I'm Dan Diaz.
Look after Customer Success
and partnering at Transparent Choice.
We are a software provider with a focus
for some years now on prioritization.
And, um, latter is prioritization.
Um, how, how prioritization can drive ROI, uh,
with better portfolio management.
So if you're here to drive,
improve your portfolio performance
and you realize prioritization is the way to do that,
then you are in the right place
because we are privileged to have, uh, Mr.
Mike Hannon with us, um, expert in the field, friend
of the company, longtime collaborator and partner.
Um, Mike is, uh, going to, well, you know what, Mike,
you tell us what you're here to do
because you'll set better than me.
Yeah. So I'm Mike Hannon.
I've been doing this project portfolio stuff a long time.
Uh, what, what I'm gonna share with you today is a mix of,
uh, as Dan said, hopefully clever stuff,
but also some stories of humility
and how I had to learn some things the hard way,
which ultimately is a great way to get to an even better,
uh, solution, right?
So if you're not familiar with this story of Goldilocks, uh,
it's basically a, a, uh, what do you call it?
A fairytale or a child's fable or something like that?
Fairytale. Fairytale or a Yeah, I think so.
Where, um, uh, you know, there's a little girl that being,
that was being threatened by three bears or something.
Now I'm goofing it up, aren't I?
Anyway, the point is the ridge was either too hot, too cold,
or just right, and, um, everything was either too little,
too much or just right,
and it was really hard to find the just right.
And so, uh, there's similar story here
that we'll share today about how
to boost project portfolio performance.
Okay? So let's dive dive into it.
So it all starts with a dilemma.
Uh, when I was a project portfolio guy in the hot seat
and I was under pressure to drive up performance, uh,
this was my belief.
I needed a complex project portfolio management tool.
I needed implemented well, I needed, I needed loaded
with good plans and all sorts of other data
that took quite some time.
Um, gotta get everything properly prioritized, which
of course, a HP and transparent choice are experts in.
I didn't know anything about
that from my PPM tool anyway yet.
Uh, and of course, we have to keep it updated
and we have to have everyone submitting time sheets,
hitting the right project charge codes,
or else all our data's gonna be off.
And so spent a whole bunch
of time trying to figure out how to get that working.
And ultimately it did work.
But boy, it was, it a heavy lift
and it never really was quite as, um, useful as,
as was promised, by the way.
Ooh, by the way, uh, with the advent of scaled agile tools
or agile at scale solutions, I think some
of this got a bit simplified.
Uh, for example, a lot of 'em don't even bother
with time sheets and project charge codes.
They just have dedicated teams,
and we know how much people cost against, uh,
their a hundred percent full-time salary against,
uh, just a single project.
So, okay, fine, but still, uh,
way over complicated if you ask me.
So on the other side, uh, when I got
to work in a smaller organization,
a bit more in startup mode
or maybe, uh, early scale up mode, uh,
we didn't need any of that, right?
A few simple rules of thumb, Hey,
what really drives our cadence around here?
Let's get this machine humming
and let's make sure I understand when we hit some glitches
or stumbles along the way so we can fix it.
Uh, and that felt great for a little while until we got
scaled up so big that this no longer worked, right?
So this sort of overly complicated and super simple,
and yet I still needed something in the middle like
Goldilocks to figure out like, how does this really work?
So I figured there must be a better way.
So some years ago I stumbled across
what I thought was a better way.
Before I dive into all that, I wanna make you all a promise.
Uh, you're investing your, the most valuable thing you have
with us today, which is your time.
So the least I could do is promise to make it worthwhile.
Uh, uh, I want to give you Goldilocks, right?
Share a way to marry the speed
and simplicity of the intuitive approach with the power
and scale of the, uh, complex PPM approach.
Why? So that any leader of any portfolio of any size
can drive up their performance, uh, with just
basic intuition and a modest investment in time.
Uh, I think it could even be done in a matter
of just a few hours.
Um, but, you know, some things may, might be,
need to be refined over time.
Um, so yeah, just basic intuition
and a modest investment in time.
I'm very excited to, uh, get to that,
and I promise I will by the end of the session.
So let's start with a, a, a key concept.
I'm curious if folks wanna pop in the chat, if any of you
have ever seen either this special kind of traffic light
or this thing from fluid
dynamics called a fluid density curve.
Take a moment to pop in the chat.
There's any fluid dynamics experts out there,
or traffic, uh, traffic engineers perhaps.
Have I put everyone to sleep already?
I mean, it was quite a niche question.
Fair enough. Statistically,
You might need a bigger audience to
get a yes out of that group.
That, uh,
So suffice to say that, uh, if you've seen this,
I got a y from Mike, very, uh, succinct, Mike, thank you.
Um, if you've seen this traffic light, you,
you can recognize it's not really the normal kind where
that tells you to stop, stop and go in an intersection,
but it's on an on-ramp to a highway, um,
or a freeway or main thoroughfare.
And the idea here is we wanna limit, uh, the, the congestion
so that things can flow well.
So in terms of flow density, we're trying
to keep the density closer to the top of that peak so
that flow could be maximized.
And if we ever let too many cars onto the road, we, we,
we've all felt what that feels like
to be sliding down the right side of that tail
when things aren't really flowing very well.
But there's sure a lot of us
out there trying to get somewhere.
So if you take this concept to project portfolios,
uh, the, the inevitable conclusion is, well,
we're probably almost always on the
right side of that curve.
We probably need a solution kind of like that traffic light.
And if, uh, if I have no other information
and I need to take action fast, I take
what I call the sledgehammer approach.
And, uh, this is worth a quick story.
I had a CEO of a small, uh, software company, uh,
find me through a friend of an acquaintance, of a colleague
of a friend kind of thing.
So said, uh, you, you, you come highly regarded, Mike.
We don't know each other and I'm afraid, I, I'm almost out
of money with my startup, so I
can't even afford to pay your fee.
