Innovation Embracing Change Through Innovation Ram Chakravarti Forbes Councils Member Forbes Technology Council COUNCIL POST Expertise from Forbes Councils members, operated under license. Opinions expressed are those of the author. | Membership (fee-based) Sep 7, 2022, 07:45am EDT | Share to Facebook Share to Twitter Share to Linkedin Ram Chakravarti is the chief technology officer for BMC . getty Nearly everywhere you look in the enterprise, IT architectures are shifting. From the data center to the cloud to the edge to the Internet of Things (IoT) devices and sensors coming online, compute is moving closer to end-users. But these accelerated changes are more than just shifts in architectures, tools and technology. They are changes in the ways business gets done. A host of statistics reinforce the enormous change that is coming to the IT industry. According to Ziff Davis’ 2021 State of IT report, 76% of businesses plan long-term IT changes. IDC estimates that investment in edge computing power will grow much faster than core computing power over the next five years, and worldwide spending on edge computing servers will account for 24. 9% of total servers by 2025. GSMA estimates that the global IoT market will be worth more than $1. 1 trillion in revenue by 2025. These changes will disrupt business models in nearly every sector. Organizations that embrace change with an innovation mindset will be uniquely positioned to leverage actionable insights from their networks and tools, becoming more agile and, ultimately, better able to serve their customers. The Coming Transformation To understand where we’re going, it’s important to understand where we are now. In the current enterprise, businesses use and deploy various applications, storing the data in business-specific data silos. The applications, tooling and data pipelines are typically managed by specific business units for their own purposes (which can be admittedly narrow). When data is reported to executives, it is generated according to the specific needs of the business unit leaders and their KPIs. MORE FOR YOU Google Issues Warning For 2 Billion Chrome Users Forget The MacBook Pro, Apple Has Bigger Plans Google Discounts Pixel 6, Nest & Pixel Buds In Limited-Time Sale Event Some relatively advanced organizations are already on their way to transformation. Rather than using siloed data operations, they rely on large, enterprise-wide data lakes to yield insights from across the organization. The future of enterprise networks takes these processes and super-sizes them. The generated data from IoT and operational technology (OT) systems are dwarfing the traditional data found in enterprise data centers, driving data orchestration and automation expansion. One forecast from IDC highlights the volume of data expected to be available: 41. 6 billion IoT devices in 2025, capable of generating 79. 4 zettabytes (ZB) of data. With more sources of information and more sensors, data volumes will increase exponentially. This, in turn, will require AI and machine learning capabilities across the organization to operationalize the data. IoT devices will enable AI at the network edge, accelerating predictive analytics. Extensive technology-enabled automation will also become even more pervasive, leading to “hyperautomation,” or the continuous integration of automation into business operations—or, in other words, more machines doing more things. In short, the future will continue to bring automation everywhere, even to the development of new tools and solutions, and intelligence-driven data mining, management and monetization will establish competitive differentiation across all industries. Modernizing For Agility So how can IT departments (and the organizations that love them) prepare for this future? Here are a few steps that they can take. 1. Optimize data pipelines to enable cross-functional collaboration. Lines of business and different departments often operate independently of each other, with each using its own technology stack, some with legacy assets and applications that don’t play well with one another. According to research done by Matillion, companies have an average of 400 data sources , and 20% of businesses have more than 1,000. The data that these assets and lines of business generate need to flow into large data lakes where they can be leveraged across the organization. 2. Automate everything you can. Automation reduces the reliance on manual, repetitive tasks and frees up valuable resources—people especially—for high-value work. Document workflows across the organization and look for ways that repetitive tasks can be automated. Start by singling out small clusters, and work your way up. 3. Transition from research to operationalization. Over the past five years, companies have built impressive data science teams to extract value from their data. But many are focused on research. As demand for data-centric projects increases, they’ll need to shift their emphasis toward creating robust, repeatable and supportable solutions. These initiatives can help companies manage a rapidly changing future, one in which business models, customer demographics and even competitors evolve rapidly. Tech Spending And The Future Technology spending has increasingly moved out of the IT domain and into the broader realm of business decision-makers as innovation initiatives, market competitiveness and other business drivers influence technology strategy. Along with this trend, we can already see non-technical staff using platforms and toolkits that were once the domain of the IT team. We can and should embrace these changes as much as possible because they are already in motion and are here to stay. They empower all of us to do higher-value work, to be more creative and innovative and to focus on value creation rather than maintenance of back-end systems. Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify? Follow me on Twitter or LinkedIn . Check out my website . Ram Chakravarti Editorial Standards Print Reprints & Permissions.