

start asking really fascinating

questions about the way you do things

rather than just assuming that that's

the way they're done

the questions will always get better

right though that I think I think Tom

our boss always talks about this concept

of she has one question a day publicly

out loud no matter how difficult or not

so difficult it might be yuge in your

questions inherently just get better and

better right and I think that that that

holds true with quantified self even the

whole truth Footwear listings the more

you dig into this stuff the more you

find out I think one of the big big like

topics these days is all about

automation right and automation is a

funny one because the quantified self

you always talk about active and passive

right right right

and I think for the last six months I've

been using an app called reporter and in

the last like I'd say two or three weeks

so report is this app done by a guy

called create by Nicolas felt Ron who

had these incredible incredible reports

about himself basically is a yearly

report about his year based on data in

infographics and one of the tools he

used to do this was a app called

reporter now I started off using this

quite enthusiastically oh yeah this is

great like a month affair yeah a month

on them just like whenever I get a ping

so it picks six random times for damage

like oh yeah I'm just like do I need to

go through I don't know just like

sporadically and I'm just gonna

basically think about it in years time

and say right let's look at the

frequency of reports and also let's also

look at the fact that the thing now I'm

now trying to get out of it is when am i

reporting and also why exactly when am i

sending these reports myself and then

comparing that to the passive data

collection that I have right like steps

my heart rate all like I do a Twitter

history when am i tweeting all of this

stuff and it could combining all that

together I think it would be more

interesting but I think active you

passive is a really interesting

conversation as well yeah especially

with quantified self and again in

business I'll reiterate this again it's

you know the the the thing I write the

reason I always harp on about passive

collection so active and passive what

Ravi's talking about is essentially this

philosophy in quantified self which

I think I don't know I don't know if I

came up with it but I think I did I read

it from somewhere and the idea is that

active is when you're physically

collecting the data yourself so you're

getting a ping on your phone you're

filling out a form and then you're

storing the data somewhere massive is

where you're not having to do that

something is doing it for you in the

background so for me when I listen to

music I don't have to log that somewhere

there's a service called last.fm which

is doing it for me scrub all exactly and

I've set up another passive way of

tracking when I'm at home and not and

the way I do that is I have Wi-Fi router

that's hooked into if this then that and

so every time my phone or my watch and

my laptop connects to the network it

loves me so I have a pretty accurate

reference for when I'm at home and when

I'm not at home just based on when my

device is connect to the network because

I'm never at home without one of those

three devices right say yeah that that's

a very good active and passive way

rather than me saying oh hello

Foursquare okay swarm okay let me check

it with Amazon - button be like I'm home

let me press this button let me press

this button right exactly it's like the

thing about this Wi-Fi collection is

that yes it might over report when I'm

at home because you know I might leave

my phone at home and go out to the shops

very quickly but my watch will

disconnect and connect so I've got I've

got such a good level of accuracy there

in aggregate compared to me manually

maybe forgetting one or two times and so

the quality of the analysis are then get

from that is much higher same with

location tracking I don't do that myself

I have a map that does it and it doesn't

have to tell me exactly where I am but

it just needs to capture the general

trend and when you have that quality of

data it's much much richer now the thing

where you know passive can't work is for

feelings and emotions because correct

going back to the weight you're talking

about when you track when you do active

forms of tracking what it tends to work

better for and when you're trying to

measure sort of your mental health or

correct paying or things that are you

know things that trigger and therefore

you think let me monitor this right and

over time when you become fatigued what

you end up doing is only recording them

that more negative aspect so if you sort

of tracking your mood and you have to

log it manually what ends up happening

is you only ever log it when you're

unhappy because you want to make sure

you've got that as a reference point but

you don't like stop in the middle of ID

and a roller coaster I'd say let me log

this while I'm going up and

[Laughter]

