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Workday’s Big Data Play: A Step in the Right Direction

Posted by Ben Weiss on Fri, Sep 20, 2013

Big Data will soon be integrated into Workday's solutions, extending its reach into corporations everywhere.

workday logo largeWorkday is catapulting itself onto the Big Data scene, and those in the enterprise technology business are taking notice. One of Silicon Valley’s biggest success stories of late, Workday strives to make financial, human capital, and Big Data management easier and more approachable for the everyday business user. Workday has caught the attention of Forbes, The New York Times, and other media outlets with the launch of Big Data Analytics and with its expanding cloud alliance with Salesforce.com. Both announcements indicate a significant shift in the marketplace from early adopters to the more mainstream enterprise user.

Aside from its recent Big Data push, Workday is especially top-of-mind for us here at Opera Solutions because we recently deployed its full Human Capital Management and Financial suite. That said, we’re genuinely impressed with these latest developments. Here are three power plays from Workday’s latest newsmakers: 

1. The Power of Data Linking. The first step in turning raw Big Data into value is to link many and varied data sources together in a way that allows users to glean new insights. Workday’s approach will link together its own HCM and Financial data with other internal data environments, such as those provided by SAP. With any luck, Workday will also eventually incorporate data flows from external sources, including social media. But even with the current data sources, users will gain new visibility on employee sentiment, customer service–driven feedback, and other helpful insight and be able to see the larger opportunities in analytics.

Take, for example, an employee-by-employee profitability analysis. This would traditionally involve a tremendous amount of manual labor by the business intelligence or analytics teams in collecting and analyzing the data — and would result in an extremely thick report produced for management eyes that was immediately dated, inflexible, and not actionable. Today, Workday Big Data Analytics can serve this analysis up within the standard Workday interface. It’s not prescriptive enough for our tastes — it still requires the user to search for the metric, make sense of it, and decide on the course of action to take — but it’s far better than the old “throw bodies at the problem” approach and substantially more approachable for typical business users.

2. The Power of the Cloud. Workday’s offering clearly demonstrates how rapidly and simply analytics can be deployed in an enterprise these days. Workday’s Big Data Analytics will join the other Workday platform offerings in the cloud, enabling companies to switch on analytics without any real IT effort. This is a far cry from the old BI solutions that required months or years of implementation to get off the ground.

3. The Power of Man + Machine. Workday’s solution is based on the underlying design principles that also guide our solution development, namely, that Analytics must be purpose-driven, understandable, and easy to use by a non-technical end user. For Big Data Analytics to truly be effective, users need to be able to dive deeper into the underlying reasoning and meaning behind this analysis and do so in an environment that encourages exploration and greater understanding. This design principle can be spotted across Workday’s HCM and Financial applications, where the UI is designed to be simple, intuitive, and encouraging of customer exploration. 

What’s Missing

While Workday’s Big Data Analytics is a great starting point for companies looking for deeper insights on their employees and business, the platform has plenty of room to grow. We’d like to see the following enhancements:

Predictive Outcomes. The current solution is largely delivering historical observations and insights from Big Data environments — basically a Business Intelligence 2.0 solution that looks at historical performance, not future performance. It could go so much further.

For example, while it will be great to see each sales reps’ performance and profitability in the last quarter, it would be even better if the platform could also predict which sales reps are likely to be unprofitable or require specific guidance in the coming quarters. The same can be said of employee attrition analysis. It’s great to understand which employees left and why after the fact, but it would be better to predict which employees are fading and which actions are likely to keep them with the company.

Directed Actions. Workday made its interface for delivering reports and visualizations in a fairly straightforward manner, but the platform still requires the user to generate the report and identify the appropriate action based on the report to get the benefit. In other words, insights are easier to arrive at, but people must still do the “arriving,” which leaves a lot of room for error and less-than-optimal decisions. We hope that the next iteration of the application allows the machine to create and serve up directed actions to remedy a specific situation. For example, Workday could provide a machine-generated list of recommended actions that an underperforming sales rep can take to improve performance.

Needless to say, this is a particularly exciting development in our space, and we welcome Workday and its customers to the Big Data Analytics party. As the platform expands, we hope to be part of its partner ecosystem, developing sophisticated predictive analytics solutions for the growing Workday customer base.

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Ben Weiss is a director in the Office of the Chairman at Opera Solutions.

 

Topics: Big Data