So I'm asking, um, with pretty please
and a cherry on top, would you give me 20 minutes
of your time to help me save my company
even if I can't pay you?
And I said, sure. Um,
and long story short, I was thinking of
that flow density curve I just showed
and I said, uh, cut your initiatives in half.
And he is like, well, that seems pretty extreme.
Why would I do that? I said,
so you can get things flowing again.
He goes, how do you know things aren't flowing?
I said, I, I don't, I just met you.
Um, but you said your company's in di Straits
and you need one piece of advice you can implement today.
That might help. So that's, so that's all I can give you.
And he goes, well, how, how do you know it's half
and not 20% or 80% or some other number?
I said, well, I don't, um, I don't know anything about you
or your company other than you're desperate
and you're willing to try anything and you can't afford me.
So that's the best I can give you. It's my sledgehammer.
Right? And long story short, he went
and, uh, uh, tried it.
Um, it turns out he did have, it was only maybe five
or six initiatives that, uh, were all designed to kind
of get him to the next level
and leapfrog his primary competitor.
Um, but truth be told, he would've been much better served
to do something a bit more minimal first,
even if the value proposition is nowhere near as strong,
it's at least some way to start the revenue engine humming.
And if you could just flow that
to market first and get something going.
So a lot of us have heard of all this with lean
and, uh, minimum viable products and such.
Um, but I take a flow lens to it
and just say, uh,
if you can actually get things moving faster, uh,
by reducing your flow density, it might work.
And it did. He called me a couple months later
and said, yep, we got something to market.
It actually was a bigger hit than we imagined.
We're off to the races.
The investors are not shutting us down.
Um, thank you so much. And I said, okay, great.
Please refer me out, um, as the, the way to, you know,
give me some kind of re recompense.
And he was kind enough to do so. So win-win.
But that's the sledgehammer approach.
And how many of us are really in such a desperate situation
that we have to reach for the sledgehammer?
Um, you know, for in, in his case, you know, he sort
of had nothing to lose at that point.
Hopefully, most of you are not in such a desperate
circumstance, and you might want something a bit more
surgical than a sledgehammer.
So let's get to that.
So to refine this concept on flow density a bit further,
we're still gonna talk flow stuff.
You can see, uh, in this picture marked with a letter A,
if our goal is to flow water outta that bottle as fast
as possible without altering the bottle
and without altering the laws of gravity, um, or the,
or the molecular properties of water.
And all we did with our management technique is flip it
upside down and, and hope for the best.
We would get some flow, uh, the bottle would empty.
And, um, as you can see, it comes,
I should turn off the chat 'cause ASOC just
asked me if I'm a hydrologist.
Maybe I should, maybe that's my next career, asock.
Um, so you will get flow, the result will happen,
but it sure will take an unnecessarily long period of time.
And that's to be expected since we haven't really applied
any sort of management techniques at all, other than
flipping it over and, um, trusting
that gravity will do its thing.
What you can see, of course, is there's a lot of movement,
a lot of collisions, a lot of activity,
and not a lot of flow.
So similar to the flow density curve, we we're kind
of on the far right tail, um, because of the bottleneck.
So if I were to ask you all, like, if anyone wants
to pop in the chat, uh, a better way to do this,
I'll give it all a moment,
Mike.
Yeah, Mike says swirl, right? Exactly.
Um, uh, and I swear Mike
and I did not coordinate in advance, um,
uh, a shock.
You're too smart. Let's delete a shock's comment.
Actually, let's, let's defer, let's defer his
comment for, for just a minute.
Um, and yeah, let the air in, right?
So the key is we have this scarce resource called the
bottleneck that has
to let air in at the same time water is coming
out if we want better flow.
And so as Mike, uh, cleverly suggested spin it
or Creative vortex, and indeed we can see that
that is generating much more alignment.
So we have everyone kind of working together.
All the molecules are doing what we want with a minimum
of management effort to get it started
and, um, and keep it going.
And indeed, as you can see in the bottom,
that double the flow with one simple management change.
Uh, and if we open the mic to a shock, which we won't,
but, um, but if we let him present letter C, uh,
I believe this is probably
what he had in mind when he suggested the straw.
And again, it's very similar to be in
that we're just finding the best way we can
or trying experimenting with ways to allocate
that bottleneck resource to let air in
and water out in better and better ways.
And you can see we don't even need
to apply any management effort to getting everyone aligned.
Uh, we just trust that with gravity
and, uh, a clever engineered solution
that's also quite simple, right, in the form of a straw
that we can allocate that bottleneck more effectively
and get, uh, even better flow.
And as you can see, it doubled again.
So might this take us beyond the sledgehammer
to something a bit more fine tuned?
Yes. And so I, I,
I learned about this thing called staggering,
probably too late in, in my career.
I wish I'd learned it many, many years earlier.
But nonetheless, the simple concept, which if you're a, um,
a veteran of Transparent choice webinars,
or you've heard me speak before,
you might find some of this familiar.
Uh, I promise none, not much
of this is gonna be repetitive just enough
to get the concept across if you have not seen it.
So the notion is if we, uh, have a project
and we got some resources,
and those resources have some area of specialization, um,
then we might have this kind of approach
where we can reliably knock out this project in seven weeks
with, uh, sort of a simple handoff scheme.
Uh, certainly you could apply a cross-functional
team approach here as well.
Um, but in my mind, all that would do would sort
of blur the lines between A, B and C.
The handoffs might not be as hard, and that's fine.
Um, if we can collaborate
and achieve a seven week result with, uh, three types of,
um, experts, wonderful.
The question is, what if we have three projects,
not just one, and we're,
and no additional resources to handle them.
Well, if we apply the notion of the sooner we start,
the sooner we finish, we'll just try
and get everything started right away.
And as you can see, even if this dilution
of focus from a focus two week task for Resource A up here,
uh, to a diluted focus approach here where they're jumping
around, I'm still assuming it'll only take them two weeks,
even though common sense tells us
diluted focus will delay us much more than that.
