Business Mapping - Turning the lights on
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00:00
Extension (kinesiology)Constraint (mathematics)Software developerSelf-organizationBinary decision diagramScaling (geometry)Projective planeVideoconferencingSoftwareTelecommunicationMassTexture mappingNumberGoodness of fitFeedback10 (number)Point (geometry)Direction (geometry)Computer programmingElectronic signatureRight angleArithmetic progressionEndliche ModelltheorieTraffic reportingData managementDifferent (Kate Ryan album)Online helpSet (mathematics)Insertion lossFrame problemFunctional (mathematics)Line (geometry)Transformation (genetics)Process (computing)Civil engineeringGreatest elementWave packetState of matterQuicksortJSONXMLUMLComputer animation
07:38
Multiplication signGoodness of fitData managementMereologyBitWritingPoint (geometry)Social classSubsetFlow separationContext awarenessPhysical systemTransformation (genetics)Computer programmingProduct (business)Self-organizationCategory of beingProjective planeRoutingBit rateScaling (geometry)Right angleCASE <Informatik>PlanningClassical physicsComputer animation
10:48
Software developerClient (computing)NumberConstraint (mathematics)Order (biology)Data structureSelf-organizationData managementRight angleFeature Driven DevelopmentScaling (geometry)outputEndliche ModelltheorieStructural loadSoftware developerProjective planeGoodness of fitPerspective (visual)Type theoryInstance (computer science)System callDynamical systemShift operatorJava appletTerm (mathematics)VideoconferencingSet (mathematics)Pay televisionContent (media)Fitness functionSingle-precision floating-point formatEvent horizonLoop (music)Software frameworkMaxima and minimaPhysical systemScatteringShared memoryGroup actionComputer programmingRow (database)Multiplication signSocial classProcess (computing)Functional (mathematics)Coordinate systemWordNetwork topologyStochastic processFocus (optics)Point (geometry)MIDICountingNear-ringTable (information)NP-hardLine (geometry)CASE <Informatik>Lattice (order)PhysicalismComputer animation
17:44
Software developerFunctional (mathematics)BitRule of inferenceMultiplication signData miningBit rateFeature Driven DevelopmentMereologyRadio-frequency identificationScaling (geometry)Computer fileFlow separationSoftwareEndliche ModelltheoriePoint (geometry)Mathematical analysisHydraulic jumpVideo gameConstraint (mathematics)Electronic mailing listProjective planeFigurate numberWorkstation <Musikinstrument>Product (business)Right angleIterationNumberOperator (mathematics)WeightGraph (mathematics)Film editingDifferent (Kate Ryan album)Cross section (physics)Office suite2 (number)Coordinate systemLine (geometry)Information securityGastropod shellCASE <Informatik>Set (mathematics)WritingGoodness of fitProcess (computing)Computer programmingSoftware testingFactory (trading post)Programmer (hardware)NP-hardTransportation theory (mathematics)Physical systemSelf-organizationWordTable (information)Type theorySlide ruleReceiver operating characteristicCurveComputer animation
24:40
Software developerCycle (graph theory)BefehlsprozessorMathematicsLimit (category theory)Wave packetQuicksortMoment (mathematics)Mathematical optimizationComputer programmingRight angleGame controllerProgrammschleifeScaling (geometry)Figurate numberSpacetimePhysical systemDifferent (Kate Ryan album)Multiplication signLevel (video gaming)Texture mappingFundamental theorem of algebraMereologyAdditionDecision theoryCrash (computing)Self-organizationClient (computing)Sound effectStructural loadEntire functionMetric systemCycle (graph theory)Equaliser (mathematics)Water vaporStatement (computer science)Product (business)Coefficient of determinationProjective planeBitOperator (mathematics)Functional (mathematics)Point (geometry)Descriptive statisticsMilitary baseCarry (arithmetic)Programmer (hardware)Streaming mediaStability theory1 (number)TheoryComputer animation
31:36
Software developerPhysical systemConstraint (mathematics)Computer programmingShift operatorDialectSelf-organizationMultiplication signHypothesisData conversionPosition operatorDifferent (Kate Ryan album)Feature Driven DevelopmentExpert systemWeb-DesignerState observerScaling (geometry)Channel capacityPredicate logicDisk read-and-write headDemosceneOnline helpService (economics)InfinityForcing (mathematics)Constructor (object-oriented programming)Structural loadCondition numberSpacetimeProof theorySoftwareSubject indexingPlastikkarteHand fanStatement (computer science)Metropolitan area networkExecution unitAssembly languageTexture mappingPoint (geometry)GravitationPropositional formulaTheory of relativityTheoryFrequencyTable (information)NumberObject-oriented programmingGame theoryMereologyMilitary baseSoftware developerNetwork topologyPhysicalismQuicksortLevel (video gaming)Right angleGoodness of fitApproximationStaff (military)FamilyMoment (mathematics)Social classCone penetration testLogicSurvival analysisSymbol tablePhysical lawComputer animation
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Software developerTexture mappingProduct (business)Computing platformAbstractionSelf-organizationPhysical systemNumberComputer configurationData conversionDimensional analysisTexture mappingExecution unitRight angleConstraint (mathematics)Different (Kate Ryan album)Task (computing)Operator (mathematics)SequenceMathematicsEndliche ModelltheorieSpreadsheetOrder (biology)BitMereologyScaling (geometry)Numerical integrationProduktraumSoftware developerDatabaseMainframe computerDomain nameQuicksortProgrammer (hardware)Computer architecturePeer-to-peerLine (geometry)Matching (graph theory)Set (mathematics)System administratorSoftware testingINTEGRALTerm (mathematics)RoboticsRoundness (object)Cellular automatonTable (information)WordType theoryCASE <Informatik>Computer programmingWater vaporSoftwareAdditionSuite (music)RhombusComputer animation
49:45
Software developerDatabaseTexture mappingLine (geometry)Data storage deviceProcedural programmingTunisRight angleTerm (mathematics)Group actionOcean currentMatching (graph theory)Physical systemMereologyForm (programming)Venn diagramTouch typingMultiplication signSelf-organizationPoint (geometry)Operator (mathematics)Different (Kate Ryan album)Database transactionRule of inferenceInstallable File SystemRhombusMusical ensembleScaling (geometry)CuboidSet (mathematics)Data miningGame theoryTable (information)Computer animation
55:19
Software developerSoftware developerMathematicsResultantPlanningBitMultiplication signCuboidSet (mathematics)Rule of inferenceDerivation (linguistics)Equivalence relationWave packetFunction (mathematics)Online helpPhysical systemImage resolutionUser interfaceTexture mappingLine (geometry)Data storage deviceEntire functionTable (information)Row (database)Uniform resource locatorQuery languageParameter (computer programming)Different (Kate Ryan album)Perspective (visual)Series (mathematics)Computer programmingChannel capacityDiagramTerm (mathematics)LiquidSimilarity (geometry)Formal languageRight angleDependent and independent variablesPhysical lawComputer iconConstraint (mathematics)Scaling (geometry)Noise (electronics)Metropolitan area networkPoint (geometry)Theory of everythingProduct (business)Arithmetic meanComputer animation
01:00:53
Software developerPhysical systemChemical equationGoodness of fitMultiplication signTerm (mathematics)Computer programmingLevel (video gaming)Set (mathematics)QuicksortElectronic mailing listSelf-organizationHydraulic jumpAuftragsspracheMainframe computerFormal languageLiquidJava appletBuildingCartesian coordinate systemDecision theoryWebsiteSource codeReflection (mathematics)Instance (computer science)Software developerGroup actionMathematicsBus (computing)Right angleComputer animation
01:04:36
Software developerTexture mapping10 (number)BuildingComputer programmingGroup actionCoefficient of determinationShared memoryMultiplication signProjective planeSoftware testingSoftware developerScaling (geometry)Level (video gaming)Data managementQuicksortFrustrationSelf-organizationIdentity managementWeb pageDomain nameInformation securitySystem callSoftwareRight angleMedical imagingGraph coloringCASE <Informatik>Frame problemExpert systemAxiom of choicePhysical systemComputer animation
Transcript: English(auto-generated)
00:07
Morning how are we? Yes Yes Okay I'm feeling relaxed Which is nice Because this talk is a it's about a 50 minute talk and I've got about 60 minutes
00:25
So usually I try and do a 90 minute talk in 20 minutes. So this is this might actually work today So I'm quite excited about this hmm, so business mapping then About two years ago something like that. I was standing probably here or somewhere like this
00:48
Saying agile doesn't scale Okay, you can't scale agile doesn't scale that's not a thing and I still maintain that I still don't think agile scales agile is a agile methods generally are a fantastic team scale solution to
01:04
The problems of software delivery we had in the 90s Okay, because that's when they're all invented So who's using scrum? Right who's keep your hands up? Keep your hands up if you have been in the IT industry for less than 20 years
01:25
Less than 20 years. So all the people less than 20 years experience less than 25 years So if your hands down if you got less than two, right? So So Only the people with their hands up have been around longer than scrum
01:42
Okay, so scrum people are still learning scrum as this state-of-the-art, you know, it's this it's though It's the way we build software. It's the way we built software 25 years ago Go us go innovation. Yeah it's a fantastic solution to a set of constraints we had in the 90s and
