Love Your Silos: Manage Legacy Silos with Control and Insight

Departmental silos in the business world have been around for as long as I can remember, as has the discussion to somehow be rid of them. Besides the inefficiency and cost of having multiple repositories of data spread across an organization, these silos create obstacles and lack of insight into how the overall business is performing, limit the ability to measure or track service level agreements (SLAs) and key performance indicators (KPIs), prolong time to market for new services, and limit visibility into how one team’s decisions will impact other areas of the business. In an effort to break down silos, companies have sought out workarounds with less than stellar results.

For years the industry has discussed improving customer experience, urging service providers to get rid of the swivel chair. Automate. Break down silos. The reality is that many companies have relegated customer experience management to up-sell and cross-sell solutions, CSR enablement, and/or a variety of network optimization methodologies. These methods have fallen short and only addressed small portions of the problem, as poor customer experience ratings still run rampant.

In addition to the customer experience issue, there is an increasing need for operational readiness, as the rate of change rapidly accelerates, new services and devices are being introduced at unprecedented rates, and new technologies such as SDN and NFV require real-time insights, analytics, and automated actions. In addition, as more service providers approach the business services market, there is a demand for real-time insights due to the financial implications of unmet SLAs. In an attempt to create operational readiness, some companies have chosen to connect their silos with multiple integration points. This provides domain-specific information and supports key operational processes, but doesn’t provide the level of visibility or control at the network level to take action across the domains.

Today’s technology climate requires that companies rethink traditional ways of addressing these challenges and leverage a dynamic, service-level architecture that leverages the collective strength of their legacy and next-generation resources and match those with key performance indicators (KPIs) that affect service quality and SLA requirements.

Companies with large complex networks cannot effectively improve their service levels and operational readiness with the discussed traditional approaches. Today’s data-driven and increasingly virtual environment requires that companies with large, complex networks leverage a combination of both existing legacy resources as well as new systems and tools from disparate silos to improve the customer experience and remain competitive in today’s marketplace.

Service Providers have to start looking at network management from the service perspective, leveraging insights and controls that work at a service layer above all of the individual silos. By moving up to the service layer, service providers can leverage the data and functions of each silo so they can have complete visibility of the service and industry standard KPIs, and then push actions down to their existing silos for proactive remediation.

A holistic view across the entire business enables companies to better manage the overall business health and performance. Businesses can instantly begin to reduce operational costs, improve efficiencies, increase revenues, and elevate the customer experience, answering critical questions and providing actionable insight to departments throughout the organization.



Call it ‘service assurance’, or you’re in enterprise and call it ITSM applications have grown significantly more c...
Call it ‘service assurance’, or you’re in enterprise and call it ITSM applications have grown significantly more c...
gen-E®was recognized in the 2017 Pipeline Innovation Awards for its vital contribution to advancing big data and analyt...
gen-E®was recognized in the 2017 Pipeline Innovation Awards for its vital contribution to advancing big data and analyt...
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