Editor’s note: K. V. Rao is the CEO of enterprise company Aviso.
Enterprise software has been a critical tool to help companies organize data and automate painfully manual processes. And unfortunately little else. To call enterprise software “dumb” might be slightly unfair, but as “smart” devices begin to proliferate, it’s time we all accept that today’s software that we use to run our businesses is painfully ill-equipped for the future.
Software Needs to Change
Think about it. We collect and manage vast stores of data for what purpose? Business intelligence didn’t make our companies more intelligent. ERP didn’t help us plan much of anything. And while CRM may have helped sales manage customer data, it didn’t help them hit their targets — and let us be honest, it really did not move the (revenue) needle!
In 2002, CRM’s weaknesses were exposed by Tom Siebel, one of its founding proponents. While Siebel maintained then that its own CRM system allowed it to “see around corners” to anticipate swings in demand, just eight months later his company suffered a massive revenue miss and admitted, “We don’t really have a thorough analysis of the pipeline here with us today.” It is disappointing that 12 years later, despite massive investments, not much has changed in value delivered by enterprise software.
The good news is that is changing. With consumer companies like Netflix, Amazon and Google demonstrating the power of big data, software companies and startups are finally embracing data science and machine learning to introduce predictive and prescriptive software capabilities to the enterprise. For example:
- Marc Benioff of Salesforce.com acknowledges the power of smart devices, and his company recently acquired RelateIQ to add data science and machine learning to enhance how sales teams collaborate.
- Workday recently acquired Identified to use data science to help recruiters find great candidates.
The potential is now real to help companies make better decisions, move faster in dynamic markets, and manage risk in the face of great uncertainty.
Take the revenue growth challenge. With predictive and prescriptive software plugged into CRM data, C-level executives will be able to clearly understand probable outcomes of a given month, quarter and year; the risks that need to be accounted and managed for; and run scenarios to understand the trade-offs of different decisions.
For example, what’s the impact of discounting a large deal right now? Which sales reps should get which deals to generate the best results? Looking out over the next three quarters, how is the business likely to perform? What are the biggest risks? And what would be the impact of trade-offs around pricing, investments in new hires, and new product offerings for our forward guidance to the board and investors?
And We Need to Change
Moneyball’s Billy Beane recently wrote in the WSJ that the newest, advanced technology is “transforming the social fabric of sport” and “the game is just beginning.” The same holds true for the enterprise. We all need to realize that it’s a whole new ballgame. And just like the insular, glacial world of baseball, this new age of software is a tectonic shift in the enterprise that makes a lot of people very uncomfortable. For our enterprises to succeed in this new world, we need more than just shiny new software. We must change long-held cultural, political biases about “how we do things here.”
In making critical decisions, enterprises too often rely on perceived rather than rigorously analyzed historical patterns. They let competing entities argue their positions, too often giving power to the loudest voice in the room. And when all else fails, they let their emotions lead the way, making gut decisions that too often are biased and error-prone.
Like CRM in 2002 or 2014, this is the state of the art, and it’s far from good enough. It might cut it today but not much longer. To paraphrase the infamous line in Moneyball, enterprises that don’t retool their organizations around the power of data science and machine learning are going to be dinosaurs within a few years.
But getting your organization rallied around implementing this philosophy can be challenging. It is easy to say that ideas outweigh automation, and that we would all prefer to apply more brainpower to our problems since we already have sufficient brawn in place. Like the software companies I mentioned earlier, many people instantly recognize the game-changing power of this new age of software and the new ideas they can help unleash. However, many more prefer to lean on what they know and what they are comfortable with.
Think about it this way: There are lots of ways to calculate ROI on CRM. What’s the ROI of better revenue decisions? If this question scares the hell out of you, rethink your career path. If this question energizes you, then you have a long, bright future ahead.