Category Archives: Dependencies

Artificial intelligence and human limits

Are we getting dumber?  Or is stuff just harder?

Both are true.  Between-silo problems are the new bottleneck.  We’re inundated with information, so we take cognitive short cuts.   And “wicked” problems keep getting wickeder.

Take this “invisible art” artist.  She sold a few.*

Real decisions are made in the heart, the gut, based on a good story.  So we’re vulnerable to master wizards: good story tellers.  And, often, we’ll do what they say.

It’s impossible to assemble hundreds of graphs and data visualizations in our heads to make good decisions. It’s a fiction that we can.  So we’re overwhelmed, take short-cuts, but it’s hard to admit.

The good news: we have new superpowers.

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Necessary, but not sufficient

When asked “who created Apple?”, it’s tempting to say Steve Jobs did it.  The truth is that, although he may have been necessarily, he was not sufficient.

Similarly Bill Gates, who (as Malcolm Gladwell tells us in Outliers) experienced a unique confluence of circumstances that led to the founding of Microsoft.  Gates deserves tremendous credit, but alone he was not sufficient.

The brain likes to simplify, and history sometimes prefers to leave out the details for the benefit of a better story. Continue reading

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Decision Intelligence solutions

Decision engineering Decision intelligence Decison model elements Dependencies Externals For Decision Professionals Introduction Levers Outcomes

My team and I offer decision intelligence and decision engineering to solve your complex problems. Simply put, data is backwards-facing. It’s like watching an elephant’s footprints, rather than understanding the elephant itself. Systems are forward-looking.  There’s no coincidence in the fact that your rear-view mirror is smaller than your windshield. Yet…

Most organizations look backwards, assuming future equals past. This is no longer true. Click To Tweet

So let’s roll up our sleeves together, and take your organization to the next level.

It doesn’t have to be hard.

You still need your data.  It’s always going to be an important tool in validating where you’ve been, and of course, operational data (like a customer’s address) is critical.

But when it comes to making decisions, data is only part of the picture.  Once you make a decision and execute on it, this creates a cascade of events within your organization.  Understanding how the decision leads to an impact…and another…and another…until you’ve reached your objective (or not) may sound like a daunting proposition.  But here’s the rub: you’re doing it already, in your head, every time you think through the consequences of a decision.  Why not get some computer help with that?  Even a little can go a long way.  Because otherwise, you’re facing the fog shown below:outcomes

Here’s what you can expect when working with me to improve your organizational decision making.  Think of this as an “a la carte” menu; some organizations choose the whole bundle, some do one part at a time.  Each has considerable value on its own.

  1. Decision intelligence training. I run half-day to full-week workshops on the core concepts behind decision intelligence.  Here’s a typical course outline.
  2. Company-wide presentation, so everyone knows what we’re up to.  Here are some videos of my public appearances, to give you a flavor of this.
  3. Decision-specific workshop.  I typically work with a multi-functional team.  We begin by aligning around desired business objectives, then proceed through decision specification, design (levers, links, external data, and more), and iterate. We work visually and collaboratively, and often the focus is understanding the links between previously silo’d groups, and modeling the “whack-a-mole” of unintended consequences.
  4. Data assessment.  Usually, only 20% of the data contains 80% of the business value. The challenge is to determine which data contains the value.  Decision intelligence provides a structured and rigorous approach to figuring this out.  If you don’t take this approach, you can waste a lot of time managing data using “operational” methods, where less expensive “analytical” approaches are a tremendously better fit.
  5. Decision model implementation in World Modeler.  You can get a lot out of steps 1-3, but implementing these concepts in an enterprise-class tool is where the big benefits start to kick in.  Sometimes we begin by modeling in Microsoft Excel as well, and often we generate data that can be read by Excel as the model runs.
  6. Decision visualization.  We usually build custom visualizations for our clients.  You can see a few demos, here (for program management) , here (for data center risk assessment), and here (a full-CG decision model visualization).  We build these to your specifications, to meet the needs of your team.
  7. Data and systems integration.  Here, we work with your organization to integrate a real-time decision navigation infrastructure into your business.  Our value proposition: “the best of both worlds”: using our World Modeler platform means that we can built solutions at low risk and lower cost and much more quickly than other companies (indeed, we once built a full bank risk analysis system in under six weeks).  At the same time, it’s fully customized to your needs, as if we’d built it from scratch. Why this is possible?  We’ve discovered what’s required in a general-purpose data and decision management framework, including optimization, data binding, visualization, simulation, and more (read our API documentation here).

Add-ons to the above  include:

  • Additional training:
    • Introduction to R
    • Introduction to neural networks in R
    • Introduction to machine learning in R
    • Building World Modeler custom visualizations
    • Deep-dive decision dependency design
  • Data services
    • Data modeling
    • Enterprise architecture integration
    • Data cleansing
    • Web-based interactive data survey / gathering creation
  • Custom model visualization development
  • ..and much more

So please drop me a line, and let’s explore together whether supercharging your organization’s decision intelligence makes sense for you.

Drop me a line and let's talk!

