article | February 24, 2016
3 Tips to Conquer Big Data
SBI recently spoke with Chris Lonnett, the Vice President of Sales Operations at Motorola. The topic of conversation was building a data plan. Too often sales ops teams struggle to derive meaningful insights from their data. Maybe it’s because the data is dirty, or because they don’t know what to look for. But since we live in the era of big data, sales ops leaders are being tasked with using data planning to outsell and out-market the competition. They have to get it right.
So, how does Chris do this at Motorola? During our conversation, he uncovered 3 keys to his success.
“We really started taking a more mature approach towards data planning here in the past couple of years,” explained Chris. What was their method? It was all about simplifying their approach. At Motorola he got down to the basics and answered these questions:
They were able to frame their data architecture around the answers to these questions. Before this simplification, Chris found that they had a lot of data. But also had the inability to extract the value or correlations that were needed. Simplifying solved this issue.
Producing basic, yet useful data allows them to be more efficient and effective. They make sure to use the data to run the business. This creates an added benefit. It allows the gaps in data to be easily identified and remedied each and every day.
A common problem faced by sales ops leader is dirty data. How has Chris overcome this challenge? He starts with the arduous task of cleaning up the data. He uses data enrichment firms, and data stewards to do so. Then, at Motorola they have put processes in place so that once the data is clean, it stays that way.
Again, the key according to Chris is operationalizing the data. If you create data and insights, but it’s never used, you’ll have no idea whether it’s clean. When you focus on the data that matters, and put it into everyday operations you will gain insight into the state of your data. Focus on the foundations. Ask the questions one way, and have a standard way of answering. At Motorola, they have clean data because they only ask their sales team to answer twenty questions. Twenty important, well thought-out questions, not just a series of random questions.
Technology is vital to sales ops leaders’ success. What sales technology stack does Chris use to support both sales and sales ops? At Motorola, their CRM is the center piece of their stack. It’s where they really want their sales folks to live in every day. And once again, it comes down to simplification. They’ve put an emphasis on simplifying fields, and getting value out of the system for the sales team. They’ve also integrated other platforms, such as a forecasting module and compensation tools. Why such a large use of technology? Because at the end of the day, it’s about making the sales teams lives better according to Chris. And these tools help them get there.
When it comes to technology, Chris had another important piece of advice. Take your time and understand what you’re trying to accomplish. Quick deployment sounds great. But it’s not a reality. Chris recommends partnering with your IT counterparts. Together, at Motorola the two departments are leading the pack. By working together, they have been able to successfully implement multiple systems to make the sales force more successful.
Chris wrapped up the conversation with three easy tips for other sales ops leaders. First, simplify things. Boil it down to the key items that you need. Get alignment around these so the entire organization is on the same page. Next, operationalize it. The sales reps, and managers must use the data in their everyday jobs. It must provide value. And finally, partner with IT. This allows you to move fast, and be best equipped to enable the sales force.
As a sales ops leader, it’s your job to provide meaningful and measurable impact to the sales team. You must do this through data. If you need help with your data planning, download our playbook here. It will give you a road map to harnessing the power of big data.