this trough right this feels great but

you're not pulling out your phone and

and lugging it straight away in fact you

just you just enjoying yourself so

active passing tends to suffer from this

at a very negative skew where you

capture more about the bad stuff than

the good stuff because the good stuff

for wide why would you mom super so I'm

actually having quickly come where

reporter and it's honestly like so what

am i reporting and we're putting when

I'm watching TV traveling texting or

chatting well mostly when I'm at home

well smiled like yeah and my mice might

because there's also like you can turn

off when you sleep when you wake up so

you've got questions to ask on you wake

up about your quality of sleep and also

when you go to sleep about your day in

general and your feelings towards it and

again that's so sporadic I have so few

data points on that because it's like

before you go to bed how am I gonna

press that button probably not because

I'm doing other stuff I'm like I'm busy

or I'm just you just like flat out and

I've just gone to sleep like but yeah I

think your point on when you do it I

think that that's really interesting

because um it's definitely something

people use in mental health like to

track behaviors and how you feel just so

you know psychiatrists or psychologists

have that information to go back to

saying like okay cool so when I'm around

Tim I'm always feeling really depressed

right for example nice and that sort of

feeling and tracking just to help people

be more aware of their emotions it does

help it does help yeah exactly and so if

I take this back to sort of business

context where this has really helped me

is that you know whenever I'm talking to

clients about the way they collect their

data and how they bring it in yeah I'm

always leaning towards the more passive

systems because I inherently know that

for the things that they're trying to

track apart from the qualitative stuff I

mean this is actually the more valuable

side of things so look if you can just

spend a little bit more time getting out

of your form culture and into your sort

of you know sort of automatic data

collection and just have have systems

that collect data on behalf of people so

a they're more likely to input when they

need to because I know that that quality

of data isn't there going to be there

inherent in a good way

and you're also taking a cognitive load

off the user for having to remember to

do a whole bunch of other stuff so I

find it easy to track my mood because I

don't have to

like all these other things I have a

think about 35 different things that I

could track passively and those are 35

things I don't have to manually track

and that makes it so much easier to

track one simple thing like say my diet

when I'm eating or something because I

stole my good way of tracking food

automatically yeah I think that the best

way I found is MyFitnessPal barcode

scanning so it has a really good barcode

database so you can scan something

you're eating and it will grab the

calorie data off its own database and

input it to health for you which is

great

mm-hmm but I still have to do the manual

task of opening my camera apps try to

scan in the barcode and I'm hoping this

is one of those features that Apple

Sherlock and then just got it into the

camera app so that you can just take a

picture of a barcode and it's all the

nutritional information about the food

without you having to open another app

genuinely generally that would be a

life-changing feature for so many people

honestly but anyway I digress these

principles carry through to the business

and it's so it's so valuable when people

do that because it also brings a

different different what is it an ethos

ethos no subject areas different subject

areas people who think differently you

know are creative in a different way end

up interacting with your data in these

awesome ways and they borrow concepts I

borrow concepts and quantified self all

the time and they've got nothing to do

with most of the client stuff I work

with but the chart types the way ya

manipulating data dealing with sort of

obscure things and like you say coming

across edge cases and realizing that

when you build systems you have to touch

test these edge cases thoroughly can't

you can't just build some it looks great

and then as soon as you have an Illinois

game rabbit realizes her fingers I'm

with my World Cup dashboard right that

was a lot of manual data collection but

yeah like what will once you go to the

second round and my my thing where

players come on and off the the team

sort of structure I didn't factor into

you know extra time so he's like taking

left two of the numbers like oh yeah

90th minute that's all they're gonna be

and then suddenly you've got a player

coming off in the 12 minutes like hang

on a second they're definitely losing

but it was because it 123

just rookie errors all round yeah but

it's fun it's funny how that they're all

all kind of plays that and I think it's

a really valuable thing I guess I guess

the now so what is that and we've

touched a bit already but actually

enabling people to have these things and

hackathons is such a good way of doing

that right yeah agreed like running a

hackathon internally even if it's within

your own data so I've sort of seen this

in two different places right so you can

either have a hackathon own internal

data where you're so you're saying right

okay the incentive is you get to present

this back to the c-suite or senior

management and show your ideas and what

you can do or also seeing this as like

his a theme here's some data tell us

something interesting use these tools

right and that both work in their own

sort of way the first one probably takes

a bit more like coaching on the tools

the second one is a bit more fun and

perhaps gets a bit more engagement but

the end of the day it's about giving

employees time and sort of saying this

isn't this is interesting this matters

to us we really do want to have our

employees work on this sort of thing

exactly exactly and also I think in

terms of how else do you support these

people to do these things and like it

sort of goes without saying we have

access to incredible software that does

all this stuff and part of that is being

able to actually you know take my copy

of tableau or tricks and be able to do

what professionals do with the data but

do it with this hobby and it's it's one

it's really important thing that to

recognize that you know people like

tableau they actually enable you to do

that through things like tableau public

so they take advantage of free software

and training courses and let people go

on that one-day training course that

might not sound like it's got anything

relevant to do with your everyday

business work but actually the skills I

learn I pick up will give them a passion

in data and also data literacy like

you're fundamentally talking about

building people's literacy levels

everything we're talking about whether

it's reading or writing as we talked

about before right and so just investing

in people you have to see alone in this

sense really really helps give back to

your business as well exactly

cool that's a good episode yes banana

kidnaps it I think we we indulged the

bit we came a bit off-track we went into

our passions but it's all worthwhile

hopefully just to try and highlight and

how valuable we think it is to our own

development also how it can be to others

and we'll be back in a couple of weeks

with another episode please keep the

feedback coming in and as a reminder

we've changed our name and branding so

we're at de fin podcast calm and we're

on datum pod on Twitter so it much much

easier to find know what not what nots

anymore I keep digging back Alicia I'm

so glad every time I have to say this

down just that I so much better

agreed agreed so much easier rolls off

the tongue a lot more yeah exactly and

as ever we rarely ask for the support in

this way but if you can give us a rating

on whatever podcasts that form you

listen to that would help because

apparently that's becoming the currency

for the podcast wars that are going to

be coming up in the future so start kind

of siphoning off podcasts and lots of

different places yeah if you can write

us that would really help us as well so

we know what we're doing and we can

improve and make sure we're getting into

the right places fantastic cheers

everyone have you are it easy