Singapore CIOs list barriers to machine learning adoption

Source: ServiceNow blog.

ServiceNow has found that machine learning is on the rise in the enterprise, with Singaporean respondents lagging behind their peers in the other countries* studied in The Global CIO Point of View survey.

The company has defined machine learning as software that promises to analyse and improve its own performance without direct human intervention, giving it the ability to make increasingly complex decisions as it learns. Artificial intelligence (AI) is an outcome of machine learning.

The report surveyed 500 CIOs from around the world, almost 10% from Singapore, to uncover the competitive benefits of adopting machine learning and hear how those leaders are accommodating digital labour - work done by machines that is carried out in concert with humans or as a replacement for human efforts, including creating new jobs that focus on work with intelligent machines.

According to IDC**, spending on AI and machine learning is expected to grow rapidly, from less than US$8 billion in 2016 to US$47 billion by 2020. "Everybody we talked to are thinking about it and thinking about how they can implement machine learning to help their business," Duncan Egan, VP Marketing, APJ, ServiceNow said.

A third (32%) of CIOs in Singapore surveyed said that their organisation are using machine learning in some or all parts of their business, compared to counterparts in Australia (59%) and New Zealand (49%). Three key areas that were identified as barriers in the adoption and maturation of automated decision making in their organisation:

· Seven in 10 CIOs in Singapore cite outdated processes and insufficient data quality (65%) as a substantial barrier to adoption.

· A third (35%) added that there is a lack of skills to manage and maintain smart machines, plus no budget for acquiring new skills (61%).

· Almost 40% of respondents in Singapore felt that there is a lack of budget allocated for new technology in their organisation.

“Machine learning allows enterprises to digitise in ways that were never before possible, but its adoption is an evolution that requires careful consideration and planning,” said Egan. “To realise the full potential of machine learning technology, CIOs need to elevate their role to (that of a) transformational leader who influences how our organisations design business processes, organise data, and hire and train talent.”

Egan said machine learning can be used by companies of just about any size. "The target is any enterprise out there that wants to automate and is inefficient," he said. "There is a global realisation that we cannot keep (adding) more people to solve more problems."

More than half (52%) of CIOs in Singapore surveyed agree that machine learning can make complex decisions that are imperative to the success of their organisation, with 54% respondents citing machine learning as a strategic corporate focus. Enthusiasm for this technology is driven by widely-held confidence by CIOs that greater automation through machine learning will increase the accuracy (80%) and speed of decisions (87%).

Machine learning software also promises to analyse and improve its own performance without direct human intervention, giving it the ability to make increasingly complex decisions as it learns:

· Nearly nine in 10 (87%) of Singapore CIOs cite profitability growth and top-line growth as the area that would benefit the most from decision automation over the next three years.

· Almost six in 10 (59%) said that product development and research are automated to an extent but still requires substantial human intervention. A further four in 10 (41%) CIOs expect decision automation brought about by machine learning to allow more room for developing new products and services for the organisation.

· Three quarters (76%) said that routine decision making takes up a meaningful amount of employee and executive time especially in departments like finance and human resources (HR, 57%). CIOs in Singapore expect decision automation to contribute to their organisation’s employee productivity by 41%, and talent recruitment and retention by 35%.

“There are three kinds of decisions that are particularly suited for automation—anything that needs routing, ranking, or forecasting, such as the assignment of IT tickets or sales lead routing,” said Egan. “The outcome of faster and more accurate decisions lies in creating an exceptional internal and external customer experience. That means thinking not in terms of individual interactions with customers, but the entire customer journey from beginning to end.”

The survey also found that nearly a third (28%) of CIOs in Singapore are making investments in machine learning today, and this number is expected to grow as Singapore gears towards becoming a Smart Nation. Half of CIOs in Singapore say that they are making organised changes to processes or leadership to prepare their organisation for machine learning adoption.

According to ServiceNow, successful machine learning is not just about adopting the right technology – organisations must train employees to work with machines and redefine their job scope to accommodate the necessary skill sets, which are diverse across multiple disciplines from engineering to data science, critical thinking to problem solving. Organisations in Singapore have shown that they are willing to make such changes in order to make rapid progress with machine learning:

· Seventeen percent of CIOs in Singapore have already set plans for workforce size and role changes within their organisation.

