In a 2016 Oliver Wyman/SIG benchmarking study about data quality, 60% of the organizations surveyed self-reported that they were bad at managing small data. Contributing factors to this issue included mergers and acquisitions or decentralized structures, which inhibit data transparency and prevent companies from using levers like data bundling to improve purchasing output. Using case studies, we will demonstrate a reliable way to produce clear, accurate and dependable data as a basis for making strategic decisions, and will specifically explain the algorithms and rules-based approach (with no fuzzy logic) to clean more than 99% of data.

• Why most organizations struggle in small data quality
• About potential solutions for producing reliable and clean data
• Why it is more important to clean “Small Data” before tackling the issue of “Big Data”

 

Contributors: SynerTrade
Categories: 2017 Fall - Carlsbad, Summit Presentations
SRC Type: Benchmarking and Analysis, Disruptive Digitization, Procurement Operations