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Machine learning will have bigger impact than cloud
Workday’s vice-chairman explains how machine learning can help employees become more effective, and hints at the company’s moves beyond finance and HR software
machine learning (ML) will have a bigger impact on business than cloud computing, enabling organisations to improve the way they manage their finances and talent, according to Workday’s vice-chairman Mike Stankey.
Pointing to the new ML capabilities of Workday’s cloud-based HR and finance applications that were unveiled recently, Stankey said a manager, for example, can automatically receive recommendations on how they can adjust their budgets to achieve better outcomes
Such recommendations are not based on a review of a single budget or one company’s budget, but instead the anonymised data of thousands of Workday customers and tens of millions of employees.
“It’s also a smarter system,” he said. “You didn’t have to ask for it because the algorithm knew you had a budgeting task in your calendar and made budgeting suggestions to help you be more effective.”
On the HR front, Stankey said Workday’s ML algorithms will help to identify an employee’s skills gap and suggest training courses. “It can also suggest mentors based on employees’ background, their hometown, the school they went to, and even career aspirations,” he added.
Asked if the rate at which new features are being rolled out by Workday may be outpacing an enterprise’s ability to take advantage of them, Stankey stressed that its customers do not have act on anything to benefit from ML.
“We’re not making people do anything – we’re giving them more value in their day. That’s how I think machine learning is going to be adopted more effectively, rather than having them dig through a system to get answers.”
Mike Stankey, Workday
Workday is not the only supplier that is baking ML into finance and HR applications. Enterprise software giants Oracle and SAP are touting similar capabilities, but Stankey claimed that Workday has an edge over those rivals by running a single instance of its software for close to 40 million users.
“Think about how much data that is – we can, with our customers consent, run ML algorithms against that large base of data and deliver more intelligent recommendations and results,” he said.
To help businesses understand the basis of Workday’s recommendations amid calls for explainable AI, Stankey said ML algorithms are catalogued and have objectives tied to them.
“It will also tell you what datasets are used, broadly, and if there are data scientists who want to dig deeper into the algorithms, we can expose those to them so there’s nothing hidden,” said Stankey.
Read more about business applications in APAC
- A majority of large enterprises in Australia, New Zealand, Hong Kong and Singapore are planning to move their financial applications to the cloud within a year.
- SAP now counts companies such as China’s Ameco Beijing as clients, and it is also going all out to address hitches that stand in the way of wider adoption of its S/4 Hana software.
- APL Logistics has moved its transport management system and other business applications to the cloud, while keeping its ‘secret sauce’ on-premise.
- A frozen yogurt chain in Singapore has consolidated its payroll data into a single database powered by Unit4’s HR management system.
Asked if Workday would extend its reach into areas such as Supply chain management, Stankey said there remains a large, untapped, addressable market for finance and HR software in Asia, Europe and even in North America, giving it plenty of room to grow.
“We aren’t currently looking at developing operational applications like supply chain management or manufacturing, but people should keep asking because at some point there might be a different answer.”
Indeed, in a sign of things to come, Workday said earlier this week that it plans to acquire Scout RFP, a cloud-based procurement platform, for about $540m in an all-cash deal.
Workday CEO and co-founder Aneel Bhusri said the deal will enable the company to “deliver a modern source-to-pay solution that accelerates our momentum in the spend management market”.