Author: Christopher Berry

The book, The Origin of Wealth, Evolution, Complexity and the Radical Remaking of Economics, is probably the most enjoyable read of the three that frame my thoughts on Analytics Strategy. It’s my second favorite book, right after Nineteen Eighty-Four. Complexity Economics is about: “Dynamics: Open, dynamic, nonlinear systems far from equilibrium.” “Agents: Modeled individually; use inductive rules of thumb to make decisions; have incomplete information, are subject to errors and biases; learn and adapt over time.” “Networks: Explicitly model interactions between individual agents; networks of relationships change over time. “Emergence: No distinction between micro- and macroeconomics; macro patterns are emergent result of micro-level behaviors and interactions.” “Evolution: The evolutionary process of differentiation, selection and amplification provides the system with novelty[…]

The book, On Competition, is a useful read on its own. In it, Michael E. Porter defines what competitive strategy is, and eloquently uses a concept that we’re going find useful. “Competitive strategy is about being different. It means deliberately choosing a different set of activities to deliver a unique mix of value.” (pp. 43) Here’s the best way to visualize what he means: This Southwest Airlines example is to competitive strategy as Harrah’s loyalty system is to analytics. It’s the main case study. The nodes represent activities and the vertices (lines) represent logical reinforcement. No meals and no seat assignments mean limited passenger service, however, they also mean 15 minute turnaround time. That advantage yields very low ticket prices[…]

The book, Business Model Generation, is well referenced within the Toronto innovation community. (I don’t know if it’s nearly as cited in other cities or other communities). Business Model Generation is notable for having a standardized canvas. This canvas forms a common language for disparate groups of people – designers, developers, financiers and others. As you can see, it has nine boxes, roughly corresponding to all the sections of a normal business plan: What is your key value proposition? Who are your customer segments? What sort of relationships do you have with your customer segments? What channels do you use to serve them? What are your revenue streams? What are your key activities? What are your key resources Who are[…]

There are three sections of three books that provide the guideposts for how I think about strategy. They are: The Origin of Wealth, Evolution, Complexity and the Radical Remaking of Economics. On Competition. Business Model Generation. The three books are readable and enjoyable. This week I will extract bullet points from each, and use them to construct a framework that is amiable for analytics practitioners to formulate their own business strategies. By the end of the week, you ought to be able to write a fairly advanced strategy. The communication objective is to link the business model canvas with a key strategic activity system as a framework for communicating choice and degrees of freedom. The secondary objective is to point[…]

This is part five in a five part series on Analytics and GIS. Part one looked at a job posting in Edmonton, part two on scoring, part three on model builder, and part four on discrimination. I’m excited for Edmonton and Edmontonians. The decision to hire a predictive analyst for road safety is an awesome one, and one that ought to generate real results well into the future. There will be no real way for any individual Edmontonian to know if their life was saved as a result of the recommendations realized and applied as a result of this program. On the aggregate, over time however, fewer fatalities and serious injuries should accrue. I’d like to see a long term[…]

This is part four in a five part series on Analytics and GIS. We’ve previous seen a position for Road Safety Predictive Analyst, that roads can be scored, that hazard can be modeled with existing tools. Today, we hit ethics. DiscriminationYou may have heard about Microsoft’s GPS Patent, the ghetto avoidance algorithm. It caused a bit of furor. Concretely: Microsoft filed a patent for a GPS guided walking app. It has an algorithm allowing the user to avoid a certain neighborhood if the crime threshold is too high. Some people say that it’s racist and prejudicial. Other people say that it has nothing to do with race or prejudice. Like People Clump Alike People who are alike tend to live[…]

This is part three in a five part series on Analytics and GIS. Part one focused on a road safety predictive analyst position, and part two focused on scoring algorithms. Tool Time ESRI produces a tool called ArcGIS. It uses open source mapping data, and has a fairly sophisticated set of functions. ArcGIS has an optional tool called Model Builder. GIS analysts use it to score environments. Or, in this specific case, road segments. Modelling Yesterday, I enumerated a sequence of attributes that a road has, ranging from speed limit, neighborhood, size, intersection and crossings. There are also attributes like weather and time of day, which are hiding yet more spurious variables like number of suspended drivers on the road[…]

This is part two in a five part series on Analytics and GIS. Yesterday, we looked at a job posting for a road safety predictive analyst. Scoring Algorithms Collisions, injury, serious injuries, and fatalities happen in a time and in a space. Both the attributes of the space, and the attributes of the space at the time can be recorded and understood. It is always preferable, when executing any optimization program, to optimize for a single variable. Scoring is one way that we take a whole bunch of factors and derive a single figure. Road segments have attributes. Is it an intersection? Is it two lanes? Is there parking? Is there a bike lane? Does it twist? Does it have[…]

The City of Edmonton posted a pretty interesting position last month. The description is so good that it bears repeating in this space. Bolding is my emphasis. Traffic Safety Predictive Analyst Put your superior analytical skills to work in North America’s first and only municipal Office of Traffic Safety. You will be joining the rapidly growing field of urban traffic safety where the application of statistics and predictive analysis is becoming a vital decision support tool in reducing motor vehicle collisions.    Your responsibilities will be: Provide short, medium, and long-term predictions of collisions and/or speeding by considering current and historical traffic safety related data as well as other influential factors, including weather and demographic data Identify, generate and monitor[…]