BT

BT used Ontology to analyse infrastructure dependencies in planning the consolidation of the many networks operated by BT Global Services

Situation

BT is undergoing unprecedented network, OSS/BSS, and business transformation. The program is very complex and as OSS/BSS applications are targeted for decommissioning or change, it is important to understand what impact those efforts will have on the networks, services, and customers. Migration planning for BT's transformation requires more than scheduling and execution, it also needs impact analysis and risk mitigation. In addition to planning and impact analysis, the transformation architects must be able to perform 'what if' analyses to understand how operations change when either a specific OSS/BSS or combination of systems are removed.

Solution

The project started by building a high-level migration planning capability using Ontology. By starting with a specific transformation goal (e.g. decommissioning Product A in Geography X), models were built to determine the customer impact and correlate the actions of the various teams. At the end of a six-week period Ontology provided comprehensive information views, data cleansing, and intelligent data-mining for BT's "what if" scenarios.

Five dependency dimensions were analyzed - applications, products, networks, customers, and processes. The ability to analyze dependencies in each area, as well as interdependencies across the dimensions, provided BT with centralized transformation program governance. The analysis shows the potential impact of migration on specific customers and delivers a correlated understanding of the interactions of transformation plans. 

Benefits

Significant cost savings attributed to short development timescales and to the major reduction in the migration planning period (75% savings in delivery time and estimate of 30%+ in overall project cost reduction).

Right-first time: minimise iterations required to obtain a complete, consistent and accurate understanding of the migration impact and therefore to eventually determine a cost-effective plan through optimal ordering of the migration tasks.

Accelerated migration by bringing product and system consolidation forward in time, therefore realising cost savings sooner.

Enhanced business knowledge by revealing hidden dependencies among the estate entities and identify inconsistencies through measurements of the data quality.