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There is Data Gold in Those SaaS Hills
Satish k. Palvai
Co-Founder and MD-Xactly Corporation
Tuesday, October 20, 2015
In 1848, the Gold Rush took California by storm. More than 300,000 people made their way to the state for a piece of the action, and in search of that little nugget that could change their fortune. One hundred and sixty-seven years later, we are about to hit another gold rush - this time, the currency is in data.

Conventional wisdom may indicate that the data ship has already sailed, waiving a huge flag that reads BIG DATA. And I wouldn't disagree. But we are sitting on the cusp of another data goldmine, this time, it's led by Software as a Service (SaaS) companies.

Here's why...
The Rise of Data Monetization

While the origins of SaaS data go back several decades, it was roughly 15 years ago when SaaS as a term first appeared in an article by the Software and Information Industry Association entitled "Strategic Backgrounder: Software-as-a-Service (SaaS)." Since then, SaaS and cloud computing have completely revolutionized the IT industry. While the initial goal was to ease the cost and complexity of IT deployments and updates, as SaaS companies continue to mature, the secondary benefits have become far-reaching.

For starters, many SaaS companies are now sitting on 5-10+ years of data. And instead of being isolated in on-premise silos as it was in the past, this data resides centrally in one location. What does this mean? The information can now be aggregated and anonymously analyzed to find data gold.

Not only does this open a whole new stream of opportunities (not to mention revenue) for SaaS companies - a term some experts are calling data monetization - it also holds the answers to critical business questions that will help customers run their organizations more effectively and efficiently than ever. In most instances, this kind of data has only been available anecdotally, being collected through mechanisms such as surveys. This real-time data that addresses specific factions of business has never been accessible until now. All this being said, why should you care?

SaaS Data - The Key to Employee Engagement and Cultural Change?

For starters, this data holds the keys to helping unlock companies' most critical (and costly) asset-people. Businesses are at a crossroads when it comes to managing employees and inspiring them to reach their full potential while also maintaining a high level of satisfaction. To put it more bluntly, we are in the midst of a motivation famine: A recent Gallup poll shows that businesses collectively lose $550 billion a year because 70 percent of the workforce is disengaged.

One major area where I predict we will see SaaS data gain prominence in the coming years is around people and performance management. With technology rapidly changing and an influx of millennial employees (by 2020, 50 percent of the workplace will consist of millennials), we must reinvent the way we work; and that starts by better understanding it - through data.

While recent articles have warned of the potential perils of data-driven employee management, I believe the benefits far outweigh the risks. In 2005, I cofounded a SaaS company, Xactly, with Christopher Cabrera. Our core business revolves around helping companies create and align incentive programs that inspire better performance. While we started in sales departments, we have seen variable incentives move to nearly every sector and function within companies - from truck drivers to receptionists. In the past year we began to analyze the multiple terabytes of information that has been accumulating in our SaaS systems for the last decade. We are talking about billions of incentive transactions each month and more than $16 billion in incentive compensation payments made in just the last two years.

What we were able to find analyzing this data was astonishing. For example, 79 percent of SaaS sales representatives miss their quota - but why? One correlation is that companies are making incentives too complicated with too many targets that can confuse and de-focus employees (hint: three is a good target number). We could also see when sales reps typically leave businesses and how the mix of base pay and variable compensation impacted rep performance and retention. This is all based on real-world data, with real sales reps - not theory or survey data. By considering these factors and countless more, customers were able to create a quota and pay mix that not only better engages reps, but drives them to reach their full potential.

Getting outside our business, the potential for this kind of SaaS data is tremendous. For example, SaaS Healthcare IT companies will have the potential to see elements such as patterns where common health issues occur. This is all critical data to helping understand and create a healthier and happier society.

In fact, one of the most pertinent pieces of data we found was less about operational efficiencies, and more about the need for cultural awareness and change. In reviewing the data, we discovered that women in sales were being paid less money, but performing better than their male counterparts. Curious, we looked at the analysis internally and found that this was happening right under our own roof as well. While we were quick to rectify this problem, it made one thing glaringly clear-big data holds the answers, but we have to be willing to ask the hard questions. Recently, we have seen companies like Salesforce take a similar hard look at their own big data to address gender pay and equality in the workplace.

No matter how you look at it, you can't deny that adding SaaS information to the big data phenomenon is a valuable proposition. And it's one I think will continue to help us rethink and reimagine how we engage our workforce and do business in the coming years. So grab a pan and start mining that SaaS data gold.
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