The evidence bears this out: in a study conducted by BMC and 451 Research about how businesses characterize their progress in their evolution to an Autonomous Digital Enterprise (ADE), overwhelmingly, the number-one tech priority for the majority of the more than 1,200 companies surveyed was to become a data-driven business. These businesses are striving to use artificial intelligence (AI) and analytics to extract and monetize valuable data from both traditional and new sources like the Internet of Things (IoT) devices, social media, and customer engagement systems. And these companies are putting money behind their motives: worldwide spending on AI solutions is expected to reach over $342B in 2021, and spending on big data and business analytics (BDA) solutions is forecast to reach $215.7B, an increase of 10 percent over 2020.

Data is also driving tremendous advances in the public sector; for example, India’s Smart Cities Initiative is harnessing data and digital technology to help address the most pressing issues in infrastructure development, creating opportunities to make sustainable and inclusive decisions that improve the quality of life.

So where does all this data come from? The better question is, where doesn’t it come from? With trillions of data points gathered from consumer activity and enterprise systems, mobile devices, IoT/connected devices, social shares, science and engineering, and so much more, virtually everything is a data source, and the numbers only continue to expand. In fact, a recent report on the data and information created, captured, copied, and consumed worldwide shows that data volume in 2020 reached an all-time high at 64 zettabytes, and by 2025, that volume is estimated to almost triple to 181 zettabytes!

But how can organizations today capitalize on this explosion of data in their efforts to evolve to an ADE? Luckily our knowledge and abilities around proper data collection, storage, processing, and analytics are also expanding and improving, fueled by rapidly evolving AI and machine learning (ML) capabilities. Data and analytics transformation projects are built on solid approaches like compelling business use cases, foundational and innovative architectures for value generation, updated organizational structures and shared-service capabilities, and an enterprise-wide culture of embedding data and analytics in organizational processes and behaviors.

Yet even with all that planning, the majority of data and analytics transformations aren’t viewed as successful, with most companies only analyzing a small percentage of the data they own, and the majority failing even to deploy to production.

The reasons for these failures are many and complicated. Here is a snapshot of the most common stumbling blocks:

• Rising, expanding, and novel data sources generated by complex business models are difficult to simplify and extrapolate
• Existing data management processes and practices don’t work well with newer technologies
• Failed collaboration and/or inadequate business involvement
• Insufficient investment for robust data analytics programs
• Scarce talent pool or inadequate/incomplete staffing
• Inability to operationalize at scale to meet stakeholder expectations
• Too much focus on new tech versus value delivery and organizational readiness
• Incomplete or unclear approach to defining milestones and success

We know now how much data we are generating, and we understand the necessity of operationalizing that data for both public and private interests, allowing us to drive the kinds of business outcomes that improve lives and ensure a competitive edge, as well as the stamina to withstand ongoing disruption. So how can we ensure that we’ve prepared our organizations, our tools and processes, and our data adequately to make our data and analytics transformations successful? At BMC, we believe the answer is DataOps, a framework that we define as the application of agile engineering and DevOps best practices to the field of data management. With DataOps tools and culture shifts, businesses can rapidly turn new insights into fully operationalized production deliverables that unlock business value from data.

We recently shared more about our DataOps model and solutions at this year’s BMC Exchange, our annual IT and business event where we explore the tools and technology that are helping businesses successfully navigate the digital age. This year, we focused on the power of data and how businesses can more effectively use their data to speed their evolution to an Autonomous Digital Enterprise. All session content, including this Day 1 keynote and a great conversation from Day 2 with Daymond John, noted entrepreneur and business mentor, is free to stream on-demand once you’ve registered. We hope you will join the thousands of other participants who have benefited from this year’s solution-focused content and register today.

Outside of your people, your data is arguably your organization’s most valuable asset. Take every opportunity to learn more about the best ways to invest in and capitalize on your data for organizational success. Please enjoy the free and valuable content at BMC Exchange 2021, and let us know if we can help your business operationalize your data!

