Why observability can break through top challenges to digital transformation
Monitoring, machine learning, and visualizations are a game changer for telling the story of systems across your organization
Digital transformation will account for more than half of IT investment by 2024, but there are persistent blockers to success, says IDC: these include lack of organizational confidence, silos, and C-suite leadership.
These challenges have plagued technology decision makers who have hopeful visions for the future. While it may be obvious that these blockers can be surmounted by good communication and collaboration, that’s easier said than done. In fact, for the better part of a decade, McKinsey keeps finding that 7 out of 10 transformations — digital or otherwise — just plain fail.
But, could some of the technologies that hold the promise of business transformation be incrementally applied to pave the path for its success? The capabilities of observability solutions may provide a hint.
Incident visibility to shore up confidence — and communicate effectively
“The problem is that, too often, business departments simply do not trust their IT counterparts,” writes Thomas C. Redman in MIT Sloan Management Review.
What are some ways to change this view? How can trust be generated?
Ahold Delhaize, one of the world’s largest food retail groups, offers an instructive example. AH Tech provides the technology for its Albert Heijn, Etos, and Gall & Gall brands, which generate a huge amount of data from IT infrastructure, 13,000 points of sale, and across its supply chain.
When AH Tech adopted an observability platform, it was able to track individual items throughout the retail order fulfillment journey — from where an item is stored, when it needs to be sent to a supermarket, its stock, when it was sold, and even its real-time price.
That means the IT team knew about incidents before an employee could report it, or a store might provide an unreliable experience. And, the team could be sure to delegate resolution to the right people or address the issue directly.
The observability solution also enabled the team to visualize and communicate what they do better. They could build a dashboard fast that was able to integrate business and operational data — connecting the dots.
With the distributed nature of modern applications and petabytes of data generated daily, observability can empower IT teams to better communicate the value of technology for the business — from the risks avoided to the revenue potential.
Visualizing the entire enterprise — crashing down silos
A picture is worth a thousand words. And in the enterprise, any way to tell a story fast unlocks opportunities to build confidence and trust.
What’s particularly effective about observability technology is it can dashboard and visualize data from across applications, cloud or on-premise storage, and beyond. In other words, it makes silos irrelevant. Good observability solutions connect business and operational data — a missing piece in most organizations.
For example, imagine visiting France as a tourist and purchasing a train ticket to travel from Paris to Provence. Oui.sncf would likely be your point of purchase. However, the fast growth of the site led to the creation of multiple silos that slowed the customer experience and threatened revenue. They installed an observability platform that enabled departments to connect all operational data with a view of ticket revenue, time to purchase a ticket, and even abandoned carts, which could then be analyzed by region. They could respond to events in real-time, with dashboard capabilities that made trouble-shooting easier–reducing incident resolution from several hours to just several minutes.
Building C-suite support by delivering insights and a clear story
Oui.sncf did something else that could be helpful to other organizations. The team constructed a giant wall of computer screens covered in color-coded dashboards. It’s a single pane of glass of second-to-second health of the business.
“[If] all indicators are green, all is well. If we see that the curves are starting to drift, we head to our workstations to open up interactive tables that will help us check for problems,” said Dominique Debruyne, who was head of the Big Data arm at Oui.sncf. Teams could build on those capabilities to create further trend analysis and anomaly detection, which could support better C-level decision making.