Artificial intelligence Part 2: Deriving business principles
Conclusion: While the current artificial intelligence (AI) initiatives are data-driven, there are instances whereby the current data is insufficient to predict the future. For example, answering the following questions might be challenging if the available data is only of a historical nature irrelevant for forecasting purposes:
- Q1: What will be the effect on sales if the price is increased by 10 % as of the next quarter?
- Q2: What would have happened to sales had we increased the price by 10 % six months ago?
The purpose of this note is to provide a framework that can be used to derive sales principles to answer the above questions. The same approach can be used to derive other business processes principles such as procurement, customer service and client complaints tracking.
About The Advisor
Dr. Wissam Raffoul is an IBRS advisor who specialises in transforming IT groups into service organisations, with particular expertise in IT Service Management (ITSM), process optimisation, outsourcing and Cloud strategies, enterprise systems management solutions and business-centric IT strategies. Prior to joining IBRS in August 2013, he was General Manager strategic consulting in Dimension Data advising clients on applying technology to improve business performance. Prior to joining Dimension Data, he was a Vice President in Gartner/META Group and issued various research publications covering service delivery processes, centre-of-excellence models, managing outsourcing vendors, benchmarks, maturity models, IT procurement evolution and supply/demand models. In previous positions, he headed HP ITSM consulting Practice in Australia. He also acted as an infrastructure manager, reporting to the CIO at a number of large organisations in government and in the financial and petrochemical industries.