Suppose the following scenario: Series A or B; A data science firm (narrow machine intelligence, applied machine intelligence, general machine intelligence, predictive or prescriptive analytics, software or hardware); Technical CEO / Co-Founder; Chief Marketing Officer (CMO) just hired; What might the CEO-CMO relationship look like? The relationship could be great. If there’s one stereotype about data science CEO’s, it’s that they like incentives to be aligned. The CMO would likely be brought on to focus on growth. If revenue grows, valuation grows, and collective comp would grow. There might be points of friction. From the CMO’s Perspective: Why is the CEO constantly at me about metrics all the time? Why is the CEO always on about non-working dollars? (Why don’t[…]
Category: Strategic Analytics
Who do you trust to manage your attention? Because now that the news cycle has surfaced Cambridge Analytica issue – that’s the real thesis question. Let me explain. How the Newsfeed manages your attention I really can’t understate just how powerful amplified engagement really is. When you overlay the like/share verbs on top of a network of individuals who all have something in common, or who procure people who have something in common, you get some pretty strong effects. Don’t believe me? Just check out the clothing in your drawers and the items in your fridge. You, my friend, are an outcome of considerable social contagion effects. Facebook’s newsfeed algorithm shelters you from a power law distribution of content that the[…]
Backcasting is a fantastic technique. It was invented in Canada. You’re welcome to use it. If it sounds like forecasting – well – that’s because it’s kind of like forecasting. With an important difference. That wikipedia page says: Whereas forecasting is predicting the future (unknown) values of the dependent variables based on known values of the independent variable, backcasting can be considered the prediction of the unknown values of the independent variables that might have existed to explain the known values of the dependent variable. I had to re-read it a few times to really get it. Once you get it, it’s just elegant. What’s beautiful is that it can silence the reactive-pure-statistician brain long enough for the prospective centre of the creative brain to imagine several futures. What I like about backcasting[…]
Some people want just one number. Some people want all the numbers. For best results, seek balance. One Number It is very possible to summarize the performance of a business or an organization in a single number. There are two main ways to do so. One is selection. One is indexing. In selection, you pick the most important metric, and you focus on it. It requires discipline and comes at the cost of myopia. In indexing, you pick the most salient metrics and you combine them into a single number. It requires no discipline and comes at the cost of boiling the ocean to the point that all the rocks bleed their salts into the atmosphere. When it comes to[…]
An orthodox Software as a Service (SaaS) business is, in part, math that an organization tries its best to manage. Think about all the math that goes into the construction of a typical SaaS firm. At the core there’s some customer with a job: a goal against which the customer wants to make progress. They can have a mathematical representation in a database somewhere. A bunch of technologists write some code, which is all math, and a bunch of creatives take a few photographs, which expresses itself a mathematical representation, and some data is Created Read Updated and Destroyed in a database somewhere, which is all just more math. And it’s all abstracted by yet more math at the processor[…]
A tier one MSI topic focuses on how should quantitative methods and qualitative methods be combined to understand the total consumer experience. It’s an excellent topic. The two worlds aren’t natural complements. They have radically different systems of activities, tools, and methods, which in turn affects their own experiences, and how they see the world. However, if the stance is unified, in the form of understanding the total consumer experience, the sum of the two approaches produces such more. That focus creates the cohesion. Facts, Experience, and Anecdata Have you ever been asked how many people need to be in a focus group before their statements become statistically significant? It’s a pretty neat question. What are they really asking when they ask[…]
This is a lot of inside baseball. The motivation is to share information while acknowledging that it’s wildly anecdotal. It’s directed at data scientists thinking about business. The Facts Andrew and I founded Authintic in late 2012. We landed three great customers. We met between 1,600 and 1,900 well wishers, competitors and prospective customers. Five major market hypotheses were tested. Revenue was earned and value was generated. Authintic was acquired by 500px in early 2014. The Feels Thrilled. Very excited. And a tad skeptical about the lessons learned. People are terrible about extracting causal factors from an experience. I’m people. So I reckon that applies to me too. A sample size of 1 isn’t authoritative. It doesn’t constitute proof, or evidence[…]
It’s the results, genius! It’s the results. The purpose of any sort of data analytics or data science is to get results. It isn’t about the spreadsheet that comes three weeks after the campaign. It isn’t about sandbagging numbers. It isn’t the few slides in the Quarterly Business Review. It isn’t even data entertainment. It’s the results. Great! So what’s the deal? Why is so much time expended on activities that don’t directly tie to getting results? Analytics Maturity It’s because of maturity, or the sum of experiences that an organization/culture chooses to remember. Very good models of analytics maturity exist. Stephane Hamel has a great one. Stances inform tools and tools cause experiences. Where you stand affects which, if[…]
You may have read something about the Samsung 7500 and 8000 series televisions, the ones with a camera installed in them, over the past few days. The tl;dr summary: “For Samsung’s 7500 and 8000 series TVs, all you have to do is say “Hi, TV,” when you walk into a room for the TV to turn on and know who’s there.” “Think of it: The tech means an advertiser or TV programmer could, for the first time, know which members of a Nielsen household are watching a show or an ad. Cisco has even developed a system meant to read facial expressions and determine whether you’re entertained or bored.” “Many people in the living room are multitasking with other devices.[…]
I tend to leave a trail of giant whiteboards wherever I go. The giant whiteboard is one of the most important instruments in an information firm. Whiteboards are colorful and communicative. They’re democratic. Anybody can really get up, grab a marker, and really go at it. They’re raw. They’re just awesome. I use them to collaborate. I use them to present problems, solutions, and opportunities. The eraser is a memory hole. Any mistake, any exploration, any avenue is open and correctable. It’s outstanding. Powerpoint. Ah yes, powerpoint. Powerpoint is an awesome visual medium. It’s great in that it really doesn’t command anybody being presented at to do anything. People sit there and you point at them. Powerfully. Powerpoint has uses.[…]