02:01
To the extent that we still have those constraints now, it's great To the extent we don't it's not so and then what happened was So back in the 90s. We were all struggling with multi-year projects who was delivering projects in the 90s Actually, that's not fair. Who was writing software in the 90s. None of us were delivering projects
02:21
Right who was right. So was yeah, so a few hands maybe about 10 15 percent of you So mostly what would happen is we plan this, you know, two three year mega thing We'll have Gantt charts We'd have all the different pieces and we knew exactly how it was going to go and it would trundle on and you know A year 18 months into this thing. You knew it was doomed
02:41
You knew it was doomed And it would rumble on for another year because no one had the courage to say this is doomed and it was usually someone's massive vanity project anyway, and So that's what the whole kind of agile movement Grew up in that that was the thing. It was reacting to saying Surely there's a better way to deliver software than this
03:01
And and they were right, I think they were right so So that this is your agile methods and then what happened was they started working Okay, so now early 2000s and people are getting stuff done so you've got these small cross-functional teams talking directly to the business
03:21
shipping things frequently and regularly and and They're good things or when they're not good things you can course correct and all this and feedback and courage and all those good XP practices or values Started working and people got really excited and then so then they said right now What I need to do is apply this to my 80 person program
03:41
to my 300 person IT Organization across my 2,000 person company right go and And so they went back to all these agile gurus and said okay, how do we do this? Okay, well you're great Thanks for solving this first seven people plus or minus two. What about 70 people plus or minus 10 and
04:04
Rather than what I think would have been the right thing to do which is say shrug I don't know that was never the problem. We were solving you should have been in my you know We should have been with us back then because it was impossible to get anything done And they said oh they stroke their beards because they're all middle-aged white men, okay
04:22
This is the the all of the agile signatures or middle-aged white men Many of whom have facial hair and so the straight their business and scaling and they feel they should have an opinion And so you get things like scrum of scrums Scrum of scrums doesn't work cannot work has never worked. Oh There I said it. Oh, there I go
04:41
Okay, it's when you want to do stuff bigger. It's a substantively different problem and one of the things that happened was And I'm gonna call scrum out on this because it does this a lot Well certainly some of the trainers do they come in and they say right, so here's how scrum works You know seven people plus or minus two blah back logs
05:02
features story points All that stuff right and they say anyone here, and I've heard a well-known scrum trainer say this Anyone here who's a project manager or a business analyst you no longer have a role here All right way to make friends. Yeah, so
05:22
I've worked in organizations where it then took them literally years to rebuild that relationship Okay, so but it's a substantively different thing so business mapping then For our last I know three ish years probably three or four years I've been trying to help Organizations scale delivery or I've been working with organizations who are trying to scale delivery for a better way to describe it I
05:47
Have a good friend called Chris Matt's as anyone I don't know if you guys come across Chris Matt's He was a business analyst at ThoughtWorks back in the day, so he's the other half of BDD so he co-invented BDD with me
06:00
and we've stayed friends it's like 12 years and Every now and then we check in I haven't really worked together since but we check in with each other and about a year ago We were sitting there glass of wine very civilized So what have you been up to and he said I've been working at eight with a well-known video communications organization that was bought by a very large well-known company on the
06:21
northwest coast of the u.s. and And we've been figuring out how to do delivery at these thousands of people scale They've got like 1,500 developers or something so thousands of people hundreds of teams. I said wow that sounds pretty cool What have you been doing? I said well. I've been working in a very large American Bank
06:40
Across about 500 people so hundreds of people tens of teams Figuring out how to get them all points in the same direction He said oh that sounds interesting and we started comparing notes And we realized we come up with exactly the same model, and we got really excited about this Because now we both have the other data point. I know my thing scales up He knows his thing scales down and so we spent most of last year
07:02
kind of Shaping this framing it giving it names, so this is what we've come up with so it's a work in progress But the reason I'm excited about this is we've done it. This isn't a hypothetical model This isn't if you do this everything will be fine. This is effectively an experience report This is we've this is empirical. We've done. We've used these methods, and we're excited about them because they seem to be working
07:25
So there you go. That's the preamble Business mapping then is the name of the whole piece and you'll see there's number of segments within it so Is my little pecker gonna work? Yes, it is fantastic. So let's start with the context then so
07:42
Context we've got some kind of lean agile transformation underway Okay, so we've started down that agile route We're maybe 18 months in two years in who's the who's there who's there on that journey, and it's how's it been? Good bit bumpy
08:01
Yeah, some people getting it some people not getting it people struggling So I had several successful deliveries You know there's a few little point success stories for for values of successful and for values of several Right, but you know we've there's been a few point successes And it's looking pretty good and so agile the idea of agile is now normal
08:21
Okay, so we talk about agile, and and it's normal. I guess become normalized so we talk about the fact that your project managers went off on a two-day class and came back as scrum masters and the fact that your Business analysts went off on another two-day class and came back as product owners, but they're all really the same people We don't talk about that, but we are all agile, okay
08:41
And so and so what I end up with is an organization saying why isn't this working? Or in actual fact what I get is the business side saying this is worse than we had before Why is this worse? There's a well it used to be I could go and tap Lily on the shoulder and say can you do this thing? For me and she's like yes, of course because she's very obliging and she's a great coder
09:01
So she goes off and does this thing and she ships it and I'm done now what happens I say hey Lily could you do this thing and she says yes? We're going to write a story and we're going to write acceptance criteria with that story Then it's going to go into a backlog and then a backlog grooming session, and it's going to get planet really Really, yeah, you'll probably see it about three months And then you know great. That's my experience of your agileness thing
09:25
yeah, and and so there's this kind of Quite understandable resistance from the consumers of this whole transformation so The challenge then and so Chris Matt's and I like I say we're doing this as effectively as a two-hander
09:40
He's all about the business. So he's up in the portfolio. He's in the business. He's where the money is Okay, I don't get that I sort of get it, but I don't get it the way he gets it I'm in with the programs and the teams and the human beings Okay, I like people and I like helping people work better Chris sociopath
10:00
There you go, so we work quite well together he breaks people I go and make them feel better, right? Let's say so on the on the organizational side then the challenge is about scaling the work So what is it? What is planning in the large look like you know? We've got we've gotten quite good at planning in the small you know planning for seven to ten people we can do that What does it mean to define a program of work by which I mean I've got a problem that is 80 people wide and
10:26
Some problems are just 80 people wide if I've got enough time to wait I'll have my eight people and they'll do their thing and they'll agile it and whatever else and it'll come Right if I'm solving tax Right tax is a 400 person problem Okay, because there's a whole bunch of parts of tax that are largely independent of each other and which I want to just kind
10:47
Of move and so the guys wanting to re-implement the VAT systems having to wait on the guys doing the corporate tax systems because all of them are waiting for the Self-assessment tax people because there's only ten people on it. That's not okay
11:01
Yeah, so it's that kind of program of work And then above the program scale what does it mean to manage a portfolio of work? So these are some of the things that some of my clients and Chris's clients have been struggling with and Then on the human being side we've got this idea of growing the people So what does it mean to be in an agile organization one thing?
