5 big digital transformation trends in 2023
The threat of a recession coupled with the ongoing need for transformation and growth means CIOs must make force multiplying investments in 2023. Here are five strategies.
CIOs and IT leaders should consider inflation's impacts, a potential recession and continued supply chain risks when evaluating their 2023 digital transformation strategies and priorities. These trends suggest that IT leaders should dial up programs that will drive cost savings, efficiencies and risk reduction in their 2023 transformation priorities.
On the other hand, slowing down work around customer experience, innovations and emerging technologies can lead to disruption. Even businesses in industries lagging in technology investments, like construction, manufacturing, healthcare, government and higher ed, should accelerate customer and growth-centric digital transformation initiatives.
Most importantly, recent layoffs in the tech sector may create cultural challenges if employees fear for their jobs or doubt the financial stability of their employers. CIOs and IT leaders must find ways for employees to feel safe about their employment status and should consider increasing time and investments applied to employee learning and experimentation.
The upshot? CIOs must identify force-multiplying investments targeting multiple outcomes. Here are some to consider.
1. Iteratively improve employment experiences and define the future of work
Employees have experienced remote and hybrid work over the last few years, and IT leaders should use 2023 to improve employee experiences iteratively. Tactics include using employee surveys to capture employee satisfaction about the technologies they use daily. IT Operations should also deploy digital experience monitoring solutions to help identify network performance and other end-user issues.
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Ultimate guide to digital transformation for enterprise leaders
But forward-looking IT leaders will also define a vision for the future of work in their organizations. With more opportunities to automate tasks, a future of work vision points to how employees will use technology to improve operations and deliver new products, services and innovations.
One trend to consider is improving knowledge sharing and reducing the risks associated with tribal knowledge. IT leaders should upgrade collaboration tools, information portals, content management systems and AI search technologies to help share knowledge between company experts and new hires. Search platforms are force multipliers because centralizing access to unstructured data can improve employee experiences and reduce costs, especially for large enterprises that can consolidate multiple search indexing technologies.
2. Deliver more machine learning to production with MLOps and ModelOps
While many organizations invest in machine learning experiments, surveys show that enterprises struggle to deploy machine learning models to production, monitor their effectiveness and support ongoing model improvements. For example, in the "State of ModelOps 2022" report, 51% of respondents have done early stage pilots or experiments but have yet to put them into production.
That statistic is troubling going into 2023, where many business executives, feeling a financial crunch, may tighten investments in experimental data science areas that aren't producing results. The same report indicates that 86% of C-suites are demanding answers about their AI investments' ROI, but 48% of data science organizations struggle to provide them.
MLOps and ModelOps are two practices and technologies that can help organizations address the gaps in bringing models to production and demonstrating financial returns. MLOps, the DevOps for machine learning, aims to simplify model development and deployment, while ModelOps provides model cataloging, governance and production monitoring. IT and data science teams seeking to expand their machine learning investments should consider these platforms to reduce the time, cost and complexities of delivering and supporting machine learning models in production.
3. Plan for the metaverse, digital twins and sustainable infrastructure
When I look at the horizons of technology innovations, I put emerging tech in three buckets.
- Emerging technologies that are ripe for early adopter experimentation. I put metaverse experiences in this category because the technology's experience and scalabilities remain a work in progress. Big B2C brands may experiment to learn the tech and see where to create early wins.
- Digital twins are my example of a hyped but very promising technology, especially for industrial, manufacturing and construction companies. Large companies in these industries should seek opportunities where digital twins can improve on-the-job learning, reduce operational safety risks and plan changes to their commercial offerings.
- Many public companies have announced environmental, social and governance (ESG) objectives. Reducing energy consumption is one goal that every business should prioritize, and CIOs should include sustainability goals in their digital transformation objectives. Options include transitioning off power-hungry data center infrastructure, automating shutting down cloud resources when not used, installing visual power management systems and considering renewable energy options to power their facilities.
4. Embrace AIOps to support multi-cloud and microservices
Digital and technology organizations must also address the growing landscape and complexities in managing hybrid clouds, multi-cloud architectures and microservices. Many CIOs investing in digital transformation are adding new applications and growing data volumes faster than they can sunset legacy systems. And these apps, integrations and data lakes are more mission-critical, so businesses expect high service-level objectives and increased automation from IT Ops supporting these technologies.
Enter AIOps technologies that aim to help IT Ops leverage machine learning around all their monitoring tools and observability data. These technologies aggregate the data, use machine learning to correlate alerts and help network operations centers (NOCs) identify root causes faster. Most of these technologies also connect with IT service management, collaboration and other automation tools to trigger communications and scripted responses. They also help NOCs develop a single pane of glass around their applications and databases running in public clouds, data centers and edge computing.
5. Develop transformation leaders and agile self-organizing standards
In my new book, Digital Trailblazer, I suggest that CIOs, IT leaders and innovators must guide their organizations out of crisis mode into digital transformation initiatives that evolve the business model. In the book, I state, "You will always be transforming, and your organization must establish transformational practices as essential core competencies."
The biggest trend in 2023 will belong to the CIOs who develop strong leadership and development programs for their aspiring digital transformation leaders, or what I call digital trailblazers. CIOs can quell the fears of their high-potential employees who fear layoffs and a poor economy by empowering them to lead agile, innovative and experimental transformation initiatives. One way CIOs can do this is by encouraging transformation leaders to define self-organizing standards, a continuous process of evolving an agile way of working that fits the organization's goals and culture.
I am certain that 2023 will bring a new wave of surprises, disruptions and technological innovations. IT leaders that seek force multipliers will be stronger at handling the year's ups and downs.
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