So we find executives working on two significant strategies:

First, there are numerous efforts underway to implement a program management office approach to centralize corporate analytics expertise and make that expertise readily available to each business unit. This central analytics team is led by an experienced program management executive (not necessarily an IT executive) that reports to the C-Suite and is a critical player in top management decisions.

In addition to personnel, the analytics team is implementing new infrastructure to unite transaction, customer, and competitive data with unstructured social-media data and users. The federation of big data elements with real-time unstructured data is a technology challenge faced by many businesses and solutions are just now coming to market to address it.

Second, business units are addressing what metrics matter and what actions should be taken as a result of the analysis. The sophisticated models and analysis coming out of the analytics team must be integrated into existing systems and tools. The interface must be simple and intuitive so that business unit employees will believe the analysis and make good use of the data. McKinsey reports that companies spend 90% of their investment on models and only 10% on front-line usage. Perhaps that needs to change.

Many service providers lament that finding out about a problem or opportunity is one thing; doing something about it is another. Doing something requires processes, training, systems, equipment, and people. There is expense involved, not to mention the amount of time required to get all of the customer-facing staff on board with the change. But the business benefit of big data and analytics' efforts relies on the ability of the business to turn insight into action.

Analytics to Insight to Action

With products from washing machines to weather stations including a digital services component, service providers are experiencing demand from every industry to deliver more than just bandwidth. As service providers focus on defining and delivering digital services; product development requires a substantial IT component. Merging IT with product development means there are more data sources, more metrics and more decisions. The ability to apply analytics to understand industry-specific trends, digital services impact, customer needs, and transformation requirements enables operators to develop and deliver new business-focused solutions both in the cloud and on the ground.

Decision Engineering

Businesses in every industry are restructuring their communications networks to support digital services and to bundle connectivity into new products for their customers. Cisco used the Decision Engineering for Enterprise Project Management (DEEPM) solution from Quantellia to upgrade its cloud-based unified communications solution for a large banking customer with 10,000 locations in 53 countries.

Using a simulation-based forward business rules engine, DEEPM provides automated visual what-if analysis for the management team, allowing them to experiment with and evaluate changes to the program plan and remove obstacles before they become problems. The transformation plan is continuously analyzed and optimized to provide maximum financial benefit: by transforming centers that yield the greatest operational cost savings as early as possible, while still satisfying the specific business rules and overall constraints of the program. 

Managing a Growing Network

What started as a download of free software for evaluation became a critical piece of corporate IT infrastructure for Ritter Communications. Ritter is a regional telecommunications provider delivering services to more than 40,000 customers in Arkansas and Tennessee. Ritter downloaded the free version of the SevOne IT monitoring solution and had it up and running in minutes.