So even if our diluted focus does not delay us at all, uh,
we can see that we have sort of built in delays here
and everyone's highly utilized if you kind
of expand this out well into the future.
Everyone's fully busy all the time.
And if you were the portfolio manager of this portfolio,
and I was the one funding it, and I came to you
and said, give me more completed projects, please,
within 17 weeks, you would say, give me more resources.
And as, uh, properly trained project managers, that's indeed
what I did for, uh, the early part of my career.
And it got me promoted and it worked.
Um, and I would usually get more resources, right?
But, uh, but then I learned there might be a better way if
you compare the simultaneous, uh, to, if we were
to stagger according to the bottleneck,
which in this case the bottleneck resources, resource B, uh,
it's almost like sticking a straw into the bottle, right?
Because without any additional resources, we get
four projects in,
and the first one to get kicked off finishes far,
far earlier than up above.
So we get to cash, you know, cash that in,
whether it's in revenue or, or other impact terms,
and we can actually get more projects done
without more resources.
And oddly, as shown in the bottom
or counterintuitively, uh, two thirds
of our resource pool is one third idle.
How could that be? So, uh,
one key thing here is you have
to have these project prioritized properly,
which is why I turned to Transparent Choice some years ago.
I had heard of the analytic hierarchy process
that they are experts in
and have great software solutions for,
and thought, great, well, uh,
my clients are having a hard time
keeping their priorities straight.
Um, therefore the staggering thing won't work so well.
Let's get, uh, transparent choice into the
mix to help solve that problem.
Great. So sounds awesome.
I thought I had found pretty, uh, effective path forward
to the challenge of boosting project portfolio performance.
I went into business as a consultant for IT and a coach,
and, uh, in some cases I would run games like this, right?
This gamified simulation showing that, uh,
Justin playing a silly game,
they can get this much more done.
And if you were to extrapolate
beyond Project four on the top there to 5, 6, 7, 8, 9,
you would basically get nine done in the same time
as you got three done.
So that's a triple right, A three x. So, wow, it's simpler.
Uh, it's way faster. It's kind
of like the straw and the bottleneck.
Wonderful problem solved, right?
Well, there's a harsh reality that I had to face.
Uh, most organizations actually still find
this a bit too difficult.
The prioritization fights are, um, tougher, even with a HP,
which solves a lot of that toughness
and gets a lot more harmony.
Um, you know, some people, uh, still find it too difficult
to get everyone on the same page.
And oh, by the way, my simple cartoon graphic is never
anywhere near reality for most organizations,
if I need at least decent project level plans,
and if I don't have some of them, if some of them are bad
and I'm basing the entire resource flow model on a,
a few bad projects in the mix, then those,
those few bad apples can really, uh,
poison everything, right?
So it was still too complex, even though I hated
to admit it, and it took me years to admit it, um,
and too hard to keep current.
And often I would find clients get great results initially,
and then abandon it over time,
and it would drive me crazy, um, realizing that, you know,
you were so close, you had it.
So I thought I had found the Goldilock solution,
but I was forced to accept the harsh reality that at least
for most I had not, it was, I would say probably 80%,
um, organizations.
Uh, it didn't really help on a sustained basis.
So I did, but what to do?
Well, I did what any rational human would.
Uh, I started by denying that it was a big issue.
I spent a few years there, um, that was fun,
um, for a little while.
Uh, then I got angry about all my lazy clients
that wouldn't put in the effort required.
Of course, it was substantial effort,
but I was kind of ignoring that little detail.
Um, I bargained with myself,
and some of that included, well,
if I just did a little extra work for the client
to help them through this heavy lift, then once they get
to the other side, they'll just kind of coast down,
you know, coast down the hill once they get to the top.
Uh, of course, that analogy wasn't quite right.
Um, I was constantly pushing the boulder up the hill,
and if you're familiar with the Greeks, the Greek myth
with Sisyphus, usually the boulder rolled back on top
of me and I'd have to start over.
So after a while, bargaining with myself got kind of tiring.
Um, so hopefully you're all seeing like denial, anger,
bargaining, and depression.
Well, here's the depression part.
Um, get depressed at the sad state of affairs.
And I started blaming whoever I felt like blaming, uh,
bad portfolio leaders, software vendors
that overcomplicate things.
Um, the agile industrial complex,
project management Institute, whoever, right?
For making this so difficult.
Uh, and then of course, um, the final step
really here is acceptance, right?
So once I got to the point
of saying, you know what, it is what it is.
Um, I thought I had Goldilocks,
but I I actually don't, at least not for the large majority
of companies and organizations out there, that
of course unlocks the, well, how might we overcome this?
And so I started chatting
with my friends at Transparent Choice about this problem,
and we kicked a bunch of ideas around for some time.
And then this gentleman, Dan showed up
and he started influencing the direction of the product,
and AI started coming around
and, uh, boom, without me even realizing it,
they had crafted something
that I think truly finds the Goldilocks solution.
And that's, uh, sort of the punchline, what we want
to get you guys to today.
Uh, we're gonna show you a brief demo of why we think,
why I think that, uh, transparent choice has helped me.
Um, once I, once I got to step five here, right?
Accepted the reality and moved on.
Um, well, there are some clever ways.
So with that, I would like to turn the calm over to you,
Dan, so folks can see for themselves
and judge for themselves what Goldilocks might look like.
Awesome. Cheers, Mike. All right, let's get this running.
Okay, you can see the screen. We good?
So We are gonna start here with,
uh, a HP.
So Mike mentioned a HPA little bit briefly.
We're not gonna go into it in detail.
We have like a regular webinar where a wax lyrical
for some time about a HP.
But in simple terms, a HP is a way
of turning your strategic objectives into a number.
So the, the point is, why do we do projects?
Well, there's a bunch of reasons, right?
We wanna make money, we wanna save money, we wanna deliver
value to stakeholders, we wanna grow the business,
we wanna be strategic, we wanna be good for the, the,
the society and environment.
