Top-performing organizations extract incremental values from various business processes. A combination of small incremental gains results in a significant change that benefits multiple departments across the organization. For example, incremental improvements in the supply chain result in better costs while also improving customer satisfaction with faster delivery. This results in more customers coming back for repeat business, thus delivering better sales. However, it must be emphasized that data initiatives need continuous effort from the various stakeholders responsible for the business performance. It is a company culture where every employee gets access to data relevant to his/her job. Every employee understands that decisions or opinions need to be backed by data and the "gut-feel."
When data is harmonized and analyzed descriptively, organizations should start investing in the ultimate prize of achieving higher automation levels via AI and machine learning. AI and machine learning open doors to opportunities that offer unprecedented efficiency gains, e.g., autonomous driving. Organizations must do a self-assessment of data maturity, without which all such initiatives are bound to fail. AI/Machine Learning techniques provide exceptional value provided the training data sets are pristine. Such models need periodic adjustments to account for various data drag.
Data is the rocket fuel that leapfrogs businesses ahead of the competition. Investments in data infrastructure, analysis capabilities, and data-driven decision-making culture are vital to keeping a competitive edge.