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Workday analytics recommends your next career move

Phil Wainewright Profile picture for user pwainewright November 4, 2014
Workday unveiled machine analytics that makes career recommendations and identifies potential leavers at its Rising annual conference in San Francisco today

Predicting expense deviations

Workday wowed customers at its annual Rising conference today in San Francisco with a slew of new features slated for the next release of its financials and HCM applications, most notably the unveiling of Insight Applications, which use smart analytics to proactively recommend specific choices.

Rather than simply reporting on or visualizing data, the new analytics tools apply data science and machine intelligence to produce predictive insights and recommendations for specific business scenarios. They will run within Workday's HCM and financials applications without any need for separate data warehousing and will include mobile functionality. Three are initially planned for HCM and three for financials:

  • Retention risk — analyzing which of an organization's top performing employees are most at risk of leaving and recommending actions most likely to retain them.
  • Career path recommendations — match candidates to the career moves that will be the best fit.
  • Workforce scorecards — make recommendations for improving workforce performance against key metrics.
  • Employee expense deviations — proactively identifying travel and entertainment expense policy abuse
  • Customer collections — identifying potential late payments or defaults and recommending actions to minimize losses
  • Financial score cards — make recommendations for improving financial performance against key metrics.

Data classification engine

The new analytics tools build on technologies from last this year's acquisition of Identified. The data science startup had set out to develop an executive search tool by building a data classification engine called SYMAN. Speaking in today's keynote, its co-founder Adeyemi Ajao, now Workday's VP of technology strategy, explained:

From an engineering perspective, to get analytics right you have to solve three distinct problems: you have to get the data, you have to classify it, and you have to apply the right algorithms.

It's data classification that really constitutes the key of the problem.

For example, aiming to build a model to place people in nursing jobs, the team analyzed a billion healthcare recruitment profiles and discovered hundreds of different job titles for the role of 'nurse'.

There are 600 correct ways of saying I'm a registered nurse. I spent three months with the team going through every single profile.

The result of this work was a definition tree for the healthcare industry built within SYMAN that allows it to automatically classify each of those 600 terms into around 17 distinct roles. The classification can then be used to run searches or perform analytics to make recommendations.

Mobile UI refresh

Ajao revealed today that the team has now completed entire industry trees not only for healthcare, but also for technology and education, and has a further 17 industries in progress done, including consumer packaged goods, financial services, government and healthcare. That work forms the basis for the applications for retention risk and career path recommendations. For example, recruitment recommendations can be based on analysis of the company's own history of how other recruits have performed, matched to prospective candidates' profile information.

Other crowd-pleasing additions announced today for Workday 25 current and future versions of Workday include:

  • A new mobile interface, the second refresh this year, which adds a 'flat' design in the style of Apple's iOS 8 update. A preview is available immediately for iOS devices and customers will be given several months to get used to the new design before it is rolled out as the default.
  • Improvements to the desktop UI (also included in the new mobile interface) including new scrolling org charts, dashboards and notifications.
  • A fully mobile expense report creation and submission process.
  • Full project management functionality targeting the professional services automation market.
  • Inventory management.

My take

Having grown large enough to graduate to occupy both north and south wings of San Francisco's Moscone Center this year, Rising needed some fireworks and the combination of a new generation of predictive analytics with the refresh to the mobile UI seemed to do the trick.

Workday has had analytics built into its applications for some time, and more recently added big data capabilities, but this new technology advances the game substantially. Dan Beck, VP of technology products, suggested that guiding a business based solely on historic analytics was equivalent to using a paper map to find your way in your car — we now routinely use connected route-mapping tools that help us avoid traffic snarl-ups as they happen, so we should apply the same logic to mapping business decisions.

Of course the algorithms have to be reliable and planning someone's career is a tad more mission-critical than finding your way to a new restaurant. But advances in machine intelligence — much of it driven by work done at consumer Internet giants such as Netflix, LinkedIn and Facebook (where many of Identified's data scientists previously worked) — are now fueling a new wave of machine intelligence in the business applications space.

Workday has thrown down a challenge with today's announcements, especially to SAP which is also starting to promote machine intelligence tools running on its HANA platform. Infor has also highlighted data science as a key area of product development. Clearly, a new front is opening up in the feature battles between enterprise application vendors.

Updated 1pm November 5th to correct several small factual errors where indicated.

Disclosure: Workday, SAP and Infor are all diginomica premier partners.

Image credit: Workday

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