Lots of good reasons to do projects.
Putting all those reasons into a structure
that we can turn into a number is critical
for the stuff Mike described,
because while it's a bunch of kind of fuzzy feelings,
you are never going to be able to use any kind
of mathematical solution for making it better.
So there's this first stage, very human right,
why do we do projects in a framework?
And again, Mike alluded to it, this is a human challenge
because having a leadership group
who are pulling in different directions means you are pretty
much snookered from the beginning
because you are gonna be pulled in two in,
in many different directions, being told to do one thing
by one person, one thing by another person.
We see this time, and again,
you can't successfully deliver a portfolio
unless you have a clear direction from the executive group
to define what actually success looks like.
So this is where we, we go a HP, right? Define success.
And there's a, there's a, some nice gamified ux, um, around
turning that sort of approach into, uh, data.
Again, we'll, we'll go, we'll do that on a, a, a,
a software demo, uh, another time.
But the point is, we build a structure
and then what we're gonna do is get this quantification.
So the point is, we talk about getting a, a, a value
for all our projects, right?
All the good stuff Mike talked about is made easier
if every, you know, project in that queue has a number
between zero and 100 saying
how valuable it's to your organization.
So all those kind of wooly, fuzzy factors,
they're all in here, but they've been turned into data.
So they are quantifiable.
And, and if we roll back to where Mike started,
this is a bit like, uh, that, that, that stoplight
to get onto the, the freeway.
This is saying, what is valuable,
what should be going on next?
So actually, it's not just a queue
where you wait your turn and then you go on.
It's, uh, it's, it's actually prioritized queue.
If you're an ambulance, you go first.
If you're a bus, you go second.
If you are carrying, you know,
someone important, you go next.
The, the, the idea is that it goes backwards.
So you're getting the most important vehicles
onto that road first.
Uh, and it's the same with your portfolio.
You're getting the most important projects, vehicles
for value onto the right first.
So we are quantifying our portfolio.
We are coming up with pretty charts to do it.
Now, there might be folks
out there that have done this before.
You've got a weighted spreadsheet, uh, that, that, that,
that gives you a number.
The critical difference, you know, we believe in terms
of a HP and, and,
and working through the, the, the approach we've built is
that you are building buy-in to that number so
that when people actually see this chart, they're not going,
yeah, but that's nonsense.
Yeah, but I don't believe that.
Yeah, I'm just gonna ignore it and do my own thing.
They're kind of going, you know what, this makes sense.
We, we, we went through a proper process.
This is fair, this is structured, this is a good answer.
So we need to then commit to
what comes next and what comes next.
Well, this is where we start getting into the kind
of AI solutions.
This is where we start with our kind
of Goldilocks hat back on of saying,
how can we provide something that is sophisticated
but not massively complicated to use?
So we've built here a scenario that just said, pretty simply
stretching the metaphor a little bit,
but how can Goldilocks get as much porridge in her bowl
as possible without overflowing it?
Um, and, and, and what she's, what she's gonna try
and do, she's, she's got some constraints here.
So she's got limits, right?
She's got a limited amount of different types of resource
that, that she can have to draw upon.
But what she wants to do is get the most value possible.
So, and now often when people talk about maximizing value,
it's a little bit like, you know, b******t bingo.
It's, it's sort of one of those words that
that's used quite liberally
that doesn't actually mean a great deal.
Um, or at least it doesn't mean the same thing to, to, to,
to different people around the table.
And again, the, the point of a HP is
that value means the same thing to everyone.
Value is actually a number.
And in this case, value is a number with two decimal places.
So the point is that you are creating value
by picking the right combination of projects to get this to,
to, to, to deliver the maximum value.
So this is sort of, you know, almost to Mike's point,
this is equivalent of the straw.
So this is trying to, uh, get the right set of projects
that mean no single bottleneck is gonna break
your portfolio.
Because of course, you can see here, right?
These are my bottlenecks
and I've got a couple that are looking pretty full.
Okay, that's fine. We can work around those, we can, we can,
we can respect that in our delivery cycle
three that are pretty full.
But the point is, normally they would be more than full.
And obviously graphically you'd struggle to represent
that on a pie chart, but we all know the reality if that, if
that is 120% full, everything is gonna start to fall apart
because all of a sudden you've,
you're gonna ruin your flow even before you started.
You're going to ruin your flow
because you know, someone is gonna drop it
and they're not gonna drop it 'cause they're incompetent,
they're gonna drop it because they've got too many projects.
So we have to have a car park, we have
to reject some projects.
And having the honesty to say we are not doing everything,
but I think is critical in terms of, of being able
to deliver value from your portfolio.
So, and I think, as I said, all this, you know,
there's an AI component to this, which is effectively,
you know, the algorithm will help you pick the right
project, click the button, apply constraints,
and you're getting really quick scenarios, um, stood up in,
in seconds so you can start to sort
of play with the parameters.
Maybe you are able to, to, you know, do some wiggle room
around these, um, constraints.
And hey, Dan, real quick, yeah, for, for folks
that might already be familiar with good prioritization
techniques such as a HP
or whatever, this may not look, uh, quite new yet,
but the, the punchline's coming.
So stay, stay, stay engaged, everyone,
this is, we're super excited about,
Is that what you, your way of saying hurry up.
But, uh, yeah, this
Is, we have plenty of time.
I'm just, you know, this
Is newish for us, but we are trying to sort of, as I said,
make it really easy to then take all that sort
of data goodness, and turn it into actions.
The so what from prioritization,
because the theme with, with this that we've, you know,
the journey we've been on with prioritization says
actually adding value is, you know,
prioritization's the right thing to do.
I think we can all feel that,
but actually plugging it in, making it deliver value is,
is critical in terms of turning the potential into ROI.
So yeah, punchline, right?
So we have built some of these optimized,
we've optimized our backlogs
and maybe we've done this across a
couple different portfolios.
So we've got, you know, a classic sort of setup here.
