Modernizing Giants

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Modernizing Giants

Transforming Legacy Systems with Data

Modernizing systems and staying agile for a large enterprise is not a trivial thing. It’s an important part of staying competitive, but it can also be a challenge for entities whose networks are vast and whose history of innovation spans decades.

Any industry that was in operation for years before Big Data often finds themselves in a position where they’re operating on legacy infrastructure. In fact, up to seventy percent of global IT is running on legacy applications, throughout government, air, auto, manufacturing, and telecommunications – just to name a few.

Telecommunications companies are an excellent example, just by virtue of the size of their infrastructure, the vast amount of data they possess, and the many years they’ve been in operation. Incidentally, today is World Telecommunication Day – so in that spirit, let’s look at how technology is helping to augment and modernize their systems.

Lixar has a twenty-year history working with Telcos, and we quickly came to understand the complexity of their setups. The massive amounts of data these companies hold, and the array of silos in which the data lives is simply staggering. We’re talking an unfathomable number of data points in multiple repositories across networks of legacy tech, much of which have not or perhaps cannot be migrated to the cloud.

If medium-sized companies are steering a yacht, Telcos are steering an aircraft carrier. Shifting to new IT is no small undertaking. But, large as these companies are, they still recognize the need to modernize.

Augmenting Legacy Workflows

Supporting Telcos in their modernization is almost as complex as the systems they depend upon. Overhauling the entire network would take massive amounts of time and money. Keep in mind these entities are focusing on endeavours like building infrastructure for 5G. Shifting the focus to completely updating technology that has in some cases been around for decades would stall progress, which would be unproductive for both the company and society as a whole. So modernizing these systems becomes an art of convergence – taking these legacy systems, those individual silos of data, bringing them together and building on top of them to produce something great.

The Solution: Data Modernization

As a small scale (but no less complex) example, let’s examine something we can all relate to: the customer’s experience with technicians and installation. We’ve all had internet or cable installed in our homes. Many Telcos make up to 10,000 of these installations each day, for a wide variety of customers.

Technicians have to keep a plethora of information in mind for each installation: scheduling, dispatch information, what product they’re installing, previously installed technology that needs to be taken into account, infrastructure in the immediate area, as well as more technical and complicated details. Keep in mind that all this info is rarely in one place – it resides in disparate locations across those different silos. Looking at these complexities and variables, it can be extremely difficult for the technician or the company to tell you when they’ll arrive.

Nonetheless, Telcos realize the importance of keeping up with the times and with customer expectations. Clients expect more specificity with the time of their appointment, and they expect the technician to have all this information at their fingertips. Taking this data, from all these disparate data sources, and porting it over to a central location is not an option – there are too many moving pieces and dependencies. But connecting all these resources and making them talk together is where Data Transformation occurs.

Connecting to the Modern World

Imagine a solution that takes information from those disparate silos and connects it to an easy-to-use mobile application for technician use. Data on scheduling, dispatch information, details about the customer, the surrounding network, pending orders, billing, product installation information, finance and account management is all discoverable with the tap of a screen for fast access on technicians’ mobile devices. Ultimately, bringing together this data could improve diagnosis of technical issues and allow for higher install success rates. Building on top of the legacy infrastructure and connecting these data sources would help reduce installation time and increase customer satisfaction.

A customer-facing version of this app would also allow clients to get better estimates in terms of duration of work and appointment time, giving them to access real-time information including details on dispatched technicians and their estimated arrival time.

This could be accomplished first by looking at these legacy workflows and understanding the data within. Experts assess and categorize types of data in these systems and apply a layer of APIs which sort the data into the appropriate buckets. This is the transformational aspect of the process – once the data is sorted and housed in the proper location, it can be leveraged for any number of solutions – mobile applications, Machine Learning, Artificial Intelligence and more.

transform-old-workflow

A similar method could be used to transform old workflows for the example above

That’s just a glimpse into the power of connecting data sources. The same kinds of solutions can be applied not just to Telco, but any industry that is working with massive amounts of data and complex legacy setups. This touches on our work in government, manufacturing, auto and air.

The Telecommunications industry is embracing the digital age; as they create the framework for a new age of digital communications, they also look back and transform their existing infrastructure through Data Transformation.
So here’s to Telecommunications Day! “Hats off” to our partners in the Telco space – the massive scale at which they operate and the feats they accomplish, all while pulling together a multiplex of systems and infrastructure is nothing short of impressive.

For details about Lixar, contact us at:
data@lixar.com or visit our data page at https://lixar.com/ai-data/