Merriam-Webster’s online dictionary defines trust as “assured reliance on the character, ability, strength, or truth of someone or something.” Digging deeper, trust is an emotion backed by beliefs and experiences accumulated over time. Iterative positive validation builds trust in someone or something.
Efficient technology lifecycle management hinges on equal trust of people and things. Co-workers, vendors, partners, users, and customers (people) must trust that commitments will be met, and problems solved. Technology management professionals must trust that the software and systems (things) used to manage the technology lifecycle will perform as expected. Users across the business must trust that the network, equipment, and software provided (more things) will be available and reliable when needed. One more thing…source data produced by people and systems must be trusted.
Trust in data can accelerate or stymie technology lifecycle management performance. When trust is high, productivity is high and management by the numbers is frictionless and efficient. When trust is low, focus shifts from executing the management strategy to questioning everything. Productivity plummets as professionals divert focus to analyzing datasets and correcting errors.
While periodic audits of systems and processes is a best practice to validate confidence (trust) in data, reliance on triage audits as the primary mechanism to repair lost trust in data diverts production resources and hinders optimal performance. As such, dedicated focus on validating data sets through programmatic quality assurance and quality control practices before data accuracy is questioned increases trust and fuels technology lifecycle management performance.