11:23
I hear a lot and I thought it was just a kind of a Random signal and I've just heard it so consistently now people talk about being lost in agile, right? So in the old days, I was dev 1 dev 2 dev 3 senior dev architect manager Right. That's me for the next 20 years. I'm good. Yeah
11:41
Was now I come in. I'm a team member What do you do? I'm a team member. What does that mean? I'm a member of a team Alright, how's that working out for you? Well, how's your career moved in the last two years or two years ago? I was a team member and now I'm a team member and it's like and it's and it's not just that it kind of sucks
12:02
From that perspective. It's what is good look like What is good look like to be someone in working in that type of organization? How do you grow? What does it mean to grow in a flat organization? Can you grow? And the bottom line, how do I get promoted? How do I get paid more? Yeah, how do I I'm sure I'm learning stuff
12:22
I'm sure I'm becoming more valuable to your organization We all agree that but how do you quantify that? And so that's the challenge. So let's take a look at then the pieces what are the inputs then? So the inputs on the organizational side, we've got KPIs. We've got organizational KPIs. So for instance for our
12:42
video A Conferencing thing I have a funnel. Okay, and I have a funnel of casual users registered users subscribers Premium subscribers. Okay, that that's your funnel. So casual users just people who occasionally get on there and talk to people
13:00
Registered so you've got an account and all that kind of stuff subscribers. I'm now paying for some content premium subscribers I'm praying for premium content as you move along that funnel you become more valuable Now There's you can slice that in terms of new people and churn So how many new people how many new subscribers did I get this quarter?
13:21
how many people did I lose and so therefore what's my net difference and In that particular case, you've also got domestic and business Accounts so I can look at domestic subscribers. I can look at business subscribers clearly business subscribers Probably going to be higher revenue for me So they're going to bring in whole groups of people and I probably charge them more anyway
13:41
And so on so I can have business I can have opinions as an organization about what I care about with those KPIs My near and midterm goals. Okay, we're going to focus on for the next couple of quarters I want to focus on reducing subscriber churn My subscriber churn seems to be trending upwards maybe that's because other rival video things like I know FaceTime and hangouts and that seem to be stealing market share from me and
14:05
I want to figure out why that is. Yeah, and Then that's the internal stuff and then you then have physical constraints. It's a hard constraint. So I might have Regulatory constraints compliance constraints. So in order to execute my business in order to do stuff
14:22
I need to meet certain criteria. So that's that that's the the the external constraints structural constraints I've got half my teams in London half. It's in Poland Okay Some of my some of my folks are in Australia which makes it really difficult to to coordinate things and they're just hard constraints. Okay
14:41
And again on the people side the hard constraints I have there the inputs I have there. Sorry our skills and capabilities Who have I got? What can they do? what are they what are they like doing and Something that was really important for me to get into this model was I wanted to have a way to make aspirational
15:02
Career aspirations a first-class citizen here. So I worked for eight years with ThoughtWorks in London and And they're they're a fantastic organization Okay, I did loads really interesting stuff met some great people work with some real talent grew all that stuff however Pretty much everything about your career development is kind of random
15:23
You know, it's kind of who which clients to get what projects do you get which projects you happen to end up on? You know So if I happen to end up on a project I'm gonna call on Lily because she's sitting there right if I happen to end up on a project with Lily I'm gonna learn an awful lot about interacting with people. I'm gonna learn an awful lot about
15:42
How team dynamics work and all that kind of stuff because she's really good at that and she likes to share her knowledge Right fantastic. If I luck out if I end up on a yet another crappy lift and shift Java typing gig It's not going to be that interesting Yeah, and so there there's it seems like there's not much in terms of resourcing you can do around aspiration around human aspirations
16:04
And I wanted to factor that in as well so then This is where Chris and I independently Started kind of worrying at the edges of some of these scaling models So all of the current crop of scaled agile models
16:22
You know what they all are right they all have essentially the same set of assumptions I've got a number of teams Okay, these are my feature teams or scrum teams or whatever there's there's small cross-functional teams that I can distribute work into yeah, and
16:40
So here's my work. It clearly doesn't fit into any of those teams. I need to figure out how to Slice up that work. So the first problem I have is how do I distribute that work? Okay, that's problem number one problem number two, which is I think it's harder right is how do I then bring all that stuff back together? And make money or do whatever it is. I do yeah, and
17:04
so this is a parallelizing problem okay, this is a constraints problem and There's a reason that parallel printers died out right there's a reason that You know single event loop frameworks are successful
17:23
There's a reason that l max disruptor has a single guy in the middle doing stuff. It's a much easier problem to Get all the work get to speed up one worker One piece of system. It's much easier problem to solve Speeding up one system than doing the scatter and the gather coordinating that because in here
17:45
what actually happens is each of these teams has a Separate backlog it has a separate product owner with separate priorities separate motivations typically facing off to separate business people And so this team has a piece of work. That's in this table is dependent on a piece of work
18:01
That's in this team's backlog Which is great except that that team's product owner doesn't really care And it's number three on the list But it carries on being number three on the list Right everything kind of moves past it and it's number three on the list in six weeks time Yeah, and so this team is now stuck through no fault of their own etc Everyone's had that problem so the the the the dependency problem the coordination problem the different priorities problem
18:26
Okay, so what if we reimagine the problem then what if we think what if we um? What if we call out some of the constraints that aren't really constraints? So I want to get beyond feature teams. I don't want to think about feature teams anymore I want to think about I've got my 80 people and I've got a big pile of work
18:43
and what I want to do is put the 80 people in a big pile of work in a bag and Shake it all up and figure out what the best way is to arrange those people around that work Okay, that's the thing I could do if I didn't have the the hard shell of feature teams, okay?
