The CIO Point of View ASIA PACIFIC The New Agenda for Transformative Leadership: Reimagine Business for Machine Learning
Global Overview Machine learning has arrived in the enterprise, and companies are eager to reap the competitive benefits the technology can provide. From automating processes that enable faster business operations to applying algorithms that improve accuracy, CIOs are adapting the technology for a wide variety of uses and transforming the way we work. To investigate the rise of machine learning, we worked with Oxford Economics to conduct a survey of 500 CIOs in 11 countries on three continents and across 25 industries and conducted in-depth interviews with leaders in the field. We found that CIOs are increasing their investment in machine learning but must overcome several barriers to achieve their productivity, revenue, and innovation goals. Unless CIOs turn their attention to updating not just technology but talent and business processes, the full value of machine learning cannot be realized. Key Insights CIOs we surveyed in the Asia Pacific region (46 in Australia, 45 in New Zealand, and 46 in Singapore) are more likely than their peers in other regions to view decision automation as important to the success of their organization. However, they are just beginning to prepare for this future. CIOs from Australia, New Zealand, and Singapore are enthusiastic about the potential for machine learning to improve business performance. Yet most respondents are still in the early stages of adoption and lag CIOs in Europe and North America in adjusting their organizations to optimize the technology. For example, few have created new job descriptions that focus on work with intelligent machines or altered business processes to maximize the value of automated decision-making (e.g., developed risk policies for machine-made errors). Making complex decisions Q: Which capabilities of machine learning are most important to the success of your organization over the next three years? Making complex decisions response shown. 2 servicenow.com
Australia: A Leader In Machine Learning Adoption Australia stands out as a leader over New Zealand and Singapore. CIOs in Australia have made more headway in changing business processes to better benefit from machine learning, and likely as a result also expect more value from machine-made decisions over the next few years. For example, 57% of CIOs in Australia say they are making organizational changes to accommodate machine learning compared with 36% in New Zealand and 50% in Singapore. This leadership position is open to challengers. Tech in Asia reported that Singapore has committed to spending more than $100 million to be a force in machine learning over the next five years an investment intended to drive innovation. Already, Singapore is leading on redefining job descriptions to focus on work with machines (52% in Singapore vs. 27% in New Zealand and 43% in Australia) and developing methods for monitoring mistakes made by machines (57% in Singapore vs. 24% in New Zealand and 48% in Australia). Machine learning maturity in Asia Pacific Q: To what extent do you agree with the following statements about your role? Agree and strongly agree responses combined are shown here. Australia New Zealand Singapore Machine learning is a strategic focus for me 40% 54% 74% We are making changes to our IT structure to accomodate machine learning 65% 47% 50% We are using machine learning in some or all parts of the business 59% 49% 32% servicenow.com 3
Point of View CIOs Are Adopting Machine Learning to Advance Digital Transformation Companies in Asia Pacific recognize the potential value of machine learning and have begun to build it into their plans. Roughly 90% of CIOs in the region, on par with peers worldwide, have adopted or plan to adopt the technology. Machine learning is increasingly central to digital strategies. More than half (56%) of CIOs across Australia, New Zealand, and Singapore say machine learning is a strategic focus for them compared with 65% in North America and 51% in Europe. However, investment in the technology in Asia Pacific is slightly behind global totals: 31% of CIOs in these countries say their companies are making some investments today compared with 35% in Europe and 43% in North America; 60% say they will be investing within three years compared with 72% in North America and 64% in Europe. Australia is ahead of its peers in Singapore and New Zealand in this area: 43% of CIOs in Australia are making some investments vs. 28% in Singapore and 22% in New Zealand. 4 90 % of CIOs in Australia, New Zealand, and Singapore have adopted or are planning to adopt machine learning. servicenow.com
CIOs Expect Machine Learning to Drive Business Value Despite lower investment levels, CIOs in Asia Pacific see machine learning as an important driver of business value. They are more likely than others to say the ability of machine learning to make complex decisions will be important to the success of their organization (60% vs. 53% in Europe and 51% in North America). In addition, CIOs in the region value machine learning s potential to improve the accuracy of decisions and increase the speed of decision-making. In fact, Australia leads all the countries surveyed in their expectations for decision automation to improve the speed of business, with 93% of CIOs in Australia expecting significant value versus 87% in the US and 81%, on average, in Europe. Together, these outcomes could have a transformative effect on business performance. The advancement of decision automation would free up time for employees to do more strategic work. For example, at Australia Post, machine learning has enabled the development of a financial tool that helps customers manage their bills, giving them a full view into and control over their financial obligations while also reducing the burden for employees. CIOs expect substantial value from machine learning Q: To what extent do you expect decision automation to deliver value in the following areas over the next three years? Substantial value and transformative value responses combined are shown here. Accuracy of decisions Speed of decisions Top-line growth Competitiveness servicenow.com 5
