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What are the odds of developing a brain tumor from long-term use of cell phones? This is an evolving area of research.  Some studies have found an association and others have not. But two recent meta-analyses suggest that the odds are about 33 to 44% greater due to long-term cell phone usage. Got your attention?…

What are the lifetime odds of dying from being hit by a meteorite? 1 in 1,600,000. Yep, not very likely.  You are much more likely to die from a dog attack (1 in 86,781) or from a lightning strike (1 in 138,849). But why odds? Why not express these likelihoods in terms of probabilities?  Seems…

First time users of Tableau often get tripped up over the default Tableau SUM aggregation.  Here is what I mean. Suppose the question is to find the average of SALES PER VISIT (sales measured across the preceding 6 months) among the males and females in a sample of 25 shoppers.  The data look like this…

“Big data.” We checked in with Google search trends recently. Appears that “Big Data” has lost its luster search-wise…started trending down about 4 years ago. Nowadays, everything is big data? Implications of big data However, this does not mean we should lose sight of certain statistical implications associated with being “big”. Yes, large amounts of…

We just noticed that it has been a full year since we started posting daily updates to our San Diego County COVID-19 dashboard. This dashboard tracks the San Diego COVID experience: new cases, tests, and positivity rates at the county-level as well as new cases for each of the county’s ZIP Codes. On this first-year…

You like potato and I like potahto You like tomato and I like tomahto Potato, potahto, tomato, tomahto Let’s call the whole thing off But oh, if we call the whole thing off Then we must part And oh, if we ever part then that might break my heart —Ira Gershwin The eye-popping efficacy rates…

In case you missed it, we are in a recession. According to Intensity’s latest US recession start date forecast, there is a 50% probability of a recession starting sometime in the January to February 2019 period.  And a 97% probability of it starting sometime within the next 6 months. Their “point estimate” of a recession…

“A good forecaster is not smarter than everyone else, he merely has his ignorance better organized.” ― Anonymous Predicting the future is an exercise in probability rather than certainty. As we have mentioned several times over the course of these articles, your forecast model will be wrong. It is just a matter of how useful…

“There are two kinds of forecasters: those who don’t know, and those who don’t know they don’t know.” ― John Kenneth Galbraith After an extensive model building and vetting process, along the lines we previously discussed here and here, the practical forecaster may still be left with several strong performing models. These models perform similarly…

“Prediction is very difficult, especially if it’s about the future.” ― Niels Bohr, physicist Holdout samples are a key component to estimating a “useful” forecasting model. Set aside data at least equal in length to your forecast horizon (“holdout sample”). Build your models on the remaining data (“modeling sample”). And compare the candidate models’ forecast…

“It is sometimes very difficult to decide whether trend is best modeled as deterministic or stochastic, and the decision is an important part of the science – and art – of building forecasting models.” ― Diebold,  Elements of Forecasting, 1998 A time series can have a very strong trend. Visually, we often can see it. Gross…

“In God we trust. All others must bring data.” ― W. Edwards Deming, statistician So, you have estimated a bunch of forecasting models and realize (kudos to you!) that they are “all wrong” (ala George Box). But your forecasting deadline is looming, and you need to find some useful models on which to base a…

“The only relevant test of the validity of a hypothesis is comparison of prediction with experience.” ― Milton Friedman, economist Holdout samples are a mainstay of predictive analytics. Set aside a portion of your data (say, 30%). Build your candidate models. Then “internally validate” your models using the holdout sample. More sophisticated methods like cross…

“Big data is not about the data.*” ― Gary King, Harvard University (*It’s about the analytics.) Machine Learning. Deep Learning. Data Science. Artificial Intelligence. Big Data. Not a day goes by that one or all of these buzzwords stream past in our business news feeds. Data analytics has become mainstream. And you better jump on…

“All models are wrong, but some are useful.” ― attributed to statistician George Box This quote pretty well sums up time series forecasting models. Any given model is unlikely to be spot on. And some can be wildly off. But through a careful methodical process, we can whittle the pool of candidate models down to…

“The long run is a misleading guide to current affairs. In the long run we are all dead.” ― John Maynard Keynes, A Tract on Monetary Reform Forecasting the future is an exercise in uncertainty. And the further out one looks, the more uncertain the forecast becomes. Most businesses are keenly focused on the next…

“The only thing I cannot predict is the future.” ― Amit Trivedi, Riding The Roller Coaster: Lessons from financial market cycles we repeatedly forget It goes without saying that every business is keenly interested in knowing what the future will bring. Will sales grow next year? By how much? Will suppliers increase their prices? How…

We were looking for data nuggets in the TUDLA Latin America B2B database the other day and stumbled on something that, to hardcore Tableau users like us, was quite surprising. Turns out that in the LATAM region, Tableau is not the preferred data visualization platform. In fact, it is not even in the top five.…

Shelby Cullom Davis, “one of the least talked about, but most successful investors,” managed to parlay a 1947 $50,000 investment into over $800 million by the time of his passing in 1994. A 23% compounded average annual rate of return.  Not too bad. During his career Shelby advised Thomas Dewey on economic matters when he…

In “places like … Raleigh, you see a real concentration of brain power. You have a lot of smart people living in the same place. That will drive the economy”, Steven P. Rosenthal, Northland Investment Corp. And so will tax incentives. The Raleigh-Durham-Chapel Hill combined statistical area (CSA), with over 2 million people, is the second…

Today, at least in the financial world, Omaha is probably most famous for being the home of Warren Buffett and Berkshire Hathaway. The company is “currently the 7th largest company in the S&P 500 Index by market capitalization and is famous for having the most expensive share price in history with a Class A share…