19:01
Lean operations, so this is where all of this stuff comes from so all of the agile methods are Predicated in lean operations lean operations rule one okay, or rule one is think okay? But rule two fairly near the top of the list of rules Is this idea that you move the people to the work and this was fundamentally different from the exist in Western models like
19:22
Henry Ford's Kavai Kavai belts yeah, so I'm sitting there in a factory, and I've got a production line and The the thing moves along the production line and so the work is transported around And it goes to each of the different workstations and people do work on it, and that's that's the typical Western model the
19:42
Lean model is Moving work around it's called transportation right moving work around is wasteful It doesn't add any value and it just cost time and time is our time is they lead time is the thing we want to reduce so What if we had all the people? Swarming around the work get the right people to swarm around the right work, and then stuff happens. This is your
20:03
Your sports car coming into the pits right and people come in they jump on it right and so I am my job is Front right wheel nut for okay Deville's job is front right wheel nut to and we both jump in with our little hydraulic things go best and
20:21
All that and then the wheels come off and the wheels go back on the fuel goes in the thing goes out in like Seven seconds and everyone goes wow that's pretty cool Yeah, or they go Okay, the cars in who's the tire guys, okay? Okay, yeah, we're done right fuel. Oh, I'm over here. Yeah, okay, just move the car along to the fuel pot no
20:42
Okay, not not a way to win a race all right if time if time is that is the constraint if time is the thing You're trying to minimize Swarming the people around where they need to be is the way to move things quickly So let's think about that what we're doing Ironically in fact. This is where the idea of feature teams or cross-functional teams came from
21:05
So back in the dark ages you would have analysts that did analysis, and then they were passed off to designers architects who would figure out how to make a system that did that and then that would go off to Programmers who would type and then it went off to
21:21
testers who would tell programmers how what idiots they were and so on and so you had this whole set of stovepipes and silos and people and the work would move along and That seemed to take an awfully long time and in fact that didn't happen at all because what would happen is it would go that way and then back again, and that way and then back again, it was always moving backwards and forwards and Stuff or I don't need to explain to you where I came from but
21:44
So the idea of a cross-functional team was we have a problem to solve we have a feature to deliver What are all of the people that need to be involved in that feature? Well, I'm gonna need all those people I just said and maybe some UX and maybe some security and maybe some compliance and maybe some of the other things as well All right And so I bring all these people together and I say solve this and they work together and they collaborate and they solve this
22:05
so the original preset of Cross-functional teams of feature teams was moving the people to the work epic, right Except then when we scale we forget that and so we think instead feature teams equals the answer
22:21
right rather than feature teams being a Projection of that value of that principle. So then what we do is we say we've got all these feature teams That's clearly the way to write software. So now we just need to divvy up the work and slide it through the teams fail Okay, and all of the scaling methods are currently subject to that fail so
22:41
The last part or the third reimagining piece And you can tell by the words that this is a crisp piece rather than a damn piece Because it's got money in it So risk adjusted return on capital if you go back into your Organizations and you go to the finance guys and you go to the project sponsors and you talk about risk-adjusted return on capital
23:04
They will fall out of their chairs Okay, that is really good walking around money right there Okay, so ROI who knows about ROI return on investment right or ROC as it's down in return on capital Okay, so So that's what we think of you invest some money you get something back
23:22
Okay, and ideally you get back more than you put in and that's a good investment right risk adjusted return on capital risk-adjusted return on investment says when When do I get that thing back? So say I want to fund a 12-month piece of work and if every month
23:42
Something useful comes out and so I start getting some return much sooner then all through the year I'm generating that money. That's really cool. So this is the business. This is part of the economic case for Incremental delivery for iterative delivery
24:01
Rather than if you think like the the curve of all the the graph of investment I've got a team the team cost me however much you know thousand dollars or thousand pounds a week And so my investment is this it's the linear, you know burn rate of the team over time Yeah, and eventually they ship something it goes pink like this and that's great and I start making money now
24:23
But I'm still really just paying off this huge amount of cost that I've incurred and eventually I go into profit If I'm doing stuff iteratively I invest a bit of stuff and then I get a return and then I invest a bit of stuff and I get a Return and so what you end up with is the amount of value at risk is low
24:40
Because you're realizing value sooner So risk-adjusted return on capital is we're going to change the metrics rather than it just being a blunt instrument of what's my ROI What should I get for this project is when will I get it and This this ties into a bit of finance theory called bond pricing. This is how you price bonds is It's not the value of the bond
25:01
It's the value of bond as a function of how soon I'll get that value So this so I'd much rather have a whole load of bonds with a lower yield sooner Then have to wait ages and then get a big bunch of money Because there's risk involved in that the longer I wait it may be that just before I get that bond or that pension The market crashes and now my pensions worthless
25:22
Yeah, lots and lots of people got burnt in 2007 2008 just as they were finishing their working lives I'm finishing my working career. All of my pension pot is in the stock market, which is now worthless brilliant If instead that money had been coming out in little pieces over, you know, the decades or whatever
25:41
Suddenly the impact of that last crash is much much lower. Yeah, so we're trying to reduce risk And this again, this is a fundamental difference between business mapping and this space and most of the Scaling methods that you'll hear about is
26:02
This is risk based. This is about this is about managing risk rather than controls So all of the stuff you get in safe and less and dad and all these all these sort of checkpoints and feature trains And all this kind of stuff are all about controls Okay, where will I get when will I see stuff okay rather than controls which is kind of like holding the tail
26:24
What we want is to be the dog, right? And so then this is the risk is understanding where you are Okay controls is trying to hang on to this thing because you don't know where you are so When you're trying to change stuff
26:41
Change effective change essentially has three parts to it work in a cycle And it took me a long time to figure this out a long time to figure this out And it's one of these things that when you see you go. Well, I know this it's really obvious So the first thing you do is visualize so You know, you're in a room full of tigers. I'm gonna turn the lights on
27:02
Okay, you were already in a room full of tigers Just saying right you might blame me because now you know But you're already in a room full of tigers So visualize is know where you are and most of change. We just start we don't know where we are stabilize then So even if we're I wateringly bad at stuff and you know visualize will start telling you this right so visualize will say
27:27
You know, it's currently taking us 12 months to ship a feature or Whatever it is Is it as we've measured the value stream and it turns out that from concept to something in production is this?
27:41
eye-watering amount of time Stabilize says it doesn't matter if it's eye-watering as long as it's consistently eye-watering, right? So What I don't want is well, it takes us 10 months plus or minus 10 months Yeah, because the problem with that is that anything you do to try to optimize the system to make the system more effective
28:02
is random Yeah, you don't know whether the changes you're making are improving because you don't have a stable base to work from So then the third stage is optimized so now we've got a stable Clear system a system we can see then we can start to tune it Okay, the problem is everyone in this room is a technologist and we love all this, right?
