Speaker 1: All right, welcome to your custom deep dive. It looks
Speaker 1: like someone's ready to tackle decision intelligence.
Speaker 2: Ooh DII.
Speaker 1: Based on all the stuff you sent our away, we
Speaker 1: we duck into the Decision Intelligence Handbook by well by
Speaker 1: DI experts, of course, and even pulled this Forbes article
Speaker 1: that really that really caught our eye.
Speaker 2: Interesting.
Speaker 1: No, tell me, have you ever felt like like you're
Speaker 1: just drowning in data? Right, but it's not really helping
Speaker 1: you make decisions?
Speaker 2: You definitely not along there. That Forbes article we pulled
Speaker 2: really nailed it highlighted a big problem. It even cited
Speaker 2: a study that found that decision makers get this, they
Speaker 2: only use like twenty two percent of all the data
Speaker 2: insights they.
Speaker 1: Get twenty two percent. What's even the point of all
Speaker 1: that data?
Speaker 2: Then? Right, it's not just wasted resources either. Think about
Speaker 2: the missed opportunities. Imagine if we could really use all
Speaker 2: that data to make smarter choices.
Speaker 3: Okay, so how do we fix that?
Speaker 2: Then?
Speaker 1: How do we bridge the gap between data overload and
Speaker 1: actually making good decisions?
Speaker 2: That's where comes in. It's not about getting more data,
Speaker 2: it's about the right data used in the right way.
Speaker 3: So it's a methodology it is.
Speaker 2: It's a whole way of thinking that really focuses on
Speaker 2: actions and outcomes.
Speaker 1: It's like that flight simulator idea from the handbook. Oh yeah,
Speaker 1: you're not actually flying, but you get to test out
Speaker 1: different scenarios and see what happens, right, and.
Speaker 2: A safe environment. That's a great way to put it.
Speaker 2: DII gives you that safe space for decisions less you
Speaker 2: explore the impact of your choices before you actually set
Speaker 2: them in motion. I like that, and the key part
Speaker 2: of that is understanding how our actions lead to outcomes,
Speaker 2: which brings us to causal decision diagrams cdds or cdds
Speaker 2: for short.
Speaker 1: The cdds were huge for me. It's like a flow
Speaker 1: chart but on steroids. Uh huh, visually mapping out cause
Speaker 1: and effect.
Speaker 2: Yeah. But from what I understand, there's more to these
Speaker 2: diagrams than meets the eye. Different types of nodes and
Speaker 2: connections and all that interesting. So let's say you're decided
Speaker 2: on a new marketing campaign AD for that would include
Speaker 2: nodes for things like the cost of the campaign, the
Speaker 2: potential reach, customer conversion rates, and then of course the
Speaker 2: impact on revenue.
Speaker 1: So you'd have nodes for each of those and then
Speaker 1: connections between them, showing how they all affect each other.
Speaker 2: And those connections they're not just simple arrows. They show
Speaker 2: different types of causal relationships. Yeah, Like, there might be
Speaker 2: a strong positive connection between the reach of the campaign
Speaker 2: and the number of leads you get, makes sense, But
Speaker 2: the connection between those leads and actual sales might be
Speaker 2: more uncertain, influenced by your sales team or the overall
Speaker 2: market demand.
Speaker 1: This visual element is so crucial it is. It helps
Speaker 1: everyone understand, from marketing to the CFO, even if they
Speaker 1: usually hate spreadsheets.
Speaker 2: Absolutely, a CDD creates a shared understanding so everyone can
Speaker 2: see the big picture and how all the pieces fit together.
Speaker 1: But it's not always straightforward cause and effect, right, you
Speaker 1: got it. Sometimes things have that we don't expect at all.
Speaker 1: Oh yeah, like that sweet potato farmer example.
Speaker 2: From the book Aha the nematode saga. Yeah, it really
Speaker 2: shows how even good intentions.
Speaker 1: Can backfire, So tell me about it.
Speaker 2: This farmer was fighting these tiny pests that were messing
Speaker 2: up his crops, making them unsellable and hurting his profits. Ouch,
Speaker 2: So he decided to invest in a new irrigation system,
Speaker 2: hoping to get bigger yields.
Speaker 3: Sounded like a solid plan, right, but it didn't quite.
Speaker 2: Go as planned. The news system, while good in theory,
Speaker 2: accidentally created the perfect breeding ground for the pests. Oh no,
Speaker 2: he ended up with even more damaged crops and even
Speaker 2: lower profits.
Speaker 1: So even with the best data and the best intentions,
Speaker 1: things can still go wrong.
Speaker 2: Exactly.