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Guest Post: A knowledge management system capable of blinking red

Inattention to critical knowledge is an old problem. Lessons are forgotten, near misses are ignored, caution is dismissed, disasters result. Titanic. Bhopal. AIG. Katrina. Fukushima. And on and on.

Knowledge Management (KM) is supposed to make the right information available to the right people at the right time in the right form—and to the best level of certainty possible—for making the most appropriate decisions when and where they are needed. KM should also direct the attention of decision makers to critical information and help them make sense of it. The bigger the stakes, the more situational awareness and mindfulness are needed. Continue reading

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The magical diminishing returns link, and why it can fix government budgeting (and yours, too)

A couple of years ago, I was honored to be invited to help with a US government budget. My team and I would fly to Washington, take the metro into Union Station, and meet with our clients, who were struggling with an important question: “how to do more with less?” as they distributed funds to hundreds of departments.

In the midst of the project, sequestration loomed, and then materialized, so this question became critical. Continue reading

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Decision Intelligence solutions

Decision engineering Decision intelligence Decison model elements Dependencies Externals For Decision Professionals Introduction Levers Outcomes

My team and I offer decision intelligence and decision engineering to solve your complex problems. Simply put, data is backwards-facing. It’s like watching an elephant’s footprints, rather than understanding the elephant itself. Systems are forward-looking.  There’s no coincidence in the fact that your rear-view mirror is smaller than your windshield. Yet…

Most organizations look backwards, assuming future equals past. This is no longer true. Click To Tweet

So let’s roll up our sleeves together, and take your organization to the next level.

It doesn’t have to be hard.

You still need your data.  It’s always going to be an important tool in validating where you’ve been, and of course, operational data (like a customer’s address) is critical.

But when it comes to making decisions, data is only part of the picture.  Once you make a decision and execute on it, this creates a cascade of events within your organization.  Understanding how the decision leads to an impact…and another…and another…until you’ve reached your objective (or not) may sound like a daunting proposition.  But here’s the rub: you’re doing it already, in your head, every time you think through the consequences of a decision.  Why not get some computer help with that?  Even a little can go a long way.  Because otherwise, you’re facing the fog shown below:outcomes

Here’s what you can expect when working with me to improve your organizational decision making.  Think of this as an “a la carte” menu; some organizations choose the whole bundle, some do one part at a time.  Each has considerable value on its own.

  1. Decision intelligence training. I run half-day to full-week workshops on the core concepts behind decision intelligence.  Here’s a typical course outline.
  2. Company-wide presentation, so everyone knows what we’re up to.  Here are some videos of my public appearances, to give you a flavor of this.
  3. Decision-specific workshop.  I typically work with a multi-functional team.  We begin by aligning around desired business objectives, then proceed through decision specification, design (levers, links, external data, and more), and iterate. We work visually and collaboratively, and often the focus is understanding the links between previously silo’d groups, and modeling the “whack-a-mole” of unintended consequences.
  4. Data assessment.  Usually, only 20% of the data contains 80% of the business value. The challenge is to determine which data contains the value.  Decision intelligence provides a structured and rigorous approach to figuring this out.  If you don’t take this approach, you can waste a lot of time managing data using “operational” methods, where less expensive “analytical” approaches are a tremendously better fit.
  5. Decision model implementation in World Modeler.  You can get a lot out of steps 1-3, but implementing these concepts in an enterprise-class tool is where the big benefits start to kick in.  Sometimes we begin by modeling in Microsoft Excel as well, and often we generate data that can be read by Excel as the model runs.
  6. Decision visualization.  We usually build custom visualizations for our clients.  You can see a few demos, here (for program management) , here (for data center risk assessment), and here (a full-CG decision model visualization).  We build these to your specifications, to meet the needs of your team.
  7. Data and systems integration.  Here, we work with your organization to integrate a real-time decision navigation infrastructure into your business.  Our value proposition: “the best of both worlds”: using our World Modeler platform means that we can built solutions at low risk and lower cost and much more quickly than other companies (indeed, we once built a full bank risk analysis system in under six weeks).  At the same time, it’s fully customized to your needs, as if we’d built it from scratch. Why this is possible?  We’ve discovered what’s required in a general-purpose data and decision management framework, including optimization, data binding, visualization, simulation, and more (read our API documentation here).

Add-ons to the above  include:

  • Additional training:
    • Introduction to R
    • Introduction to neural networks in R
    • Introduction to machine learning in R
    • Building World Modeler custom visualizations
    • Deep-dive decision dependency design
  • Data services
    • Data modeling
    • Enterprise architecture integration
    • Data cleansing
    • Web-based interactive data survey / gathering creation
  • Custom model visualization development
  • ..and much more

So please drop me a line, and let’s explore together whether supercharging your organization’s decision intelligence makes sense for you.

Drop me a line and let's talk!

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Getting the links right: Sketch graphs, AHP, ML, and more.

Cause-and-effect links live at the heart of complex systems.  And understanding them means we can go beyond historical data to understand situations we haven’t faced before, using piecewise causal links from the past to inform new situations.  This is incredible, because it breaks us from the tyranny of using only historical data in data science, machine learning, AI, and more.    Here’s how three previously separate approaches can be used to help us get the links right.

Continue reading

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