At Contemporary Analysis (CAN), we take a completely new approach to helping companies and organizations get more out of the information they have access to. At our core is the idea that businesses should be working smart and hard. At CAN, we are different because we always keep the human element, actionable impact, and added value at the forefront of our development process.
We start the entire process with keeping the human element in mind. Everyone has gone through the frustrating process of being passed off from one person (if you’re lucky enough to reach a real human) to the next throughout a customer service or sales process. In most of these situations, half the time speaking with a new person is catching him or her up on things you have already said to other members of their organization.
At CAN, we understand the importance of having one contact throughout the entire process. This contact, known as a Navigator, takes the time to understand your specific business and helps you distill problems with big impact solutions. Navigators understand the majority of managers and executives don’t have the time to learn about predictive analytics. Navigators take the time and effort to understand the problem or issue from the end user’s point of view and then strategize to reverse engineer an efficient solution. It is our job to couple your expert knowledge and historical data to give you a solution with impact.
At CAN, we understand businesses outsource services for added value. The value of using predictive analytics is only as great as the actions and changes made with the information provided. You could have a GPS system in your car, but if you never turn it on, it doesn’t do you any good. From step one in our customer process, we work on finding helpful insights into areas in which you can TAKE ACTION or MAKE CHANGE, not just look at the report and think “Hmm, that’s interesting.” If the information we provide doesn’t induce change on at least some level, we didn’t properly do our job.
At CAN, the solutions we provide make sense financially. We use predictive analytics to answer questions in about 30 days. Think about that for a second. In just 30 days you could have an analytical model which, while not being perfect, will allow you to make much more informed decisions. Whether it’s having a better understanding of up-sell, cross-sell, or customer loyalty. It is important to remember, the goal of predictive analytics is to be LESS WRONG, and models continually become less wrong by using current information to test and re-test.
Compare 30 days with CAN to the alternatives – doing nothing or creating an in-house predictive analytics department. In smaller companies, the alternative to CAN is to do nothing. Smaller companies don’t have the resources to create in-house predictive analytics, but have a lot of the same issues as large companies.
The other alternative is in-house analytics. I believe in-house predictive analytics departments are something every large company should invest in. Properly managed and financed in-house departments can change organizations in ways never thought possible, in ways which only the future will show us. No longer would justifications for decisions be based on gut instinct, or worse yet, “because that’s how we’ve always done it.” This business is your passion, and nothing proves a point faster than quantitative justification. However, what if you’re not a large company?
In-house departments require management, direction, and resources. A company looking to develop the smallest possible in-house predictive analytics department will pay for the following:
- Find and hire a highly sought after Ph.D. or Masters at a cost of 75-150k.
- Add half the salary again for employee benefits, taxes (FIFA, FICA, etc.), office space, physical equipment, and HR resources.
- Purchase a Tableau, SAS, or SPSS license costing 10’s of thousands of dollars for just one year
This cost of 175-250k is just the initial investment. You haven’t solved one problem yet. Taking into account the months of required training and corporate acclimation before any useful insights can be made by this new hire, it can be 12 to 18 months before you have a solution to just one of your smallest problems. 30 days and a cost of at least a zero less sounds much better to me.
Like I said before, I would encourage all large companies to take the plunge into predictive analytics. Even with well developed predictive analytics solutions there is a high possibility the department would suffer the same downfall as some IT departments, the disconnect between who designs or provides the technical knowledge and who actually uses it on a day to day basis.
At CAN, we take your expert knowledge and use your data to provide valuable insights you never thought possible. Throughout the entire process, we never lose track of the importance of the human element. Whether you’re a large company with an in-house analytics department or smaller business with no means for self analysis, we care about your business and can give you value in the form of information from which actions can be taken.