We've got the business and we've got it backlog.
So value means different things for those different folks,
but they both deliver value in their in own way.
And they've both optimized
what they think they can get done in their own way.
And we can have different scenarios
where one gets more than the other,
but let's build this base case out,
divide up those constraints,
and actually then bring it back together
and say, right, we are not gonna get all this done.
We can't get all this done at once.
And, and we've gotta do some of that kind
of staggering goodness that
that might took us through in the beginning.
So yes, we've got our list,
but actually what we want to do is we want to do some ai.
So I'm, I'm pressing the button live,
which it's a bit like working with children and animals.
You should never work with a live, uh, algorithms.
But I did it anyway because, you know,
andray, here we go, it works.
Uh, so we've just analyzed 147,000 different permutations in
terms of how we can put the Lego set together.
Uh, it's come up with a bunch of different ones that work
and it's given us the, the, the favorite.
And it's just dropped it here into a simple kind
of graphical view that says, look,
you gave me all these projects.
I'm telling you when to start 'em,
I'm telling you when, when, when they'll finish.
And this is going to then give you
that staggered straw up the bottle type return.
Because what you're able to do is say, look,
you can start these ones now, but don't start these ones.
So you've got your optimized portfolio,
but you know, it's not gonna be bang,
everyone starts the race together.
So this is a bit like you imagine, I think of this as sort
of like a marathon or something.
You know, you don't want the elite runners stuck behind,
you know, the guy wearing a novelty outfit.
Um, and you don't want everyone just
trampling each other starting at the same time.
You want 'em to go off in, in reasonably, uh,
manageable little cohorts.
So, so they can actually, you know,
run as fast as they can run.
And the upshot of this is that you can then
feed this into your, you know, your,
your Microsoft delivery, your Asana, your PPM,
whatever it is, you, you know,
that's your goldilock solution for, for managing projects
and, and crack on and do it.
Um, and you can iterate.
So as reality changes, you can update your plans,
update your schedules, um, and, and, and, and,
and go around the cycle again.
And because it's driven algorithmically,
this is not a complicated, you know, exercise
where it takes you ages to do this balancing.
You are pushing the button, getting the outcome
and working with that.
And, and what we are actually sort
of working on right now is, is also then making
this almost like a kind of scenario based approach.
So I think I alluded to it here,
we've got different scenarios built in.
So it's not just about saying,
here's the best answer we can come up with.
It's about providing your executives with choice.
So here's maybe base case, base case works.
You can get base case, base case will deliver you, you know,
this Gantt chart
and this is a financial exercise, here's a here and this p
and l, this set of financials coming from your portfolio.
Uh, and we, we know we can reliably deliver it.
'cause we're not talking about fairytale, uh, kind
of business plans with too many projects,
but maybe actually we want something different.
So maybe what we want to do is steal a little bit
of resource here from the it backlog, the BAU work
and pump it more into the growth portfolio.
'cause you know, that's, that's
what we wanna do is maybe some shortcuts we can take over
here, which we think are reasonable risks to absorb.
And then we're talking about a different return.
The, the growth profile will look different
because we've got more growth projects, not
because we're saying yes to stuff we can't deliver,
but we're saying, why don't we do something different?
And we're offering choice based on data, which again,
is our, that's our Goldilocks solution.
So some execs might like
their porridge a little hostile than others.
So we, we, we can have that kind of inherent in, in, um,
the user experience.
So the, I see the pump, the, the, the,
the chats been pumping away and I've been yaking on.
Um, I think I've come to the end of my, uh, my product demo
unless there's anything, anything from the chat we want
to kind of dive into if I've forgotten anything.
Yeah, let me, let me just throw my own little punchline,
Dan, since obviously I'm pretty excited about this.
Um, the notion that you can just feed a few basics about,
uh, your resource constraints without having every single
resource loaded and leveled and,
and strewn across multiple, um, resource level loaded
and leveled project plans and resource histograms and,
and then checking whether those resource profiles are
actually likely to play out in reality or not.
And then having all those debates, uh,
you're just channeling your intuition in a,
in a few key spots here.
And then asking the computer to run through a bunch
of simulated scenarios.
Kinda like if you, if you've ever seen where, um, hey,
these two sports teams match up
and we did a computer simulation model
where they might play a thousand times
and one team wins 592
of those thousand times or whatever, right?
Mm-Hmm. It's sort of like that.
So, uh, over time you can kind of see patterns
and probabilities and trends likelihoods
and go with go with that as long as your intuition validates
that that seems about right.
Yeah. And, um,
and you don't need all these complex resource models
and project plans, et cetera.
That's a really good point you make, Mike, is that
the kind of concept here is
that you're approaching portfolio management from
a top down perspective, not from a bottom up.
So if you start in the weeds
of real detailed resource up project plans,
you'll simply never get to a point
where it rolls up into the goals of your organization.
So we very much, you know, believe in the philosophy,
you start with the goals, you start with those,
those high level value objectives in your a HP model, um,
or in the different a HP models for different portfolios.
And you start by then coming downwards
and answering the next question of
where should my resource be?
What projects should I be doing?
And it's only when you get into the teeth of execution
that you start taking on that extra weight of detail.
And if you go straight to that detail,
you are gonna have no flexibility in order
to have the agility needed to get project
resource in the right place for your strategy.
Yeah. I have another interesting point.
Um, if you remember my diagram
where we staggered based on resource B mm, right?
Resource B is sort of the natural pacesetter
or drum B for the portfolio.
Well, what if you don't really know who your resource B is?
What if your intuition, you know, you look around
and you just see everyone's so busy everywhere,
it looks like there's bottlenecks everywhere
and, uh, you know, you,
you have no insight into what's really
the natural pacesetter.
Yeah. Um, this, this new, uh, a HP
AI model will actually run a bunch of scenarios
to help you see where your
bottleneck probably is going to be.