28:24
So we jump on to optimize and we optimize and optimize and optimize and no one's bothering to check Yeah, so we're not looking where we are. We don't know whether we're stable It's like it's the the the mountain climbing thing where you should always have three limbs touching rock
28:40
Okay, and then you move the fourth limb and then you move another limb you that that's a stable way to climb as soon As you only have two limbs, there's risk. Yeah, if you have no limbs, you're in trouble, right? So and because I see loops everywhere because I think in systems, you know, and then you go back around again Okay, so the whole of business mapping is in the visualize space
29:02
So business mapping doesn't say do this It doesn't say it doesn't tell you how to make decisions It doesn't tell you what to decide I have opinions about how you should make decisions. I mean come and ask me But what it does is this it says this is where you need to have an opinion It turns the lights on in a way that says now you can figure out what you need to do and you do that
29:23
However, you do it. You won't do that. Hi hippo, right a highest paid person's opinion. All right hippo decision-making Yeah, who's the senior person in the room? Let's just shut up and let them speak then Right, or it may be collaborative. I'm working with one client where they're nice and nice is a double-edged sword
29:40
Because they're so nice. No one ever wants to offend anybody and it takes ages to get decisions made I'll be honest. I'm much rather work there than the not nice So yeah, so we're in the visualize space. So then Business mapping. What does this look like? We start with initiative mapping and I'm going to unpack this in a minute initiative mapping is
30:02
Those top-level KPIs that you know, reducing subscriber churn that kind of thing How do I map that to the business initiatives? I want to carry out, okay Demand mapping. How do I design programs of work that are going to realize those initiatives?
30:24
Then on the supply side Who have I got this is this is Katie she's a programmer you'll meet her again in a minute and What does she do? well That's skills mapping we call that so and then you got demand mapping is the demand side skills mapping is the supply side if You're like of people and and skills and then we bring all that together
30:44
And we shake it all up in a bag and we call that delivery mapping Okay, so I'm going to unpack these things now. I'll give you a bit of a description of these things So let's start with initiative mapping In addition I think I'm going to take my business Metric and as I say it's a KPI It's something that runs the organization and it may be a business side metric. So
31:06
You know increase in profits all that kind of stuff increase in new customers reducing churn all of that It may be an operations side metric, you know reducing cost per customer reducing quality Thing, you know like sort of user visible outages that kind of stuff. Okay, so
31:24
So I choose the metric And then I say right what I'm going to make the entire organization point at that metric because initiative mapping it says and oops for that game this here this is a
31:41
an Assertion I am going to make an assertion that if I introduce these programs of work these sorry these initiatives These initiatives will drive that top-level metric now All of this is hypothesis based. What's a hypothesis any scientist? What's a hypothesis?
32:04
Sorry Something that is not proven It's an assumption Something that can be tested close what's the difference between an assumption a Hypothesis and just an assertion you may have some reason to believe it's true
32:28
Okay, everyone in the room he thinks that in hypothesis driven development or whatever. Yeah Please if you take nothing else away from this talk take this away a hypothesis is a falsifiable statement
32:43
Science is asymmetric Which is really frustrating you can't prove anything in science You can just disprove things and so what happens is you have a body of knowledge that is increasingly better but always assumed wrong and We lost that when we took the idea of hypothesis into software so even like I've seen index cards that say
33:05
You know hypothesis driven blah and the index card say hypothesis. I believe statement I will know this is true when condition fail You cannot know it's true. Okay. That's not how hypotheses work That's how predicate logic works, but that's not what a hypothesis is. I can disprove this by is our hypothesis
33:26
All right, and so, you know for 300 years we knew how gravity worked until about 1905 And then I saw went now Now, I mean, it's a really good approximation If you're traveling very fast, or you're very big or you're very small. It doesn't work
33:42
Okay, all the other conditions. It's fine, which is why it lasted 300 years. Yeah and then a better proposition came along for how gravity and space and time and stuff might work and Made Falsifiable statements that held up against a relativity and didn't work against Newtonian physics
34:03
Okay, so we're looking for falsifiable. So this now we've built a falsifiable system. I believe if we do this work We will shift Well, well, it'll later just stop working. We will shift that dial. Okay, and likewise
34:21
If we each of those initiatives I might have a marketing initiative an engineering initiative a sales initiative that are going to drive the organization forward Each of those is falsifiable as well I should be measuring this all the time and as soon as I can disprove the hypothesis we're doing this work It's the right work. It feels you know, and it's going okay
34:41
It's not moving the dial. Well, we should stop. So we should stop I can point. There we go And so now what I do is I start designing programs of work, oh there he goes back again Wow, I'm having laser problems come back I'm gonna will it I'm gonna will it in to go back anyway, nevermind
35:05
So, yeah, so again each of these programs of work has a metric has a reason for existing okay, and so So Again, I can I should be in a position where if that program the the metric it started isn't moving the dial
35:22
It's supposed to dial to move I can kill it if it's part of an initiative that isn't moving The things that should buy to be able to kill the initiative. Okay, so this is about falsifiability So initiative mapping start there. Okay, most organizations can't tell you this story They don't know why the initiatives they have are there other than head of marketing said so head of engineering said this is what we're doing
35:45
Yeah, there needs to be that alignment so Here's an example, so say I'm going to make some movies, okay I want to make some Avengers assemble Avengers Age of Ultron Captain America Iron Man 4. Okay, these are the movies. I'm gonna go make
36:02
I'm gonna they all they have chase scenes in New York, right? And so I'm gonna need some help I need some help from the various Services in New York, I've got police I've got ambulance of an air of a fire department And what I do is I look at each of these movies and I say well given the movie How much help am I likely to need from these various?
36:25
facilities right and we kind of come up with an idea so Avengers assemble, I'm gonna need some police. Well, I'm a force got a Robert Downey jr. In it, right? So a he's mental I'm gonna need load of ambulances and also he's Robert Downey jr
36:40
So I'll need a ton of police to hold the fans back. All right, you know hundreds of thousands of screaming women and Robert yeah, so So I can see that's gonna be that's gonna be a major investment there Avengers assemble, I don't need any air or fire support there. So I'm feeling pretty good about that But now let's think about this Say I want to I want to make Iron Man 4
37:04
Okay, I'm gonna need a lot of police support to make Iron Man 4 if I just go up to the New York PD and say I need 35 units or whatever of policing. I Just gonna laugh at me but what I could do is I maybe I make Avengers assemble or Captain America first and
37:21
I need much smaller investment from the police and we become friends and they know that I am You know, I I do my part of it whatever and we've got a relationship and then I go back and I say You know that what we did before. Well, I need that but about three times as much and I go Yeah, sure, we can do that. Okay, all these they're more likely to there's no point me making a devolt run Yeah, because there's no police involvement in that at all. So that won't help move that relationship forward
37:44
Yeah, so I can already start seeing this and in fact you can view this as constraints So these various services that I need are constraints and this becomes a theory of constraints problem There's say there are only 20 police units Available right? I can't make Iron Man 4 period right? That's off the table
38:04
Yeah, and so each of the numbers in this whole grid here represents a conversation And it represents a conversation. I need to have a relationship. I need to build in The same way in your organization. You may have constraints around
38:21
web developers right around DBAs around the various different skills and capabilities you would need to deliver things Okay, subject matter experts about something really arcane. Yeah, and that constrains how you work now one other observation here is
38:42
Most of the scaling methods like safe and less and Dada and friends They assume that money is the constraint They assume that funding is the constraint and so what they're trying to do is they say well I've got this this capacity of people. I've got a and what I want to do is is fill up my capacity
39:03
So I've got a big I've got a bunch of feature teams and then we've got backlogs and I want to just fill them All up, so they're all doing stuff. Yeah But that's not true So I will I will try it all try something here. I'm gonna give you infinity money Okay, I'm gonna give you infinity money all I need you to do is deliver twice as quickly
39:25
