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Customer Experience and Trust Rely on Building IT Systems That Scale
Solving for scale is the key to ensuring IT delivers on its responsibility to create trust-enhancing customer experiences.
February 23, 2023
5 Min Read
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Adopting hybrid or public clouds remains IT’s go-to means of achieving scale. While this transformation has improved price performance and advanced tech-driven business capabilities, including faster and deeper data insights, it hasn’t always engendered greater customer trust.
That’s due in no small part to widely publicized hacks that have exposed personally identifiable information (PII), as well as to increased customer dependence upon mobile commerce, inconsistent inventory systems, and unreliable online ordering. By some measures, performing at scale is all about improving transactions per second.
According to a 2022 PwC study, “87% of business executives think consumers have a high level of trust in their business. But only 30% of consumers say they do.”* One of the biggest threats to trust is a data breach, according to the study. Significantly, 91% of consumers say that if businesses gain their trust, they will likely buy products or services from them.
Building customer trust in IT systems requires more than scaling capacity in storage and processing. It also requires generating timely insights from structured and unstructured data to improve uptime and help prevent trust-destroying incidents.
IT Scale and Trust Depend on Analytics and Insights
In many companies, the problems that undermine customer trust begin with a lack of real-time visibility and access to the flow of operational data. Operational teams need to assess what’s happening across the business, but they can’t when there’s a lack of shared telemetry or data access. Data security and performance issues become exacerbated when companies attempt to scale their services to reach a more significant number of customers.
“When scaling up a cloud-based system for hundreds of millions of users, I have to make sure one user doesn’t impact the performance of another user,” explains Abhishek Das, founder of Acante, a data security company. He believes that security teams need visibility into every service and must examine the telemetry to identify where problems are happening and how to resolve them.
The lack of operational insight is a chronic problem for security operations teams (SecOps), which rely upon real-time, unfettered access to operational data to assess threats and prevent or at least investigate intrusions. And the reverse is also true: IT operations teams are under pressure to be more security-conscious and understand the implications of new code or technologies from a security perspective. Das believes a security operations center (SOC) team needs to apply machine learning and an observability tool to correlate and take the proper action.
How do you increase your operational resilience? Learn how to make use of your data in real time.
Seeing Value in Real-Time Insights
The playbook for deepening customer trust starts with mining operational and environmental telemetry for real-time performance insights and cybersecurity analysis. “You must look at structured and unstructured data sources, retrieve data quicker, and correlate them together,” said Das.
Here’s how three companies approached and solved customer trust challenges by improving observability and scaling operational insights:
Optimizing customer experiences and preventing downtime are crucial objectives of WePay, an online payment service provider owned by JPMorgan & Chase. The company found that entering all available logging and telemetry data in a search-powered solution could reduce the time to identify the customer impact during incidents by 90%. WePay’s security team also taps the streaming data to protect the business against external threats and satisfy all compliance regulations.
The quest for greater insights led Albert Heijn Technology (AH Tech), a European supermarket brand with more than 1,000 stores, to try observability for harvesting a vast amount of data from its distributed IT infrastructure and 13,000 points of sale. The company has seen a 40% decrease in end-user IT incidents and raised store sales by 10% while reducing product shortages.
Increasing speed, monitoring, and scalability are priorities for Auchan, which previously relied on on-prem infrastructure to manage data but faced problems given how quickly its operations were growing. By using a search-powered solution to enable its teams to observe data in a clean dashboard and choose which information to capture and analyze, Auchan is able to process — and actually observe — the roughly five million data flows that move through its database daily.
Increasingly, companies are turning to search-powered solutions to tame and analyze their data — from cybersecurity to applications to customer interactions and transactions.
Learn how to analyze your data in real time to improve your customers’ experiences.
*Trust: the new currency for business, 2022. PwC. www.pwc.com.
About the Authors:
Lou Celi is the CEO of ThoughtLab, a company that produces evidence-based market research and thought leadership that draws on the latest analytical tools and research methods to understand the impact of technology on business and government. Lou has nearly 40 years of experience as a corporate leader, author, speaker, entrepreneur, and consultant. He has led a broad range of research initiatives on the digital transformation of companies, industries, and cities.
Janet Lewis is executive editor, finance and innovation, with ThoughtLab. She is an expert writer and editor with 30 years of experience in researching and synthesizing complex business and financial concepts. At ThoughtLab, she has worked on many survey-based projects, contributing to survey development, interviews, analysis, presentation of results, and writing e-books and white papers.
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