Spin it Like Einstein: Why Traditional Technology Sales No Longer Works

Brian Gagnon
July 19, 2018

“If you can't explain it simply, you don't understand it well enough.” Albert Einstein


Einstein didn’t need a sales force to go out and “find customers” for his groundbreaking insights about the structure of matter, time and space. He published scientific papers at the age of 26 that brought instant acclaim in academia and eventually, accolades from every strata of society. He had a mind that understood the structure of the universe and could also explain these weighty concepts not only to his peers but to the average person as well.


Many commercial ventures don’t employ a team of “Einsteins” but instead train and employ sales people (sales engineers and account managers) to go out and peddle their products against other companies with similar ambitions. In this case, it’s not the physics of the universe that needs explaining, it’s the increasingly complex landscape of the intersection of technology and business refinement and operations. With the advent of machine learning, artificial intelligence, and other seemingly brainy technology game changers, businesses need to get a much more in-depth understanding of how these can change their business and increase profitability, sustainability and portfolio of services.


Don’t get me wrong – I’m not suggesting sales people aren’t intelligent and don’t understand their customers. They simply aren’t embedded in the day-to-day complexity of client problem solving and all that goes into crafting the solution – from algorithms to analytics and strategy creation.


A relatively new concept, infonomics, is a promising new area of identifying, monetizing and acting on data, is changing the classic idea that ‘information is power’. Sure, everyone knows that the more you know, the better your chance of doing the right thing at the right time. The sheer amount of data generated by today’s business interactions and the “internet of things” alone requires a steady increase in resources, time and effort to find the golden needles lying in the vast haystacks of data. Meanwhile, the meter is turning on the cost to produce, store, categorize, back up, restore, process, etc. all this data.


Here’s the challenge: traditional IT sales teams are out there with products to sell that continue to fulfill their pipelines while furthering the problem: sell more storage, faster storage, cloud compute, secondary backup, failover software, on-prem hyper converged compute and storage. None of these help solve the problem – by no fault of the sales teams or their prospects, but because many companies don’t have a strong grasp on where the value of their data exists. As a result, business as usual is easy and the past of least resistance for a sale.


MIT estimated in a 2017 study that only 0.5% of data stored is ever processed and analyzed. This isn’t an infrastructure problem, it’s a value identification and optimization problem. How can we identify valuable data for the business to drive automation and ensure the right people can access it decisions? Today, this is best solved by experienced consultants and engineers that can take plain text problems and challenges and translate them into algorithms, workflows, process improvements that help solve the equation, not just sell the next greatest piece of tech and hit a quota.


Rather than fielding a sales team to identify opportunities and operating in the traditional hunter roles, we’re leveraging consulting experience that can identify and solve problems, whether they be process improvements, growth challenges, hardware and software optimization, or how we employ machine learning smartly.


Clients and customers are increasingly savvy in their approach to finding solutions to their problems. We have doubled down on shortening the connection between the technology that solves problems, the people that can translate the solution, and continuously refining the whole ecosystem systematically.


Experience and knowledge sells itself. Infonomic Data is a consulting firm first and a software company second today. Over our evolution, we’ll transform to a much more software led solution when customers are ready for that step in the journey. We understand the complexities of bringing artificial intelligence, machine learning, deep learning, and cognitive science into use throughout an organization so well that we can explain it — simply – without a sales team.