Who reckons if I gave them infinity money, they'll be able to deliver twice as quickly tomorrow Right, that's not the constraint Access to people is the constraint. Okay Different skills is the constraint Organizational constructs is the constraint politics is the constraint where people are geographically
39:42
There's loads and loads of stuff that is the system of work. You're in that really is the constraint Money is a side detail Yeah, sure. It constrains certain things, but it's not the thing we want to be solving for So demand mapping then demand mapping is the demand side. This is how we put a program of work together
40:04
so demand mapping is It starts off looking very gantt charty and that's kind of deliberate because I want to get those guys in the room as well Okay, so we start tomorrow mapping starts like this it says What are the things I want to do one of my big ticket items I want to do and so I lay them out
40:22
So these are things I want to do next quarter and then Q 2 Q 3 Q 4 and so on and as I go across Here, I've got an increasing cone of uncertainty. I'm pretty sure the stuff I'm gonna do the next quarter The quarter after that less sure by the end of the this is completely speculative Q plus 4 is like as a year Away. Yeah, but what's gonna happen is each
40:42
Quarter, I will do this exercise and so that new quarter has just shifted into focus so we're always working with increasing uncertainty and Then we say I want these things and the question then is how much? How much do you want these things and how much in actual money? All right, so
41:01
We use a metric which is about a team for about a week and so that teams about ten people and So they're about a thousand dollars a day Fully loaded cost that's them and their desk and they're all that kind of stuff And there's five days in a week That means it's about fifty thousand dollars a week to run a team. Okay, completely arbitrary numbers
41:23
But you'll notice that that immediately takes a bunch of conversations off the table Like plus or minus a person doesn't matter plus or minus a few days doesn't matter Okay, so this is units of investment And so we say right we have and we call these swags sweet wild-ass guess
41:40
Okay, we're going to invest swags and so we look at what we have across those various constraints The the different skills and capabilities we have available and we say we have this many swags, how do you want to spend them? yeah, and And so we say this is how much I want to invest in So this this top one here is an ongoing piece that's finishing here
42:02
This is a fairly small piece here. And then you've got some other initiatives kind of starting out across the year And This is where we part ways with Gantt charts So the assumption in Gantt charts is that this is now a reducible problem I can break it into tasks into work items and I can schedule them and essentially now I need to manage a
42:24
sequence of dependent tasks, yeah Software development is emergent. It's not reducible It's a self-modifying system as I build things I learn and that changes the things I build As I build things and show them to people the people's opinion changes and that
42:44
Reinforce that changes the thing I build if we choose to do it that way Okay, so we have an emergent system so Rather than pretending I can break this into pieces All I do is I say in order to deliver these things which skills which capabilities am I going to need?
43:00
Okay, so The sorry which which apps and systems so that's all I care about what what gets touched by delivering this thing here What what are the systems that I'm going to touch? What are the parts of the organization? What are the maybe external vendors what things? Get impacted when I build this thing and then I say based on that
43:24
What are the skills and capabilities that I would need in order to successfully deliver against those things? So one of those things might be a legacy system. It's in COBOL. It talks to a db2 database on a mainframe And I need someone with deep domain knowledge of
43:41
Pensions administration, right? And so there's a technical skills and the business skills are all part of that suit. And so So this now sort of creates the demand side. So we've gone from what are the diamonds? What are the what the business capabilities? I want to want to build What systems get impact how much to honor invest in them? What systems get impacted?
44:04
Therefore what skills and capabilities do I need right? I'm going to park that I'm gonna look at the other side skills mapping remember Katie So Katie's a programmer She's a developer. And so I said to Katie. So what do you do? Tell me about yourself and she says well She's I'm a developer. I'm in a team
44:22
working on a product On a platform and I work in a department in an organization okay, that's what I do and Katie is immediately a very interesting person. She's like there's six dimensions here The six completely or not independent. There are six different dimensions here That I could explore Katie on right that make Katie more or less
44:45
Valuable more or less useful. Okay, and against each of those dimensions. There's a set of skills So what are the skills in my organization that would differentiate a good developer? What do I want them to know? In a team, so this is like team skills. So how well do they play with others?
45:05
How well do they work in a team, but also it's the t-shaped thing So if Kate is a developer How well how good is she as a DBA as a sysadmin as a tester as an analyst? Right because that means that she can start covering off some of those other gaps. Yeah, so that makes her more valuable to me
45:22
And she's working on a product. Well that suggests domain knowledge. So how well does she know the product? How well does she know the product space they the customers the the competition the business all of that kind of stuff? And that product doesn't live in isolation. It lives on a platform. So this isn't kind of Abstract technical skills, this is specific to our organization
45:44
This is so we've built these platforms these api's these systems and how well does she know all of those if she's going to build Something new and she totally understands all of the platforms as she has access to she's likely to build something That is more aligned with those things Faster yeah, she knows what options she has each of these dimensions is creating options
46:05
She's in a department. Well now what does that mean? That means that she's navigating the organization, right? How well does she navigate the organization? What about the relationships she has with people? What is her network? Like how well can she influence outside of her own bubble? Right and then finally in an organization so that organization has
46:23
Values they may be publicly declared values But it has a way of operating and how well aligned is what she does with what the organization does so you see there's like a lot of different ways in which Katie's interest in and So I asked Katie I say what I want you to do is I want you to let me know how good you think you are at all this stuff and
46:44
It's a really simple scale I used to use the Dreyfus model for this but I found a much simpler scale which is zero one two three none read write teach Okay, so let's talk about your C sharp Katie says well my C sharp. I would say I
47:00
Reckon I mean I can write C sharp. I don't think I could teach it yet I don't know deeply enough to teach it, but I I could write it and so on But then you could also say let's talk about influencing skills None, I wouldn't recognize influencing if I saw it read I can tell when someone influencing is taking place I can tell when someone is influencing upwards or across I
47:22
Can influence people I can teach people influencing skills. Yeah, and so It's a really nice lightweight way of scoring But I don't just ask that question I actually asked three questions and you end up with something that looks a lot like a spreadsheet because it's a lot like a spreadsheet
47:41
It looks a bit like this and so we might say for one of the platform questions This is my XYZ platform, and I say so based on that platform How well do you think you know the architecture of that platform and Katie says she answers three questions here So this is how well do you know it? Right, that's you and then there's a lovely technique called moral reasoning
48:02
which is if I asked someone else if I asked your peers to assess you, what would they say and so then she says they would say I'm a two as well and then this dotted line here is Where do you want to get to with it and she's well actually I'd like to be able to teach it I thought it'd be a really useful thing
48:21
And then we look at the next one and the API is she says well, I think I'm a three I think I could teach this stuff If you asked my peers, I reckon they would say I'm a two Okay, well that the fact that those numbers don't match is data that suggests maybe she's a bit frustrated She hasn't had an opportunity to teach this stuff so that's why her peers wouldn't recognize that but maybe she wants to and
48:43
The other way around if you look at so Chris's integration skills his understanding of the integration points for this platform he says Well, I'm a one I can see how it works, but I couldn't design it myself, right? I wouldn't feel confident doing that. But if you ask my teammates, they'll tell you I'm a two they'll tell you I can
49:04
That suggests a risk Right that suggests and and Chris is saying because I know people who can do this and I'm not one of them That suggests that the team thinks that there's that skill in the team and it doesn't exist Yeah, so you can start when the numbers don't match. There's some really useful data there and you can see Dan down here
49:22
He's he's he's can recognize the architecture. He's seen a lot of architecture. He's fine with this. He doesn't really know this one deeply He's pretty good with it. He can recognize the API He'd like to get good enough with the API to teach it in terms of the integration stuff He can do it, but he's not interested in taking it further And so now I get this really useful data. I get what can my people do and where do they want to get to?
