The anatomy and viability of any organization is shaped and defined by multiple internal and external variables. Some such as sales, manufacturing, marketing, supply chain and procurement to name a few are internal. The external include the company's target consumer base response to its products/services, geopolitical situations, the global financial markets and even sometimes, unforeseen natural phenomenon. In all these variables, there is a transactional string that pulls at each and dictates the company's net revenue.
Taking marketing as a simplified example, a company has a dedicated marketing team focused on influencing its target customer base to purchase its products/service. Marketing, in return, is given a spend budget which is allocated among various suppliers and service providers to ensure effective initiatives towards the target customer.
Leading organizations recognize that burrowing down to influencers of external, as well as internal, transactions across their enterprise equates to insights and processes that result in sustainable marketplace competitiveness. The concept seems rather simple, but multiple facets must be taken into consideration and they must be strategic in nature. More importantly, access to sanitized, real-time data and ability to properly utilize it to interpret, predict, simulate and optimize business processes and functions is critical. A.T. Kearney Procurement & Analytic Solutions is developing a solution called Computational Commerce™ to help clients holistically address this very need.
A.T. Kearney's Computational Commerce™ methodology leverages cutting-edge advanced analytics methods to help clients develop capabilities to optimize and effectively implement business strategies across key business functions, as well as positively influence the bottom line. Data is leverage as a competitive differentiator on a new, exciting and innovative scale. Computational Commerce™ examines the transactional influencers/drivers of a company business function(s)/process, identifies critical gaps, and provides an optimal means to address them.
Coming soon: Case Study and Thought Piece on Computational Commerce™