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[…]

In this post, I will unpack the concept of Convenient Reasoning and link it to managerial judgement and the spirited defense of Gut. I really haven’t challenged these assumptions in a few months, so, if you dislike what you read, give me a shout. I’ll spend too much time over the next 45 days repeating the orthodox line of scientific management and continuous learning in digital. It’ll be a great opportunity to unpack some language and really tone down the information density. Gut Just as I translate the word ‘leverage’ into ‘use’, I translate the word ‘gut’ into ‘my feelings about expectations’. Or, put more derisively, ‘muh feelz’. I’m indebted to James G. March for highlighting the difference between expectations,[…]

Analytics in 2014. What a year. We hit peak Data Science hype in October. We hit peak Data Science sometime over the summer. This has a few important impacts for 2015. The end of that hype will make it harder for the majors to sell binders of plans. It’ll be tougher to find optimistic customers. It’ll be rough going for some of the weaker offers on the market to fake it long enough to make it. It’ll sort out the ‘transformational change’ shops from the technical shops far more slowly. Markets aren’t nearly as efficient as they should be. It usually takes 180 days for the peak to bite and 270 days for the money to run out. It’s really[…]

There are three important, reinforcing concepts in analytics product development. These are usability, numeracy, and empowerment. Usability is an important goal to pursue in analytics product development, but is no antidote for poor numeracy and empowerment. Usability is particularly important for analytics product development. Good usability enables the non-specialist, the data civilian, or the casual business user to engage the product and extract the information they need to know. Some interfaces require specialized training to use (SAS, R, SPSS) while others used to require little experience (Google Analytics pre-2008, OWA today). Several companies have gone to IPO with only marginal improvements to baseline analytics usability. Some companies started out with usability as a key differentiator, only to fail to manage simplicity with[…]

Here’s what you need to know about automated statistical analysis: 1. Automated statistical analysis is not a substitute for good judgement Statistical tests are tools. They help us understand why nature is the way that it is. Nature resists being known about. But, she is knowable. Statistical tests themselves are part of nature. The tests themselves were never meant to be substitutes for good judgement. That belief, that tests could replace people, has only ended up causing the accumulation of some pretty outrageous assumptions over the years. Just because there is a significant correlation between Magnum Ice Cream sales and Piracy in the Indian Ocean doesn’t mean that it’s causal. Statements of causality require judgement. Automated statistical analysis is not[…]

It’s a big week for analytics in Toronto. There’s a growing industry of digital intelligence / analytics, professionals in southern Ontario. It’s a brilliant and welcoming industry. This is the week when we get together, share knowledge, and welcome newcomers. The eMetrics Summit, the conference of the Digital Analytics Association (use the promo code BERSPK for a discount to the summit), will also mark second major Southern Ontario Chapter meeting. There will be case studies from TD, CBC, Bombardier, Intuit, The New York Times, TVO, Hyatt, and Maple Leaf Entertainment. Zoe Morawetz (TD) is showing us how they execute digital segmentation. Gareth Cull (Mozilla), Mark Dykeman (BMO) and Tim Ashby (CM) will be sharing which technical traps to avoid, Greg[…]

This piece from McKinsey highlighted the inflated expectations of big data analytics – “…expectations of senior management are a real issue…but too often senior leaders’ hopes for benefits are divorced from the realities of frontline application. That leaves them ill prepared for the challenges that inevitably arise and quickly breed skepticism.” The listicle (et tu, McKinsey?) summarized below, is somewhat related to that concern: 1. Data and analytics aren’t overhyped—but they’re oversimplified 2. Privacy concerns must be addressed—and giving consumers control can help 3. Talent challenges are stimulating innovative approaches—but more is needed 4. You need a center of excellence—and it needs to evolve 5. Two paths to spur adoption—and both require investment (automation and training) In a fit of[…]

There are varying concerns about what constitutes a causal model, the degree to which data is biased, certainty that the model is predictive about the future, and, that the model itself is a truthful depiction of nature. Over the course of the past two weeks I’ve talked with many people about their perspectives – data scientist, developers, technologies, product managers, brand managers, statisticians, consultants, professors, executive producers, and founders. We’ve talked about everything from why analysts and their customers won’t accept narrow models, why it’s far easier to summarize data than it is to describe the relationships in it, and the intractable differences between what is performance reporting and what constitutes an insight. The verdict is not in. There are varying beliefs[…]

The Circa app (As of January 2014) is notable for the choices the designers made. And the choices they made. The color palette is consistent. The leading is consistent and generous. Upcoming information is faded and effectively previews content. The  app can be used with gestures from one thumb, making it great for one thumb use. Just the right number of stories are presented on each day. They made quite a few good choices. They chose to hide most social sharing under a button, instead of surfacing all the options directly within the app. They chose to invest in making good recommendations about related content. They chose to invest in designing an elegant right rail breadcrumb that both respects the[…]

“The End of Facebook” trumpeted the headline. 46 points in 46 minutes on Hacker News. “Facebook Screws Social Media Marketers!” trumpets Business Insider. “Facebook is losing teens” states Global Web Index. Here we go with the bandwagon. Hop on! Only that this time isn’t going to be quite like the last time(s). Teens have fled to their smartphones They’re computers they can control. They’re computers that aren’t tied to the family room, where parents can seen them. Small screens offer a degree of privacy and intimacy that larger screens, even the tablet, just can’t replicate. Facebook saw that a long time ago and snapped up a few cool startups. Ditto Twitter. Ditto Google. And the rest of us are behind[…]