49:45
and so now delivery mapping is where I bring all these things together and delivery mapping says Says So I've got my diamonds here. So this is business demand. These are things I want to achieve these are the amount of
50:01
The amount I want to invest the systems that are going to be affected and therefore the skills I'm likely to need Okay, and I can look at the team I've assembled and I can immediately take a risk assessment of that team again This doesn't tell me what to do It tells me where to look so you look at skill II whatever that is That might be a database tuning or something, right and it looks pretty good until
50:23
Katie goes on holiday Right Katie goes on holiday and now no one in the team has a clue. Yeah, that might not be a problem All right, we might be okay for that. But at least we're now aware of it. Likewise if If Dan who's got that skill a
50:40
Leaves heads off for a holiday or leaves the team or whatever We're very very light in terms of that and skill see No one knows how to do we've got a couple of people who can recognize it But that's basically it and so if we've assembled that team We now immediately know what care and feeding that that group of people might need Okay so then
51:00
We can sum all this up in a lovely little Venn diagram of business need current skills aspirational skills and each spot on this Venn diagram is Significant so very briefly then in the middle. I
51:20
Have there's a business need it's a current skill and it's something I want to get better at Go nuts Right awesome because that means that by delivering something using a skill you have you will practice that skill You'll get better at it. Everyone's happy. Right? That's great. So if we look above there We've got as a business need where there is a current skill, but it's not really anything. I want to grow
51:44
Right. I'm fine with that. Well, so what does that mean? Well, that means I can teach that So we I can be in a team where someone else wants to learn and so you can use the skills mapping as A dating thing right you can match up people who want to learn with people who want to teach Yeah Um, so by me teaching that's great because I can hand that skill off to someone else I'm changing the system of work
52:07
So teaching is a form of Kaizen. I change the system of work to one that has more people that have that skill And likewise down here There's business need which is an aspirational skill of mine, but I don't have that skill pick me pick me
52:20
Right because now I go to I learn Yeah, and then on the left here Is business need? Okay, there's no current skills and no one cares No one has an aspiration. This is this is my kobold. Yeah Here be dragons Right. This is a risk
52:40
Okay, and I'm not telling you what to do. I'm telling you how to find it This is a risk. There is some work you need to do you've identified. There's a business need it's on your demand map Yeah, that touches a system that has a skill or a capability that you don't have and no one cares about Okay So going down the right-hand side then so this is outside of business need in
53:03
The middle here is where I've got a current skill that I want to get better at Well, this is now elective practice. This is where I go to user groups meetups. This is where I use my own time To my own discretionary time to learn a thing Okay, and likewise below it. It's an aspirational skill that I don't have but there's no business need right? So this is elective learning
53:26
Again, this is where I go and pick up a new skill, right? And as an organization you could choose to have an opinion about that We want to invest in people I want to invest in people and give them time to do this or create internal resources to do this or we just don't
53:40
Right, but it's it's a thing you can choose to do which leaves this top right one, which is there's a current skill There's no business need no one really cares And I'm not really interested in growing it. However, it's a massive opportunity And The reason it's a massive opportunity is this it may be that all of that latent skill I can use to point
54:04
at the open business need gap yeah, and Maybe slay some dragons. So very quick example I was working in a bank and the operations part of a bank and the operations part of the bank is all the unsexy stuff after the tradings happen where you have millions and millions and millions of
54:23
Different sides of transactions and you have to match them all up and it has to add up to zero It never adds up to zero. Okay, that's how matching works and And so and so and it's usually done on big databases and it's usually done with big ugly store procedures because history okay, and there was one Friday afternoon and
54:42
We were looking at a particularly ugly store procedure and the reason they were looking at it because they were gonna Jack it up and shove another if in there. Yeah a new rule Right and the problem with jacking up a store procedure and dropping another if in there Is this when there's only two or three ifs of adding another if doesn't matter Right by the time there's 50 or 60 ifs adding another if doesn't matter
55:03
Yeah, there's never a point where adding an if matters so people don't bother caring about these things And I'm looking through this, you know hundreds of lines of store procedure and the thing that jumped out is this looks really really Imperative it looks really Cody
55:20
More than secretly now just it feels like it's the wrong technology and it was a Friday afternoon and we had quite a bit of downtime So, right, let's just for giggles spend two hours Your time box it two hours and we'll see if we can write that set of rules in Python so Python my back pocket language, so we sat down and we paired and In two hours, we had a Python equivalent to this stored proc and we ran it and it had the same output
55:45
Which one data point, but we were feeling a little bit confident So hundreds hundreds lines of store proc 20 lines of Python The fun thing though was this the stored proc took 90 minutes to run and locked up the entire table of millions of rows
56:01
Yeah, which meant you couldn't run it during the day And so you have to run it at night and also any changes had to come through as a change request and developers had The Python thing for giggles ran in five minutes that wasn't the plan it just happened to write and so Suddenly now they had exactly the same query, but they could run it intraday. No one would notice five minutes done
56:25
So anyway, so that was just a spike and so I went away and I came back a few weeks later and a few weeks Later, what happened is this it had gone viral so someone had jumped onto this thing cleaned it up a lot better than our little spike and it now ran in three minutes and They put a web interface on it
56:40
So now it was self-serve So now the business guys who used to send in through these change requests just popped up a went to a URL Typed in the query parameters. They wanted hit a thing and in three minutes later, they had all their results Right and and so now that became the way that they do that kind of matching now It was just a hack right? It was just a complete fluke on a Friday afternoon. Yeah, so opportunity
57:04
And this is when you bring people with different backgrounds together They look through different lenses different perspectives if you're in Jesse's talk a minute ago She was saying change your perspective You know, they're looking through a different lens And so so this is where we end up then so business mapping
57:24
We start with initiative mapping up here. What are our corporate KPIs? Where do we want to go as a business in the next quarter? few quarters Turn that into a series of initiatives series of programs Which is the demand mapping piece, what are the business outcomes that we want?
57:42
Business capabilities we want to build like the lot the big the big ticket stuff How much we want to invest in those? What skills and capabilities are we going to need and then on the supply side Katie and all the other Katie's? We get the skills mapping and these are both public internal documents
58:01
Anyone can go to the wall and see what the next few quarters of delivery map looks like Anyone can go and check anyone else's skills because they're all we know what people can do But none of this is secret and the great thing is you can do and and Chris started doing this I didn't get as far as this but Chris and Tony grout is another chap He was working with they built an internal tool that would do the dating
58:23
You could match yourself up with this skill And I want to do this thing and when it would do the capacity planning piece for the for the demand mapping All right, so they started to to automate some of this which is really cool And then you end up with you put them all in the bag and you shake it up and you get this thing delivery mapping
58:42
One thing to add is Again, remember this doesn't solve things for you It tells you where to look but now I can look at that that delivery map that Venn diagram and I can say Where am I light on skills and then you get into this concept of skills liquidity? So do anyone know what to do all these finance terms because it's Chris is a finance guy
59:01
They don't know what liquidity is. They don't tell me what liquidity means What's liquidity How easy it is to convert an asset to cash this finance guy It's it's really it's an availability thing. How available is that thing? So if I can turn something into cash easily I consider it available if it's really hard to get hold of that thing. So some stocks trade very
59:27
Infrequently, they're illiquid. It's hard to get hold of them. The people who've got them are holding on to them Okay, other assets are very liquid people are happy to sell them and they're happy to buy them and there's a lot of activity there So you can look at skills in a similar way if I'm light on Python, right?