Speaker 1: This is where di I helps us see those hidden factors.
Speaker 2: Those unknown unknowns that we might not even be aware of.
Speaker 3: Right.
Speaker 1: Instead of just focusing on what we think will happen,
Speaker 1: di I helps us explore all the possible outcomes, all
Speaker 1: of them, including the ones we might not have thought of.
Speaker 2: It's like a pre mortem for decisions. I like that
Speaker 2: it captures what DII is all about, anticipating what could
Speaker 2: go wrong before it does and making smarter choices. Yeah,
Speaker 2: based on a deep understanding of the situation.
Speaker 1: Okay, so we've got this powerful tool helps us see
Speaker 1: the whole picture, anticipate the unexpected, make more informed decisions.
Speaker 1: But how do we actually use it?
Speaker 2: Right? How do we apply it in real life and
Speaker 2: the real world. The handbook had some interesting case studies,
Speaker 2: like that telecom company they were trying to figure out
Speaker 2: the best price for their unlimited data plans.
Speaker 1: Oh yeah, they were facing tough competition, fierce, and.
Speaker 2: They knew they had to make a data driven.
Speaker 3: Decision, not just go with their gut.
Speaker 2: Or copy what their competitors were doing.
Speaker 1: This is where that sensitivity analysis comes in, right, Exactly.
Speaker 1: They could use di to simulate different pricing scenarios and
Speaker 1: see how those changes would impact their bottom line.
Speaker 2: They could model all sorts of factors like customer churn,
Speaker 2: competitive responses, even work capacity.
Speaker 1: So they could run virtual experiments.
Speaker 2: Essentially, yes, to see which pricing strategies would.
Speaker 1: Work best maximize profitability.
Speaker 2: Right, it's not just picking a price and hoping for
Speaker 2: the best. Yeah, they could test different levers, see how
Speaker 2: they interact in a complex system.
Speaker 1: That telecom example is great. But I'm wondering, does di
Speaker 1: I completely ignore human intuition.
Speaker 2: That's a great question, because experience and gut feelings still
Speaker 2: play a role. Right, You're absolutely right. Di I isn't
Speaker 2: about replacing human judgment with algorithms. It's about empowering decision makers,
Speaker 2: giving them the insights.
Speaker 3: They need to make better choices.
Speaker 2: Because even the best models have limitations and there are
Speaker 2: always things we can't predict.
Speaker 1: So it's not data versus intuition. No, it's finding the
Speaker 1: right balance exactly. The handbook mentioned a company trying to
Speaker 1: upgrade their phone systems in like fifty countries.
Speaker 2: Oh yeah, it was a huge project, a.
Speaker 1: Logistical nightmare, absolutely, even without the technical stuff.
Speaker 2: They had all these old systems, hundreds of content, different
Speaker 2: needs in each location.
Speaker 1: It was overwhelming, it was and.
Speaker 2: Their first attempts failed because they just focused on the easiest.
Speaker 1: Upgrades without seeing the big picture.
Speaker 2: They missed those connections, the interdependencies.
Speaker 1: That could make or break the project exactly.
Speaker 2: That's where DII came in. They use it to create
Speaker 2: a CDD that mapped out everything, the complexities, the interdependencies,
Speaker 2: contract expirations, you name it.
Speaker 1: So they could simulate different upgrade sequences.
Speaker 2: And find the most efficient path.
Speaker 1: They could see how actions in one country would impact
Speaker 1: other countries later on, anticipate bottlenecks, avoid those cascading failures.
Speaker 2: The results were amazing, saved millions of euros, finished at
Speaker 2: as schedule.
Speaker 3: Wow.
Speaker 2: More importantly, DI changed their mindset. They started taking a
Speaker 2: more strategic approach.
Speaker 3: Holistic the decision making.
Speaker 1: It's not just finding the right answer, it's understanding the
Speaker 1: whole system, making choices aligned with the bigger goals.
Speaker 2: Speaking of goals, one thing that stood out to me
Speaker 2: about DII was the focus on def objectives before diving
Speaker 2: into data analysis.
Speaker 3: You have to know where you're going exactly.
Speaker 2: Even with the best data, you'll get lost.
Speaker 1: Like setting off on a journey with no destination.
Speaker 2: You might end up somewhere interesting, but probably not where
Speaker 2: you want it to be.
Speaker 1: So do I helps us define that destination and gives
Speaker 1: us the tools to map out the route.
Speaker 2: But it also makes us confront those unknown unknowns.
Speaker 1: Those factors we might not even be aware of.
Speaker 2: That's why the decision artifacts are so important. The cdds, models, simulations.
Speaker 1: All the stuff we create during the DI process.