E Exactly. So this, then when we kind of look back
to the optimization, uh, view here, um, you, you can see
for example, the, the, the little pie charts at the bottom
are calling out, right?
What, what, what, which bits
of your resource model are breaking first?
Which bits are you packing in?
Now, this is all kind of dummy data, so it's probably not
as, uh, it's probably a bit more uniform maybe than,
than reality where you tend to have one
or two clear bottlenecks.
But, but the reality is that, you know,
if you see this at the beginning,
you are more likely to be able to solve it.
If you ignore this at the beginning
or you just don't know it, it doesn't mean it doesn't exist.
It exists and it's gonna quietly creep you up
and bite you on the ass at some point
during your delivery cycle.
Um, and, and
Say a quick story on that. And
then I, I know we do have a couple questions,
and I promise we'll get to them all, um,
unless you suddenly overload us with 20 more or something.
But, um, I had a scenario with a client
where they bought off on the staggering model.
They had the political courage
to do real good solid prioritization.
They put all the projects in the portfolio on hold
and resequence them according to the cadence of
what they thought was the natural pacesetter.
And in their case, it was an it organization
of a few thousand people.
And they felt like our, our very top senior architects
that had been around since the merger
and know which systems were decommissioned
and which ones had to be shortcutted
and which ones had weird workarounds.
And oh, by the way, now we've gotta, uh, attach mobile apps
to these old legacy systems and how do we do that?
And those guys, uh,
and gals were, um, the ones that knew
where all the bones were buried.
So of course, they're the natural pacesetter.
So they had the political courage to stop everything
and resequence according to that natural pacesetter.
And after a month, nothing got better.
You can imagine just the, the red faces
that I had to deal with.
Um, after that. Now they had some great
learnings from that experience, right?
They learned, okay, it's not where we thought it was.
Well, that's great insight.
Now let's imagine, uh, if you know where it might be.
And indeed, their architects very quickly we're able
to tell them, well, we're waiting on stuff upstream.
Uh, so the natural pacesetter must be upstream,
which was actually in the business.
Um, so that was a very, uh, risky and expensive
and uh, and required massive amounts of political will
to even get to that learning.
Um, this, doing it in a safe simulated environment here
could get you to that same learning without all of
that courage and risk and time.
Yeah, absolutely.
And, and, and it's really,
you did mention political courage.
I think you still need political courage.
Hopefully this is, this could be, this could be your shield
or possibly your sword as you go into your political battle,
uh, as opposed to kind of going in,
in your metaphorical under crackers, um,
waiting to get slaughtered.
So this is, this is about, um, this is about enabling,
you know, bold leaders
who recognize this is a situation and it needs to change.
Um, but to mites kind of like sequence of denial.
There will be a point when you go, oh,
are we mature enough for this?
Have we really got leadership buy-in?
Are we ready to take the leap and do things differently?
And, and do I really have
to risk political suicide in order
to get something moving around here?
Yeah. And what we always say with folks is, you know,
let's get the, let's get the big dogs in the tent, uh,
early doors in the process.
So, you know, it's, it's taking some of those kind
of leadership people on the, on the journey,
so they understand that, you know,
the, the model is for them.
This is not a task for them.
This is a tool for them, you know,
that this is an opportunity for them to take more control
and to get better results, to get better return.
Um, but they do need to commit to kind
of supporting and making it happen.
So, you know, a HP and, and,
and, you know, scheduling is really about honesty,
data led collaboration, uh, as opposed to sort
of old school ways of doing it. So just, just
Make everything look green.
Everything look green. Exactly.
Everything's all good until it isn't.
And then we'll leave and get another job. Uh, hey,
So Mike Clayton put a question in the q
and a saying, how does the sequencing algorithm allow
for potential delays?
Yep. If an early project delays
and resources get tied up, then you know,
there's some ripple effect downstream, right?
So how does algorithm allow, uh, you know,
to catch that ripple effect?
Yeah, absolutely. So, you know, part of the reason that,
you know, we, we believe this works with,
with the algorithm approach is,
is the simplicity and the quick turnaround.
So, uh, I think I had a thing flushed up a second ago. Yeah.
So you have a little plan here
and you, your plan's got your best guess in it, right?
Uh, best guesses don't always turn out to be right.
So you might go in and update a plan that's in flight.
Uh, you might link it up to a, as I say,
a project management tool that's got more detailed data
and estimates and things captured and pop 'em back in.
So you can have that kind of constant refresh cycle
that just says, okay, let's change these estimates
because we've got a slightly different set of data.
Press the button again. Okay,
maybe these three projects are gonna have
to move back a little bit to make way for this one.
And also then having that kind
of governance cadence that sits on top.
And at some point just says, from time to time,
hang on a minute, this project's now twice
as expensive in terms of time.
Hang on a minute, maybe actually we'll challenge some
of the benefits of this project
'cause they've moved as well.
So again, it's political honesty saying
actually maybe mathematically this project
isn't a great choice anymore.
Um, and, and, and,
and we need to kind of rerun that prioritization process
and say, we prepared to say
the cost remaining versus the benefits
expected no longer makes sense.
Hey, so let me add onto that, Dan, that, um, you know,
if you imagine the scenario I painted earlier
where we were juggling multiple projects at the same time
and everyone was jumping from project to project mid task.
If you're trying to understand the ripple effect
of a delay on one of those projects, uh,
you have a pretty simple answer.
It will, it will, it will delay everything, right?
Um, and of course that's not a great,
that's not a great outcome.
If you imagine the same scenario in the staggered model
and the project that I have,
my pace setting resources working on get stuck
and it's gonna take a week or two longer than we thought.
Well, we can easily see the ripple effect of that, right?
We know we have to, to re-stack
reschedule the staggered starts for a week
or two later for the next projects.
Similarly, if Murphy does not show up
and things go better than we imagine, oh man,
we're set to finish sooner.
Maybe we should tee up the next project,
start a bit earlier, and, um, you know,
we often hear executives ask to push things to the left,
what, you know, can we please start things earlier?