59:44
That's a very liquid skill. I can teach anyone in this room Python in a week. It's a very easy language to learn It's great fun, right? if I if the skill I'm light on is And a pricing exotic derivatives. Yeah, I'll see you in 18
01:00:00
months of intense training. And so that's an illiquid skill. So this will shine the light on the gaps. But then it's up to me how I respond to that. So maybe for some of those skills, I'll rent them in. I'll get some specialists in.
01:00:20
I'll get some contractors or some outside help. For some of them, I might invest in them the training of people. And again, I'm changing the system of work. For others, I might say, is there a way I can solve this problem without needing that skill? Because I don't have it, and it's illiquid, and I can't solve getting it. So it now becomes a constraint. I'm going to solve this without that piece.
01:00:42
But all of this is about helping you reason about the landscape you have. And then you can start reasoning about how you're going to solve systems in it. And that's all I have. So thank you.
01:01:03
Do I have any minutes for questions, or are we out of time? Oh, fantastic. Any questions, thoughts, reflections, or it's lunchtime, let me eat.
01:01:25
So when we want to build the list of skills, how do you generate that list of skills? The most effective way I know to do this is federate it. So what I do is I'll say to the analysts, what do you think are the skills and capabilities in this organization that make you more effective?
01:01:41
And if you go across different organizations, there'll be a lot of overlap, but there will be specific things. So for instance, one large bank I was working in that has a slew of legacy systems. Yeah, COBOL and JCL and some of those mainframe languages are useful skills.
01:02:01
Deep knowledge of the particular applications, way more valuable. And in fact, in terms of liquidity there, one thing we did, or I observed this thing, and it just made me grin like a child. So there was a team, and this team, one person in this team knew how to look
01:02:22
after this very old system. And it wasn't a hoarding thing. It was that over the years, everyone else had been laid off or left or whatever, and she was the only person holding up this system. And she hadn't had a vacation in three years or something. And one of the guys in her team, a Java developer,
01:02:40
learned COBOL. He said, I'm going to pair with you. You're going to teach me COBOL, not as deeply as you know it. You're going to teach me this system so you can have a vacation. And about a month later, she had the first vacation she'd had. And yeah. That will never appear on his CV. I'm just telling you.
01:03:01
But that is, and this is how teams work, is that they can see where the imbalance is, and they don't see it as, generally, it's not a hoarding knowledge thing. It's a, we have a risk there. We have a risk that people are going to get burnt out or that people might leave or, for good reasons.
01:03:22
They'll always get run over by buses. I don't know anyone who's ever been run over by a bus. There you go. It's always a really rubbish metaphor, right? But people get promoted or poached or leave or do stuff or just change careers all the time. So yeah, so in terms of building out that skills profile,
01:03:40
and again, you can start, so I started small, or relatively, I started at program level. So I had 80 people, and between us, we figured out what the set of skills were that we're used for. And it wasn't exhaustive. It was how do we make decisions? That's all its purposes. Chris and Tony started at a portfolio level. So they were looking across these thousands of people
01:04:02
and coming up with the skills that would be useful across all of them. So you can start at either side. If you have access to the business and you have access to that kind of the exec and then that sort of leadership level, brilliant, because it means you've got a lot more levers, but you can start doing this tomorrow at program level. And it's surprisingly liberating.
01:04:24
So, and so for instance, what you do, the thing I didn't mention, what you do is when you go to our, jump back to, let's go to here, there we go. So each of these pieces of work,
01:04:41
what I'm doing is assembling the team that will, or assembling the group of people that will solve that piece of work. So that's the thing we're solving for. And what you end up with is short-lived groupings of people. And there's a receive wisdom that that's bad, right? We want long-lived stable teams, because they said so, yeah?
01:05:07
Well, at a program scale, well, the thing is you could, if I had 20 people, I'd do this, right? This is still how I would reason about it, but it's just much quicker to reason about it. We do it in the morning, yeah? The first time you do this at a sort of 60, 70, 80 person scale,
01:05:20
it's like pulling teeth, right? It'll be two days of frustration. And then the next time you do it, it'll be one day of frustration. And once you've done, like I say, if you're doing this quarterly, I'd start doing it monthly, right? And then just practice it, because it means you're planning a much shorter timeframe. Once you get the hang of it, you can plan several quarters in half a day,
01:05:42
and everyone's on the page. So you have all the people in the room who are part of this. So you have the business guys, the domain experts, the delivery folks, and all of the support people, like if you can, your HI, security, compliance, one of those guys as well. But yeah, so it goes from very small to,
01:06:02
well, we've done it at thousands. I don't know if it works at tens of thousands, but certainly works at thousands. But yeah, so what you're building is your team, the thing, your sense of identity, your belonging, the team is the program team. So we have come together to build this system,
01:06:20
right, to build this thing, yeah? To deliver this program. Now there are small, short-lived groupings of people within that, and the received wisdom is that's hard. And it turns out that's not hard, right? So every Disney movie ever is like the bad guy comes in to dig up the village and all the villagers, the little old lady and the grumpy guy and the delinquent youth
01:06:41
and the kid with the dog all get together and they save the town, right? The end, yeah? And little bluebirds, right? Because if you have people with shared values, right, we love our town, and with a shared goal, get rid of the bad guy, they will figure each other out very quickly and they will work together very quickly.
01:07:00
They will collaborate well. And I experienced this time and again with ThoughtWorks is there's a bar, right? There's a recruiting bar, you know whoever turns up on your project as a tester is gonna be a pretty damn fine tester. Whoever turns up as a developer is gonna be a pretty tasty developer, right? So you know whoever the grouping of people are,
01:07:21
you've got shared values, because one of the things they hire on is values, yeah? You've got shared skill level so you can lean on each other. And then it's like, okay, what are we gonna solve here? And so the storming piece happens relatively quickly. And the same thing happens here is, and especially once it starts to self-select. When you, the first few times you're doing this as a program manager or program lead,
01:07:41
you're probably handpicking the groups of people. And that's about who likes working with who, who can't work with who, which skills do you need, all that kind of stuff. Once the program team and the organization starts to mature with this, it becomes largely self-selecting. It's like, I really like working with you. There's a thing I wanna learn from you.
01:08:01
This piece of work is coming up in next couple of quarters. Let's get ourselves onto that. Right, and so people start self-forming around the work. So you end up with fluidity within a team. But my team is now what, Spotify would call it a tribe probably. But it's like, you know, my 80 hundred people or whatever, that's my sense of identity.
01:08:22
That's the people that have away days and all that. And then within that you have relatively, and they might be one or two people working on a thing. They might be 15 people working on a thing. You may have individuals who just wander around and never join teams, because they're much more effective wandering around and never joining teams.
01:08:40
A size of business. So this program here would probably be 50 to 150 million. So this is, you know, I've got about 80 hundred people and we're doing a bunch of stuff. So what I'm saying is it works at that kind of scale. It can work at a much smaller scale as well.
01:09:01
The problems become easier. The more zeros you add, the trickier it gets. It seems to be what happens. I'll take one more. Oh okay, so I can't take one more. So we're out of time.
01:09:20
Thank you very much. Enjoy lunch.