A healthy share of Fintech investment has been on the banking-side of the financial services industry, especially loan origination like LendingTree, OnDeck & SoFi, and in payments companies like Venmo, Stripe & PayPal. However, the Securities & Investments sector is also undergoing disruption. Companies like Betterment and WealthFront are targeting investment advice. And StockViews, AlphaSense, Alphametry,…

One of the uses of any B2B database is to find prospective customers that look like current customers (aka “look-alikes”). With more developed and complete data, like what exists for the US, this can often be done using statistical predictive models. These models can yield “prospect scores” appended to individual business locations as to their…

Posts like “Facebook’s Q4: Conference Call Tone Matters More Than Results” in the financial press suggest that earnings call tone is important. And, invariably, the tone of the call does come up during the post call commentary and analysis. Were executives overly positive in their comments? Did they mean what they said? Did analysts’ questions…

In the Americas, once marketers venture beyond the US and Canada, basic firmagraphic information on businesses starts to become spotty.  Marketers used to powerhouse databases like ZoomInfo, InfoUSA, Data.com, D&B and others must scramble to assemble what information may exist for the Latin America (LATAM) region.  If basic data like company name and address exist,…

An old piece of business advice for startups is to “get out of the office and visit customers.”  “Great,” you say, “the Fintech market is over $18b (see our previous post)!  Where do I find my prospects?”  If you have a new service for savings and loans or their customers, the data may point to…

Fintech, or Financial Technology, has been around for some time.  Lately, interest has been gaining steam, particularly among venture capitalists.  However, fifteen years ago, this was the abbreviation used when banking discussed its plans for IT spending, mostly back office infrastructure.  When you hear the term now it’s #fintech, referring to startups threatening to disrupt…

The “five forces of context” (mobile, social media, data, sensors and location) have be called the future of computing. Why? Because they may finally give computers the ability to understand “your context”. Analysts under time and deadline pressure need to know that the information distilled by an AI solution is relevant to their context and…

Is “almost” good enough?  In terms of concept detection, the answer is most certainly “yes”.  In another guest post by Tom Marsh, CTO at Boulder Equity Analytics, Tom argues that textual analysis using BEA’s AI software allows analysts to efficiently cull through mounds of documents to eliminate the noise.  What is left are “scored” paragraphs…

Tableau is a powerful tool for visualizing data.  It is easy to throw data into, to start exploring data and to begin creating charts.  But there is a lot going on “under the hood” and more advanced analytics requires a bit of a learning curve to get Tableau to do what you want it to…

Some form of textual analysis has become a standard feature among services that offer summaries of large volumes of documents.  Natural Language Processing (NLP), deep learning and neural nets are buzz words we often hear.  But when you look under the hood, most of the functionality is based on keywords, word counts and rigid taxonomies. …

Guest Author – Tom Marsh, CTO of Boulder Equity Analytics. At Boulder Equity Analytics (BEA), “Our mission is to build an intelligent, enriched and fully interactive database from all the publicly available reports to improve the productivity and insight of the analyst covering an industry sector.”  We call it O.A.K.L.E.Y, collaborative artificial intelligence, a 2nd…

Guest Author – Tom Marsh, CTO of Boulder Equity Analytics AI, artificial intelligence, has been through several boom and bust cycles.  Today the pronouncements are everywhere with AI coming soon to everything from medicine to your underwear.  For those of us laboring in the dark for years, it feels good to be the most popular…

KDD Analytics is offering free access to its annually updated ZIP Pointe™ Market Sizer. ZIP Pointe™ Market Sizer offers a quick and comprehensive way for B2B marketers to estimate the relative potential size of US private sector markets.  Offered as Tableau dashboards, ZIP Pointe™ Market Sizer is based on the most current US Census data…

As we saw in an earlier article, the Information Services industry is the most “intensive” user of information technology (IT).  In 2015, the Information Services industry invested (per worker) over 8 times has much as the average and nearly 300 times as much as the least intensive industry. This is not just a single year…

“It is sometimes very difficult to decide whether trend is best modeled as deterministic or stochastic, and the decision is an important part of the science – and art – of building forecasting models.” ― Diebold,  Elements of Forecasting, 1998   A times series can have a very strong trend. Visually, we often can see it.…

According to US government data (US Bureau of Economic Analysis (BEA)), Healthcare industry investment in computers, software and communications equipment has grown by a compound annual rate (CAGR) of 6% since 2000.  For the rest of the private (non-government) US market, such investment has grown at a slightly lower rate of 5% per year. Interactive…

Investment in information technology by US businesses varies dramatically across industries.  On a per worker basis, the top industry invested over 300 times that invested by the bottom industry in 2015. Why does information technology investment per worker matter? While information technology (IT) investment per worker has grown over time across all industries, there clearly…

“84% of B2B buyers are now starting the purchasing process with a referral, and peer recommendations are influencing more than 90% of all B2B buying decisions.” (Harvard Business Review) Wow! Why are buyers shying away from salespeople?  According to this same article, salespeople “tend to prioritize a sales agenda over solving a customer’s problem.” To…

Data availability can limit the quality of B2B prospect scores.  We are not talking about sample size, which is important.  But about the characteristics of the businesses the prospect score is meant to rank. A client’s customer was using an “off the shelf” application for prospect scoring.  This application used a very limited set of…

We build a lot of B2B prospect scores for one of our clients.  One customer of this client recently tested a prospect score we built on their behalf. Their goal was to determine how much “lift” the prospect score provided to their outreach campaign for their information technology networking solution.  That is, they wanted to…

It’s 8:00 pm, the night before the quarterly board meeting.  And you are still pulling together financial data on your company, as well competitive intelligence on your competitors, into presentation worthy graphics. Procrastinator?  Maybe. But one key section of your financial competitive intelligence report is hampered by a lack of standardization in SEC filings.  Moreover,…