IBM impacts SA finances

Nedbank group chooses Cognos Software

At the IBM Financial Performance Management event, held recently at the Crowne Plaza Hotel in Rosebank, Preyesh Mestry, Head of IBM Cognos Development and Support at Nedbank Group, discussed the challenges faced by the group and how a Financial Processing Architecture (FPA) was implemented, using IBM Cognos technology as a base, to help solve some of these issues and streamline the finance and budgeting processes.

According to Mestry: “Prior to implementing IBM Cognos Software, Nedbank’s budgeting was completed on spreadsheets and a variety of other applications.

Calculating group level budgets was conducted in this way too, interfacing at a divisional level. This meant that the various divisions and Group finance often had different final numbers. Another problem was that the level of detail varied greatly between clusters as the reporting was based on data from many disparate toolsets.”

“This is a common problem among large, geographically dispersed or decentralised organisations,” said David McWilliam, Manager: IBM Business Intelligence & Performance Management, IBM South Africa. “Disparate data coming from many different sources leads to complexity, inaccuracy, error and time wasted spent trying to correct these mistakes that could have been avoided in the first place.”

Several vendors were involved in the selection process before Nedbank group settled on the IBM Cognos platform, selecting Cognos because of its flexibility, ease of use, look and feel, its alignment with the technical and architectural functions at Nedbank, and the total cost of ownership, which is far lower than many of IBM’s competitors.

“The IBM Cognos solution has several benefits for the Nedbank Group,” concluded Mestry. “It is a fully decentralised solution, so that divisions can prepare their budgets at a detailed level, based on their own requirements, with full drill down capability. A central database means that there is a single source of the truth for budgeting and forecasting purposes. This leads to quicker turnaround times, enhanced processes, more ownership at cluster level and ultimately alignment between Group and Cluster budgets and forecasts.”