There’s an inherent truth that many are missing when it comes to enterprise transformation: data plays a central role in tackling business challenges. Take, for example, the case study of a transportation association my company has been working with for the better part of a decade.
The relationship started when Maven Wave migrated the entire organization to Google Workspace. A couple of years later, they came to us when they started their cloud journey, and together, we moved five disparate data sources into one central cloud repository. Then, they started running machine learning (ML) & artificial intelligence (AI) to curate a 360-degree view of their customer. From there, we worked together to build out a ride-sharing capability and an automated roadside assistance intelligence platform, using Google Maps and AI.
Today, that organization is able to predict where motorists will break down and better position service vehicles to help their customers quicker and more efficiently. The journey started with a straightforward cloud migration to a company-wide collaboration tool, and today, the team stays ahead of the competition because they’re using company data to better serve customers.
That’s exactly what all enterprises need to do to survive.
Throughout the pandemic, digital transformation trends that were expected to take a decade were adopted in a matter of weeks. The tactical view of shifting workloads to the cloud or gathering big data is no longer enough; instead, enterprises get ahead by leveraging carefully curated data to solve business challenges and put the customer first.
Here are five 2022 data trends driving business (and digital) transformation - and by extension, five ways enterprises can set themselves apart with a world-class data strategy.
#1: Cloud Migration Opens Up More Data Possibilities
Data and the cloud only work well as a pair. Trying to develop a modern data analytics strategy for an enterprise simply doesn’t align with legacy on-premises data centers and disparate data streams. On the flip side, the cloud has drastically transformed the way enterprises receive and act on data.
Regardless of vertical, organizations are looking for a single source of truth to access and consume their data. The cloud is the only vehicle for maximizing the true value of data to derive actionable insights across the organization. As enterprises have turned to the public cloud during the pandemic faster than ever expected, they’re now positioned to better use their data. Any enterprise that doesn’t have a strong public cloud presence would do well to re-evaluate that strategy in early 2022.
#2: Real ML & AI Applications
For the past two years, I’ve seen many customers employing brilliant data scientists in completing pilot projects to determine whether ML / AI would be valuable for their business. The overwhelming answer has been: yes. Now, the conversation has shifted to, “How do I operationalize ML / AI?”
Companies are digging into the details of how to add new data, keep models up-to-date as fresh data streams come in, and ensure from organizational and change management perspectives that the project is a success.
#3: Adopting a Ubiquitous Cloud Mindset
For years, we’ve been discussing public, private, hybrid, and multi-cloud — not to mention edge computing. Heading into 2022, the current state of affairs is that most enterprises will keep some workloads on-premise and leverage more than one public cloud. Likewise, they’ll build out edge capabilities and mine a lot more data at the edge that has never been accessible before.
So the world’s biggest enterprises are building data management strategies that take into account vast, ongoing shifts in data best practices, and all signs point to a ubiquitous cloud in our future to organize and streamline those efforts. The top prediction in IDC’s “Top 10 Predictions for the Future of Digital Infrastructure” states “leaders will prioritize business objectives over infrastructure choice.”
In the future, it won’t matter to the customer where a workload lives, but whether it’s being run in the most efficient manner with the lowest latency appropriate for the use case - and that the team can easily access data to mine it for value. A single pane of all IT environments, with the ability to quickly move workloads around and scale as needed, is the future.
#4: Industry Alignment Deepens
Across verticals, a depth of industry experience has never been more critical. Data is the powerhouse allowing for deeper industry expertise than ever before. For instance, in healthcare, data allows nurses and doctors to provide better bedside care and deliver better outcomes with near-real-time information based upon streaming IT insights.
#5: Sovereignty and Security in Spades
This one functions alongside the ultimate “trend,” which is to put the customer at the center of all data decisions. Though Europe may be the impetus for the data sovereignty discussion, the conversation has rippled throughout the world. A growing percentage of all RFPs have sovereign data rules and regulations at the heart of them - and that’s only going to continue growing. So, to compete in the global market means to keep data sovereignty and security top of mind. According to IDC, “by 2025, regional divergences in data privacy, security, and placement/use/disclosure mandates will force 80% of enterprises to restructure their data governance processes built on an autonomic foundation.”
In closing, I’ll return where we started: enterprise case studies illustrating data in action. During the heat of the pandemic, we launched the first and most innovative workforce development program of its kind, ensuring Rhode Islanders receive the skills they need to secure well-paying jobs across growing industries. For a large theme park, ride censors and data analysis prevent two catastrophic failures per month, saving millions of dollars for the organization and keeping customers happy. We’ve helped one retail giant speed up a pricing model from 10 hours to 8 minutes. A new program is tracking opioid overdose data in Texas to guide future interventions and get resources where they’re needed most.
All of these case studies have one truth in common: organizations making the most impact in their industries are mining their data for business transformation opportunities.
