May 28, 2015
By Tracey E. Schelmetic, TMCnet Contributor
When it comes to inside sales, it’s a job that’s frequently performed by newbies: young people right out of college, interns, or people changing careers. Inside sales was once considered a good place to start a sales career because it exposed the recruit to a great deal of hands-on training and mentoring by a sales professional in the form of an inside sales manager. It’s one of those ideas that looks great on paper, but seldom represents reality. Often, sales managers don’t have the time they might wish to nurture would-be sales superstars to fruition.
Under-trained inside sales reps mean that leads are lost (or never found), time is wasted and outside sales teams don’t get the support they need to fill the sales pipeline. Accordingly, inside sales team members who might otherwise have promise are missing out on becoming talented outside sales team members. The situation is getting worse, not better, as most companies today strive to keep headcount low. According to Christopher Mims writing recently for The Wall Street Journal, there’s a place for big data analytics here to literally “fill in” where sales managers leave gaps. Essentially, it’s a way to break down the upside-down pyramid structure of a sales organization and push more responsibility to each individual member of the team.
“Startups are nimbler than they have ever been, thanks to a fundamentally different management structure, one that pushes decision-making out to the periphery of the organization, to the people actually tasked with carrying out the daily business of the company,” wrote Mims. “And what makes this relatively flat hierarchy possible is that front-line workers have essentially unlimited access to data that used to be difficult to obtain, or required more senior managers to interpret.”
One of the individuals Mims interviewed for his article spoke of “data bread lines,” a scenario in which managers had all the data they needed, but their staffers had to get in line to get the information they needed to make decisions. The nature of data management once made it necessary to limit data querying to a few people in-the-know. Today’s data analytics make it possible to make the intelligence easily accessible and customizable to anyone in the organization who needs it.
“Cloud-based services that connect to or ingest whole databases mean anyone in a company can, for example, instantly calculate the lifetime value of a customer according to where they came from and what they previously bought,” wrote Mims. “Or a sales employee can throw as many different considerations as needed into a calculation of the return on investment on an advertisement.”
The result is that every employee can access the tools to monitor progress toward any goal, and the old role of middle managers as people who gather information and make decisions can be deemphasized, particularly in today’s culture of spreading responsibility out to the people who actually work in the trenches. With new startups bucking traditional hierarchical management structures, this availability of data at all levels will be an important way to ensure that responsibility is spread out in a way that doesn’t cause the organization to collapse.