· More than half of CIOs in Singapore (52%) have begun to redefine job descriptions to include a focus on work involving intelligent machines – which is well ahead of Asia-Pacific peers in Australia (43%) and New Zealand (27%). These are not just engineer or data scientist positions, but finding the right kind of talent, such as project managers, Egan said.

· Almost 40% of respondents said that they have developed a roadmap for future process change.

Source: ServiceNow infographic. What CIOs plan to use machine learning for. Seven in 10 (68%) said they would automate repetitive tasks, the top choice.

ServiceNow also recommended how CIOs can jump start their journey to digital transformation with machine learning:

- Build the foundation and improve data quality. One of the top barriers to machine learning adoption is the quality of data. If machines make decisions based on poor data, the results will not provide value and could increase risk. CIOs must utilise technologies that will simplify data maintenance and the transition to machine learning. "Many organisations we work with come from a very siloed approach," Egan explained.

- Prioritise based on value realisation. When building a roadmap, focus on services that are most commonly used, as automating these services will deliver the greatest business benefits. At a high level, look for tasks where many unstructured work patterns can benefit from automation. Commit to re-engineering services and processes as part of this transformation, rather than lifting and shifting current processes into a new model.

- Build a better customer experience. A core benefit of increasing the speed and accuracy of decision-making lies in creating an exceptional internal and external customer experience. When creating a roadmap to implement machine learning capabilities, imagine the ideal customer experience and prioritise investment against those goals.

- 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. CIOs must build a culture that embraces a new working model and skills. That means establishing guidelines for executives, engineers, and frontline workers about their work with machines and the future of human-machine collaboration.

"Just because you have have a great technology doesn't mean it'll work in your organisation," Egan explained. Barriers to adoption can include employees who fear that their jobs are being taken away, and companies have to redirect them to more high-value and stimulating work, he said.


- Measure and report. The benefits of machine learning may be clear to CIOs, but other C-level executives and corporate boards often need to be educated on its value. 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. CIOs should also consider building automated benchmarks against peers in their industry and other companies that are of similar size.

Egan also disclosed that the next release of the Now platform will include machine learning, and that Servicenow is already experiencing the Now on Now value realisation internally.

Agent Intelligence will be the first machine-learning solution, to be available in the next release, codenamed Kingston. Agent Intelligence will initially be applied to improving the speed and quality of IT and customer-service processes. Agent Intelligence machine-learning capabilities accurately categorise requests nearly instantly, eliminating the bottleneck created by agents having to manually triage, categorise and route requests (incidents/ cases).

Agent Intelligence also classifies and routes requests with fewer errors, increasing agent productivity.
The pilot programme for Agent Intelligence revealed that, on average, customers can expect to save 8% of their service desk’s time through improved categorisation, prioritisation and assignment of incidents.

“Of the incidents categorsed by ServiceNow Agent Intelligence, we can expect a 97% to 99% incident-assignment accuracy,” said a senior IT manager at a major retailer.

When ServiceNow’s Now on Now programme put Agent Intelligence through its paces the customer service team found that Agent Intelligence was 95% as accurate as humans are in categorising incidents. As the team handles more than 13,000 incidents a month, it saved more than 315 hours in two months of using the new technology and has seen both productivity improvements and a rise in customer satisfaction.

Explore:

Read the Global CIO Point of View report to find out more about ServiceNow's recommendations (PDF)

Watch the video introducing the Global CIO Point of View report

View the complete infographic (PDF) and the interactive data visualisation 

*ServiceNow commissioned Oxford Economics to survey 500 CIOs about machine learning and automated decision-making. Asia Pacific respondents came from Australia, with other countries of origin being Austria, France, Germany, the Netherlands, Sweden, the UK and the US, representing a range of B2B and B2C sectors. The survey was administered via computer-assisted telephone interviews (CATI).

**IDC, Worldwide Semiannual Cognitive/Artificial Intelligence Systems Spending Guide, October 2016.