Machine Learning Demands New Jobs and Processes Successfully automating tasks and decisions requires more than just the right technology. It requires talent and updated business processes as well. Leadership must train employees to work with machines and change their job descriptions to accommodate necessary skill sets. These new skill sets are diverse, involving disciplines such as engineering, data science, math, critical thinking, and problem-solving. Yet most CIOs surveyed in Asia Pacific are behind their peers in Europe and North America in preparing the broader organization for this way of working, which will require new approaches to workflows, talent, IT management, and risk management. In fact, CIOs in these countries are the least likely to say they have recruited employees with new skill sets compared with CIOs from other regions (21% vs. 29% in Europe and 30% in North America). They are also more likely than their peers to cite outdated processes as a barrier to the adoption of machine learning (53% vs. 46% in both Europe and North America). 21 % of CIOs in Australia, New Zealand, and Singapore have recruited employees with new skill sets. Top challenges to machine learning adoption Q: To what extent do the following factors interfere with the adoption and maturation of automated decisions at your organization? A substantial barrier and a complete roadblock responses combined are shown here. Australia New Zealand Singapore 80% 65% 78% 70% 57% 61% 61% 40% 38% 54% 20% 9% 37% 35% 27% Insufficient data quality Outdated processes Lack of budget for new skills Lack of budget for new technology Lack of skills to manage and maintain smart machines 6 servicenow.com
It is clear, though, that CIOs across the region and beyond understand the importance of making these changes and are aiming for rapid progress: 91% of respondents in Australia, New Zealand, and Singapore have begun to rethink business processes for machine learning (compared with 96% in North America and 94% in Europe). Failure to amend business processes could threaten the promise of machine learning and make it more difficult for companies to compete with their peers in North America and Europe. (Our Global CIO Point of View includes recommendations on first steps to take.) CIOs making changes for machine learning Q: Which changes, if any, has your organization made? Respondents were asked to select all that apply. Redefined job descriptions to focus on work with machines Developed a roadmap for future process changes Developed policies for ensuring the accuracy of data Addressed the legal risk of mistakes made by machines in risk policies servicenow.com 7
Conclusion Getting value from machine learning investments will require substantial planning and disciplined follow-through all while adjusting to rapid, ongoing changes in technology. As CIOs embark on the machine learning journey, they should take the following five steps to maximize their investments. 1. Build the foundation and improve data quality. Consolidating redundant, legacy, on-premises IT tools into a single data model is a good first step. 2. Prioritize based on value realization. Focus on those services that are most commonly used, as automating these services will deliver the greatest business benefits. 3. Build an exceptional customer experience. When creating a road map to implement machine learning capabilities, imagine the ideal customer experience and prioritize investment against those goals. 4. Attract new skills and double down on culture. CIOs must identify the roles of the future and anticipate how employees will engage with machines and start hiring and training in advance. 5. Measure and report. CIOs must set expectations, develop success metrics prior to implementation, and build a sound business case in order to acquire and maintain the requisite funding. (Read more in The Global CIO Point of View.) CIOs in the countries we surveyed in Asia Pacific are among the most ambitious in the world for the potential they see in machine learning delivering value to the enterprise. While they lag global peers in their level of investment and in preparing their organizations for change, they appear on track for success. To realize full value from machine learning, they will need to continue to expand focus beyond the technology to processes, workflows, and culture. First Mover Advantage We isolated a group of respondents we call them first movers who are ahead of their peers in spending on machine learning, automating business processes, making organizational changes to support digital work, and updating business processes and talent strategy (see our Global Point of View for a full breakdown of the criteria). Their plans and actions provide a useful guide for CIOs to advance machine learning in their companies. Companies are just beginning to adopt this technology, but some are further ahead than others: 10% of global CIOs and 9% of CIOs in Australia, New Zealand, and Singapore qualify as leaders in our analysis. First movers demonstrate leadership in a number of areas: They are concentrating on innovation (70% vs. 54% of others), and say automating routine processes (50% vs. 33%) and digitizing business processes (46% vs. 27%) will be important to their organization s success over the next three years. Download the Global CIO Point of View: servicenow.com/cio Technology leaders in Australia are more advanced than those in Singapore and New Zealand today, but given the growing confidence in the technology, this landscape is ripe for change. 8 servicenow.com