And the result is a traffic jam, right?
They're shoving more work onto the system before it's ready,
and we're on the wrong part of
that flow density curve again.
Well, the staggered model can, can give us a way
to push things to the left without destabilizing our system.
Uh, and so this model that, um, that Dan is showing, um,
helps you see all of those things pretty, pretty readily.
And, and, and yeah, my, I mean, you're alluding
to another part of the, the, the solution.
We, we've not got into a massive detail,
but the kind of the concept of buffering, um, that says,
again, when we do our resource allocation,
particularly if we've identified our bottlenecks,
we might be more cautious about buffer and, and,
and having some kind of holdback.
So we want to have a little bit more buffer
around the one we know as a bottleneck.
So if something does go wrong, then we are more adaptable,
uh, to respond to it. So
You sound like a theory of constraints expert. Dan.
I'm, I'm, that's because I'm an expert in sounding,
sounding good with a small amount of knowledge,
but, uh, no, I've just listened to you before, Mike.
So we've got another, um, let's see, it's, uh,
Steven Jenner,
that was Mike's point about a few poor project schedules
mucking things up addressed.
So I imagine, in fact, let's imagine, Steven, you,
you're like the worst case scenario.
Let's imagine we had schedules that
looked like we were gonna,
it was gonna take just a couple of months.
Simple little projects don't even need any
of our scarce bottleneck resources on it.
No big deal. And in reality,
it 10 times more complex than we imagined we'd completely
goof the scheduling and the resourcing.
Um, how does it, how might this solution help us, Dan?
Yeah, so I think we, we alluded to it before.
One is that kind of governance cycle that sits on top
and just says, as the data updates, the value
for money updates, right?
So there's, there's, there will be a point where
that benchmark affordability just drops.
So you need to always keep an eye on
actually is this delivering value threshold
and it's value based on the value
and the cost as a combination of data points.
So value for money should be a benchmark.
If you're below it, then maybe it's not worth doing anymore.
You know, I didn't even ponder that aspect.
'cause if we're really struggling with this project,
that surprised us somehow with how much more complex it was,
it's quite possible that the additional complexity, time
and cost and resourcing fundamentally altered the, the,
the value proposition of that project in the first place.
Oh yeah. And so often we're just blindly going,
you know, like, well, it was approved, it was funded.
Yeah. Uh, you know, everyone wants this project done,
it was prioritized number eight or whatever.
Um, well, maybe it's time to reprioritize. Yeah.
And especially if it's a bad apple, let's get it out the,
out the out of the barrel.
Exactly. I mean, we prioritization should be a, you know,
a, a threshold for value.
It shouldn't be a gate, a one way, a gate you go through
and then that never to see it again.
Thank God my business case got signed off.
Well, hey, let's, let's get spending.
Cool. So Ian asks, uh,
what minimum project delivery capacity data
do you need to feed into this system?
Uh, as in how simple can we get? So very simple. Um, uh, I
Say this is my favorite part, by the way.
Simple. Yes. Look, so at, at, at, at the end of the day,
you, you just need, you need, you need, you need sort of
to know the project's value, the project value.
If you, if you work with Mike, you'll have four criteria
and you'll be done, done, done by lunchtime.
Um, I've had clients
that like a few more criteria in a bit more detail, um,
but for good, um, in terms of the, the, the kind
of modeling data, it's really about
how many bottlenecks you've got,
how many resource pots you, you want to work with.
Um, we don't work with kind of looking at
what Jeff from the data team is gonna be doing
in four weeks on Thursday.
This is about looking at high level bottlenecks,
potential kind of landmines in, in the plan.
So it might be three, it might be 4, 5, 6.
There's not a particular number.
Um, and the level of granularity in the business plan,
which I realize I've still got up on the screen,
again, fully configurable.
So it could be very, very simple, you know,
annual kind of numbers.
It could be kind of much more ma micro
monthly kind of scheduling.
Just depends on Yeah,
Yeah. In fact, I think,
I think one of the early versions, you,
you guys had shown me,
you basically can slot a number of person months.
Yep. Right? So three architects working for two months,
each is like six person months.
Yep. That's my capacity.
I don't really need, like, sure, some
of my architects work faster than others
and I might want on this type of project, but not that.
And it's, there's all the details that are of course, um,
real, but we, we don't concern ourselves with too much of
that, unless you want to spend that extra time
and energy trying to find, tune it.
But you'll never, it, you know,
the point is this solution is not trying
to replace your detailed planning tool.
Uh, exactly. And, and,
and, you know, any solution that tries to get all that level
of detail in place is gonna be so hard to implement,
particularly if you are trying to bring together
delivery groups that have different, uh, approaches to
how they schedule and work, different ways of prioritizing.
So if you're trying to drive alignment,
alignment is typically gonna come
through different siloed groups working together better.
So you've gotta have a solution that is relatable
to the marketing team, the data team, the IT team,
you know, the, the business facing folks in operations.
And therefore, you know, we are great believers in,
you know, you can plug this into different
types of planning tool.
You can do something in Excel and,
or you can do some stuff directly in here
if you really want to keep it simple.
Um, the, I the idea is, yeah, you've got that flexibility.
So when you wanna implement,
you're not gonna spending a year
and then realizing that half the people hate it
and adoption is poor.
So I, I'm gonna skip to the most recent question.
I will skip back to the other ones
because I think you just, you just, uh,
at least partially answered Todd's question, Dan,
that can this link to the resource planning tool
through some sort of API?
Yes. So we have, we have connectors.
So, uh, we've connected it to a few different things, uh,
power BI and as DevOps.
Um, but we've got little kind of, um, yeah.
Data layer that we can configure.
So like an ETL tool built in that you can sort
of point at at data source.
Oh, did you say you already have an
Azure DevOps connector?
Yes. So, uh, we, we did it
'cause our, um, our IT team used Azure to kind
of manage sort of bits and bobs.
