With more and more data available to analyze, organizations are realizing the value that sophisticated analyses using artificial intelligence and machine learning (AI/ML) can provide. The benefits of these analyses are significant: our Dynamic Insights research on machine learning finds that organizations most often benefit through competitive advantage, but also improved customer experiences, increased sales, the ability to respond quickly to opportunities in the market, and lower costs. However, the need for specialized skills to deploy AI/ML models can stall data science initiatives. An organization’s efforts to scale data science and apply models are often complicated by a lack of self-service access to infrastructure, tools and data.
Business improvement stems from technology investments that advance automation and apply intelligence to your work and processes, increasing the potential achievement of desired outcomes. Assessing vendors and utilizing technology for optimization and innovation is the foundation for digital transformation, and our chief research officer asserts that by 2025, over one-half of organizations will determine that the chaos of digital technology usage requires a rationalization of vendors to ensure operational excellence.
The virtualization of business and the evolution of digital transformation to applications and systems that operate in cloud computing — or the “as-a-service” environment — has fragmented enterprise and data architectures. The role of cloud computing has become a utility to provide elastic resources in support of operational needs. For example, data in the cloud requirements are provided by third-party vendors, managing security and storage of data outside the organization.
The artificial intelligence industry is unique in that it has evolved to the point of making dramatic impacts across other markets. AI is used to help businesses scale, improve customer experiences, decrease waste and streamline cumbersome tasks. Ventana Research sees the need for AI innovation for the future of technology and the many other industries it influences, but making such tools available to everyone at fairly low costs can be difficult. It is no surprise that nearly two-thirds (62%) of organizations report using machine learning today, and nearly three-quarters (72%) of organizations participating in our research say they plan to increase ML use.
Performance management helps organizations understand, optimize and align performance through a variety of methods and processes and is an essential part of what is called digital business. For many organizations, engaging employees through a series of check-ups, goal tracking and kudos to encourage and motivate them helps ensure that expected people and operational performance is realized. But in a changing world and workplace culture where workers prioritize mental health and organizations view working from home as a positive change, vendors of performance management applications must provide tools that help leadership adapt.
Robotic process automation has developed into a significant part of the enterprise software and low- to no-code development approach in the past few years. Organizations utilize the software primarily to automate predictable, rule-based, repetitive tasks, but the use is now expanding into more intelligent automation. Ventana Research sees the need for further innovation within the RPA market to better help organizations accelerate operational agility and efficiency by automating significant processes using digital workforces. More advanced technologies also have the capability to use artificial intelligence and machine learning tools to better serve workers.
For disruptive technology companies, maturity is often accompanied by the realization that customer retention and expansion are as important as a new logo acquisition. Arriving at this realization is one thing; reorienting your organization to it is another. The necessity of aligning revenue-generating functions in business-to-business technology has been common knowledge for quite some time. Still, organizations have only recently begun to implement dedicated, centralized revenue functions.
Business continuity — especially during a pandemic, natural disaster, cyber event or geopolitical situation — requires business and risk mitigation processes. Unfortunately, few organizations are prepared to respond appropriately. Whether an organization rises to the challenge or descends into survival mode is determined by the way it meets the expectations of the workforce, customers, stakeholders and potentially shareholders.
When you think about it, events are at the very core of computing, right down to the simplest if-then operation in a spreadsheet. Each event leads to a set of choices, often binary, which then become events in themselves. As computing has become more ubiquitous and has developed into the architecture upon which all business and commerce runs, the events themselves have become more consequential and more numerous. There’s still an event, and each "if" still leads to a "then," but now we evaluate at enterprise scale.