Evolving a CX/PX credibility rating model for software organisations: A joint endeavor with CRISIL, India

Abstract

This document details our work towards evolving a Credibility Rating Model for Software Organizations, a joint effort with CRISIL Bangalore, our guide & 'customers': Unlike credit rating (which reflects the ability of the issuer to meet the financial obligations towards the investor) Service credibility rating, reflects the capability of the management and sustainability of service of the IT Service provider. Service Credibility Rating works on the principle of estimating the maturity of the IT Service provider - in Managing risks on multiple fronts - Strategic, Financial, People, Process and Technology, including customer centricity aspects such as service delivery and post delivery service. The methodology used is an extension of the methodology used for Credit Rating. Credit Rating has a risk perspective and looks at Business, Financial & Management Risk. Credibility Rating uses a maturity perspective and looks at a wider area of risks, leadership engagement, strategic direction, past trends of achievement vs. goals, activities & achievements towards continuous improvement, service level sustainability, reliability of services, customer satisfaction, maturity of risk management etc. Credibility Ratings are a boon to both the Customer and IT Service provider. The Customer benefits by able to choose a IT Services Provider easily & fast, with almost no investment on any resources or time, through a objective, independent/TBQ Approach, (thus minimizing gage reproducibility & repeatability errors), configurable, extendable, reusable and easy to use. The model has a holistic view and integrates financial analysis and strategic evaluation with multiple quality models - ISO, SW-CMM, SA-CMM, PCMM etc. The model has been conceptually accepted by CRISIL, but yet to finish the hands-on trial runs at its first rating site. Results so far have been encouraging. Since this is an ongoing research, further extensions/features are possible. Examples include - automation, webbification, building knowledge based rules based on findings from data mining on previous ratings, building a best practices consultancy base etc. We estimate the immediate, current year market potential for this model at approximately 200+ rating assignments