Speaker 2: It becomes a record of our thinking. Yeah, our assumptions
Speaker 2: are understanding.
Speaker 3: At that moment in time, and they're not.
Speaker 2: Just valuable for that specific decision, but for future decisions too.
Speaker 1: Like a library of wisdom exactly. We can revisit them,
Speaker 1: see what worked, what didn't.
Speaker 2: Maybe even spot patterns we missed before.
Speaker 1: And continuously improve our decision, making.
Speaker 2: A continuous improvement loop.
Speaker 1: We're not just making one good decision, We're building a
Speaker 1: system for making better decisions overall.
Speaker 2: That's a great way to put it is an ongoing process,
Speaker 2: the journey of discovery and.
Speaker 3: Refinement, and a key part of that.
Speaker 2: Is the decision retrospective.
Speaker 1: We take the time to review what happened after a decision,
Speaker 1: extract valuable lessons regardless of the outcome, because sometimes a
Speaker 1: good decision can lead to.
Speaker 3: A bad outcome, and vice versa.
Speaker 1: It's about learning from our experiences exactly.
Speaker 2: The retrospective is all about honesty. Did our process align
Speaker 2: with our objectives? Did we consider everything? Challenge our assumptions.
Speaker 1: Because even when there's no right answer, we can still
Speaker 1: learn from the process.
Speaker 2: Did we think about all the angles, identify potential risks,
Speaker 2: challenge our own thinking, the accountability even when things are
Speaker 2: out of our control.
Speaker 1: Bringing us back to the human element of DII, balancing
Speaker 1: data with expertise and judgment, di I is really pushing
Speaker 1: us to be more deliberate, more thoughtful about our decisions.
Speaker 2: It's a shift in how we think for sure, and
Speaker 2: not just for individuals. D I could change how entire
Speaker 2: organizations work.
Speaker 1: Imagine every department using di to guide their choices.
Speaker 2: From marketing to finance to operations.
Speaker 1: Instead of all these separate decisions that often cause conflicts
Speaker 1: and inefficiencies.
Speaker 2: Right, everyone would be on the same page, working.
Speaker 1: From the same playbook, with the shared understanding of the
Speaker 1: big picture.
Speaker 2: Shared understanding and alignment are key to really using di
Speaker 2: I effectively.
Speaker 1: It's not just theory either.
Speaker 2: The hambook mentioned companies already using di across the.
Speaker 1: Board seeing real improvements.
Speaker 2: In efficiency, profitability, even employee morale makes sense.
Speaker 1: If people feel like they're part of the process, they'll
Speaker 1: be more engaged, more invested in the outcomes.
Speaker 2: It creates ownership, accountability.
Speaker 1: It sounds amazing, but DII isn't a magic solution, is it.
Speaker 2: Of course not. There are going to be.
Speaker 1: Challenges, especially in big organizations.
Speaker 2: Change is always tough, especially when it comes to something
Speaker 2: like this.
Speaker 1: People get comfortable with the old ways.
Speaker 2: Some might see it as a threat to their power
Speaker 2: or expertise.
Speaker 1: And there's a technical side.
Speaker 2: Building the cdds, getting the data, creating the simulations.
Speaker 1: It takes a lot of resources and expertise, it.
Speaker 2: Does, but the potential payoff can be huge, like.
Speaker 1: Any good investment, and you don't have to jump all
Speaker 1: in at once. Start small, maybe a pilot project in
Speaker 1: one department, prove the concept, show the results win over
Speaker 1: the skeptics exactly. Those case studies from the book are
Speaker 1: really helpful.
Speaker 2: They are. They provide real examples of how DII is
Speaker 2: solving problems achieving.
Speaker 1: Results in all sorts of industries.
Speaker 2: A roadmap for the DI journey.
Speaker 1: We can learn from others adapt their approaches to our
Speaker 1: own situations.
Speaker 2: Which brings us back to you, the listener.
Speaker 1: How can you use these ideas for a decision you're
Speaker 1: facing right now?
Speaker 2: Could d I help you see hidden factors, test out
Speaker 2: different scenarios, approach decision making with more confidence. That's the
Speaker 2: question we want to think about.
Speaker 1: That's it for this deep dive. It wasn't just about
Speaker 1: shit information. We wanted to give you a new way
Speaker 1: to think about decisions.
Speaker 2: To make more informed choices in all parts of your life.
Speaker 2: We hope this deep dive sparked your curiosity and gave
Speaker 2: you some valuable tools and insights. Remember, better decision making is.
Speaker 1: A journey, and DI can be a powerful ally.
Speaker 2: Thanks for joining us.