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Location as a Foundation for Digital Transformation

By: Ben Edmond

It’s virtually impossible to find a senior executive in any industry who hasn’t heard of digital transformation. The concept of applying innovative digital technologies to solve critical business problems is disrupting all major verticals, from healthcare to manufacturing. While most businesses aspire to be seen as technology-savvy leaders in their space (and have drafted annual, CIO-driven initiatives to back it up), succeeding in truly transforming an organization is often very difficult. It requires abandoning old methods and processes while simultaneously embracing new ideas and approaches to running a business.

The telecommunications sector is no different and for an industry whose products enable the digital transformation of other verticals—whether ride-sharing or consuming business applications in the cloud—the space will continue to experience the pressures of major market forces that will necessitate the need for its own digital transformation. The key to unlocking digitally driven growth in this environment will be to start with a mindset of “location first” and build out all go-to-market operations around that mentality. Those who can adopt this mindset and overcome the difficult transition of parting with the old way of conducting business will not only survive but also capture market share and grow in an increasingly complex space.

Understanding the process gap

The telecommunications space does have a great track record of innovating and delivering high-quality, digitally driven user experiences to customers. OSS/BSS technologies have done a nice job of automating many backend operations such as order management and billing. The issue, however, is that this level of innovation hasn’t made its way to the sales and marketing sides of the organization. This go-to-market function should be the focus for any CIO looking to identify the place to enable maximum value with digital transformation initiatives. 

Let’s take a look at sales organizations in particular within the connectivity space. Say you ask a senior-level sales executive to show you the best targets for the team to pursue, based on data-driven insight into all of the buildings they can service, which tenants occupy those buildings, or how many other competing networks service those sites. You’ll likely get long processes with multiple touchpoints to drive those answers—if they exist with any real accuracy. Moreover, if you asked this leader if they can incorporate this into the pricing strategy, you’ll probably see that this is a significant pain point as well. The cold reality is that digital transformation hasn’t truly made its way to the front of the house, mainly because it’s been virtually impossible to establish location as the primary object of focus and layer on top of that the intelligence needed to make smart decisions—and the automation required to execute quickly.

Successful transformation of the go-to-market operations of a network operator offers the opportunity to capture increased revenue and market share in the space. And, a few key areas have the most impact on the sales pipeline and process. Specifically, these include:

  • Increased visibility into potential deal flow: a sales organization has the ability to identify its entire addressable market (whether the buildings are on-net, near-net, or served through a growing ecosystem of suppliers) and automatically communicate that internally and to partners
  • Higher win rates: sales leadership and sales representatives alike have a shared, data-driven method for identifying the optimal opportunities to pursue—whether those opportunities are direct, wholesale, or channel-driven. Most of the data needed to support a viable method would relate to network and tenant insight, such as the competitive nature of the building or a detailed understanding of the end customer and their technology stack
  • Higher average selling prices: sales teams that successfully transform themselves should be able to leverage highly specific, building-level data to intelligently assess a price for each product and subsequently automate the process of issuing that quote to the customer


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