Cold calls used to work, then they didn't and now they work again. I used to agree with most people, that cold calls do not work. In fact, I established my sales career on referral networking. However, I have rediscovered the power of cold calling and how to do it effectively. Networking is still important, but now I don't have to wait around hoping for referrals.
We love predictive analytics and if we are not careful, it is easy to start reducing everything into predictive models. I have even caught Tadd standing at the window collecting primary data on the smoking habits of the people in our building. To make sure that CAN and predictive analytics experience continued success, we have developed a guide for when to apply predictive analytics.
First, predictive analytics should not be applied if:
The cost of being wrong is low.
You should not apply predictive analytics if reducing uncertainty does not provide enough value. Predictive models should only be applied in situations with a high cost and/or probability of being wrong and where predictive analytics can provide information to reduce uncertainty. To determine if predictive analytics is worth applying to a decision you need to calculate the expected value of information. In the book How to Measure Anything, Hubbard provides the following formula, expected value of information is equal to the difference between the expected opportunity loss before and after information. The expected opportunity loss is equal to the chance of being wrong multiplied by the cost of being wrong.
The value of dashboards and visualizations are that they allow users to shift from serial to parallel processing. When reading a block of text you can only process the information serially by starting at the top left of the text and finishing the bottom right. Dashboards and data visualizations allow you to absorb information in parallel making it easier to absorb information quickly, identify relationships and trends.
A dashboard is a single display that in a glance provides essential information for a specific objective. Since you are limited to a single display capable of being monitored at a glance, the first step of dashboard design is to select the purpose of your dashboard. This provides you with a filter to make sure that your dashboard effectively accomplishes its intended purpose.
Predictive analytics is the next step in the evolution of business intelligence. Most companies, even local small business, have already implemented business intelligence systems that help them understand what has happened, why it happened and what is currently happening. For example, most small businesses have implemented Quickbooks and Google Analytics that allow them to report, analyze and display data about their finances, operations and marketing.
It is official, Drew Davies and Drew Gourley at Oxide Design have turned CAN into a Lolcat. This is quite out of the ordinary for an enterprise predictive analytics company, and we are unsure what this means for our brand and customer loyalty. So, our analysts are working hard to answer this new set of business questions, all because of a Lolcat.
This post is part of a series of interviews with experts in business intelligence, sales management, marketing, customer retention, management and strategic planning. Everyday, the CAN team interacts clients, mentors, and friends who are leaders in their fields, and we started this series to share their expertise.