1 IDC Press Release, IDC Forecasts Companies to Spend Almost $342 Billion on AI Solutions in 2021, August 2021. https://www.idc.com/getdoc.jsp?containerId=prUS48127321

2 IDC Semiannual Big Data and Analytics Spending Guide, H2 20205

3 https://www.statista.com/statistics/871513/worldwide-data-created/

4 https://www.businesswire.com/news/home/20200106005280/en/NewVantage-Partners-Releases-2020-Big-Data-and-AI-Executive-Survey

5 https://www.sigmacomputing.com/blog/top-20-big-data-statistics/

6 https://www.datanami.com/2020/10/01/most-data-science-projects-fail-but-yours-doesnt-have-to/

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First, we’re already seeing more and more organizations bring in internal IT teams, utilize software-as-a-service (SaaS) platforms, and roll out self-service models to reduce the dependencies on external, outsourced, and siloed IT resources. Next, IT organizations are now more critically involved in helping other areas of the business meet the need to provide similar self-service capabilities that IT has successfully deployed to their customers.

As these two interdependent entities begin to realize the benefits of collaboration through merged and coordinated tools and processes, there’s never been a better time than today to start adopting enterprise service management (ESM) across the organization.

Business Benefits of ESM

IT service management (ITSM) tools have advanced considerably in response to the demanding, diverse needs of the modern enterprise. ESM broadens the scope of these evolving ITSM tools beyond IT and across the organization into other areas of the business—like human resources (HR), finance, marketing, and facilities—to improve performance, deliver a transcendent customer experience, increase employee engagement, and strengthen business outcomes.

By extending and enhancing the functionality, traceability, and reproducibility of ITSM to other lines of business with ESM, organizations can yield significant business benefits beyond greater efficiencies and cost savings. For example, if businesses want to thrive in the future and survive any seismic changes, they will need to evolve into an autonomous digital enterprise that embraces intelligent, tech-enabled systems across every facet of the organization. ESM helps make rapid innovation achievable within this ecosystem.

Not only that, as we experience generational and cultural shifts that change how we consume technology, applying ITSM principles enterprise-wide can help address the very pressing needs and expectations of internal customers—the employees—and external customers. Replacing unstructured, mundane work with modern, automation-based alternatives through ESM enables personalized, responsive service that creates happy customers and frees up employees to focus on business-critical tasks.

Along this journey from basic automation to automation with deliberate human intervention to a fully autonomous solution, the level of intelligence increases, so it’s fair to characterize that progression as a path of intelligent automation. By using the power of artificial intelligence (AI) and applying methods and algorithms that can learn and adapt from the right set of data, intelligent automation is made real in solutions like ESM.

Now that we’ve uncovered the business benefits of ESM, let’s dive further into how to implement strategies for successful ESM adoption.

Strategies for Success

Establishing SaaS-based, enterprise-wide, multi-device-compatible service management functions is necessary to adopt processes that drive digital transformation. It’s also helpful in reducing the complexity that may have resulted from hastily scaling ITSM solutions as the world shifted to remote work.

Choosing the right ESM solution can be discouraging and confusing, especially as most tools on the market are simply far-reaching ITSM tools designed for specific use cases. In order to plan wisely and ensure ESM success, consider the following:

• Follow the tried-and-true guiding principles of ITSM derived from the ITIL 4® framework.
  • But don’t apply ITIL blindly outside of IT; understand what is valuable to stakeholders so that the transition to ESM truly benefits them.
  • Carefully assess the organization in order to determine what to improve or to replicate.
  • Progress iteratively in small achievable steps.
  • Avoid silos by including the right people throughout the process and by being transparent with sharing actionable data and open to constructive feedback.
• Look for flexibility and functionality but be cautious of tool sprawl.
  • Ensure the ESM solution you choose is flexible enough to deliver the specific functionality for your intended use cases across the organization.
  • Be careful not to create a bespoke ESM experience using a selection of unintegrated ITSM tools, which may lead to more complexity and cost inefficiency.
  • Provide a seamless experience to customers across the organization on devices and channels of their choice.
• Ready the organization for change.
  • Get senior-level buy-in and create adoption initiatives and training to ensure that the decision to implement an enterprise-wide solution does not come as a surprise.
  • Communicate the change before crossing the finish line.
  • Collaborate with others and work to deliver a solution that employees will want – and want to use.
• Think long-term when developing a plan for ESM. Longer-term benefits of a more cohesive approach will help ensure better organizational maturity and expansive business benefits. After all, change can be costly and daunting for stakeholders so it’s essential to get it right to not just for today’s business demands, but also future technological and cultural disruptions.

When done correctly, ESM solutions help organizations create, manage, and analyze data that improves business performance and delivers insights on growth, competitiveness, and efficiency—while also empowering users with service-oriented experiences delivered by simple, familiar, and fast user interfaces. Now that business and IT alignment is no longer a goal but a requirement for digital competitiveness, it’s time to adopt the very processes that drive digital transformation, beginning with enterprise service management.

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