Um, so we, we, we plugged it into Azure.
Well, so a shock asks, I'm assuming you need a robust,
long and short term strategy in place first.
Then from that a roadmap can be
provided from the system, the roadmap being what projects,
um, to do, to get the best ROI and benefits.
Yeah. When, when we, when we talk about kind
of getting started, um,
to some extent the first question is where are you starting from?
So do you have a mature strategy everyone's happy with?
And all you need to do is sort of, sort of shape it
so it fits into an a HP model.
That's great. But if you have, don't have that,
which is often the case, you need to get, you know,
someone like Mike who's good at kind of corralling a bit
of executive alignment in, on, in on and on the process.
And, and then it's a, it's a,
a good old fashioned consulting kind of exercise of talking
to executives, finding out what their motivations are and,
and putting that into a framework.
If you are spending money, uh, if you have pros
and cons, if you have some rationale
for doing stuff, you have a strategy.
It just may not be written down.
It may be more implicit rather than explicit.
And so the first step is making it explicit.
Yeah. And you know, given that, you know, it's clear
that Asock knows what he's talking about in general here.
Um, and he brings, brings some obvious experience
and knowledge to the conversation.
I would say Asock, of course, we all want a robust, long
and short-term strategy before we really do anything.
Um, in my experience though, people, organizations
that have half baked strategies
do better than those
that have really good strategies if they have an execution
model to actually get things done.
Right? Because that way, even, even if it's half baked,
well the half that is baked, um, can get done
and deliver value and then we can hopefully improve
and realize that the other half was
probably stuff we never should have bothered
with in the first place and doesn't really align
to our strategy very well,
or our strategy wasn't very clear, et cetera.
And we can refine that as we go.
Um, but I find a lot of organizations spend a lot
of time on strategy with the most beautiful, well thought
through strategic plans, and the execution just isn't there.
And so what's the point of having a robust strategy if we
can't execute it, right?
Yeah, completely. And I, I also find a lot, one
of the challenges strategies tend to be almost
by definition inclusive.
So they trying to be open enough that, that,
that everyone can relate to them
and feel positive about them as as, as being,
you know, a way forward.
That, that, that, that, that is gonna work.
But the problem is, strategists don't always pick
what they really care about versus what they're like me
sort of half care about.
And what prioritization does in terms of an HP model,
it forces you to really make preference, make a preference.
So, you know, was that that commitment to HR
really what you want to do?
Or is it what you sort of stuck in at the end?
'cause the HR director was there and you had to,
but when push comes to shove, you're not gonna spend
a million dollars on an HR system because,
So I'm mindful of the time, there's two, two questions.
Maybe a small third one we haven't gotten to the,
maybe we can, I wanna actually start with Connie's,
and I'm not skipping over your last one a shock,
but I think answering Connie's will help answer yours too.
Um, Ken, like what are some limitations
of a HP compared to other techniques?
Um, you know, in the interest of time,
I'll give you the short answer, Connie, that the,
the real solution isn't about, um,
all the detailed calculations
that give you the exact weighted criteria
or criteria weightings against which, uh,
project candidates should be judged.
Although that is a benefit of hp, it's, it's the,
does it trigger the right healthy conversations among people
that have genuinely divergent points of view?
And does it encourage the diversity of viewpoints as we try
to come up with a single harmonized approach, right?
Are all voices actually heard if they're in the room in the
first place and we want to hear them, right?
And, uh, too many other techniques fall down in this basic
human element, right?
So, um, again, with more time
or maybe some other webinars, Dan, we can answer, uh,
in a bit more detail.
But then there's also anything you wanna add.
Absolutely. So we can, we can send out, we've got a,
a blog on that we can send it out for, for,
for those who want some homework.
But, you know, at the, at its simplest level, the best,
the easiest way to make a decision is an old piece
of technology called the Magic eight Ball.
Right? You can shake that bad boy
and it'll tell you the answer straight away.
Now it's complete nonsense, but you'll make a decision.
It's easy, but it's rubbish.
And, and, and, and, you know, so, so what what we're trying
to do is, is move the world forward.
So it's not going for necessarily the simplest way
to make a decision, but it's actually the most effective.
And you're exactly right, Mike.
Effective decisions come from people.
They come from people working together.
They come from people working together in a structured,
staged way that respects decision science
and doesn't just make stuff up.
Um, because as people we are noisy creatures.
We come up with all sorts of nonsense.
Uh, and yeah, we need a little bit of structure
and a little bit of science in order
to get the most from us, um, as we, we try
and maximize human intelligence.
So a lot of talk about ai,
but you know, we're great believers in human intelligence
here as well, which is what, so
Real quick, let's squeeze a,
a shock's last question there.
What about the pet project that some top executive wants,
even if it's not necessarily the highest value?
Um, you know, there's no great solution to that.
A shock other than at least shine a light on it.
Yeah, right? If, if we can see
that it actually scored lower than eight other projects.
Well, the fact that the top executive thinks it's the best
is interesting perhaps,
but requires, um, an additional healthy conversation
or two that, um, I,
And it comes back to Scenarios.
Smoke out the false assumptions
And it's scenarios rather than context, right?
So it's not, it's not pep project, yes or no.
It's scenario one.
You know, do you want to do pet project scenario
with value this, or do you wanna do maximized value
scenario with value this?
So you're not picking your pro,
you're not just picking your pet project,
you're consciously picking a lower value project
or a low value portfolio.
And I'd be surprised if many execs still back their
project at the back of that.
So as we wrap, Dan, uh, Todd also asked if you could give,
give him a show and tell exactly. I,
I'll reach out to you, Todd. No
worries.
So I will, uh, thank you all for your, again,
the most valuable thing you
have to offer, which is your time.
I hope this was, um, useful, enlightening.
Um, I hope you see the same Goldilocks. I do.
I'm, I'm, I'm first in line to try
and bring this to my clients, um,
and I'm real excited about the potential where it can go.
Thanks so much, Dan.