“What gets measured gets improved.” — Peter Drucker
It’s more than a sound bite. It’s the foundation of business success. Yes, goals and plans are critical. But unless you can measure your business performance, how do you know your plan is working? You don’t. There’s no way to see your progress—or even to know if you’ve set the right goals.
That’s why ServiceNow® Performance Analytics is so important. It delivers 360° visibility of your business performance against your strategic, operational, and individual objectives—how you have performed in the past, how you are performing now, and how you are likely to perform in future. That gives you actionable insights—so you can tackle issues and identify opportunities as soon as they start to appear.
At ServiceNow, Performance Analytics ensures quality and drives continuous improvement across our business—whether that’s in customer service, development, professional services, or our internal IT support. It’s a crucial part of our digital transformation journey.
Let’s take a deeper look at one of these areas—customer service. We'll share some key challenges, how we solved them, and the benefits we’ve seen. We hope that our own experience provides practical insights into how you can use Performance Analytics to transform your own business.
Introducing Ian Cox and Sandy Swanson
Ian Cox is responsible for managing our customer service applications and uses Performance Analytics to continually enhance the value that ServiceNow delivers to customers. Sandy Swanson leads our operational analytics team for our customer service and development organizations.
Sandy remembers how things were before Performance Analytics. “Just like other companies, we spent weeks analyzing operational data with spreadsheets. It took too much time, and it was incredibly complex. We were dealing with out-of-date information and, because we used spreadsheets, we were always hunting down errors. There was no real-time visibility and it was virtually impossible to identify trends or extrapolate them into the future.”
Ian agrees, saying that “Every operational team had their own PowerPoint deck, which was reviewed at our monthly operations meeting. By the time we saw the deck, the data was at least two weeks old. That meant we were reacting to things that happened in the past, rather than proactively focusing on the present and future. And we didn’t know if we were measuring consistently across our teams. For example, was everyone counting customer or internal requests the same way?”
Analyzing data in real time
Reviews were only a part of the issue. To deliver high-quality services, our operational teams need to analyze data in real time. Ian highlights an example, saying that, “At ServiceNow, we promise our customers the nonstop cloud. That means providing 99.999% availability on average for customer ServiceNow instances.”
Ian continued, “If the availability numbers start to dip, we need to know right away. Waiting until the next monthly review just isn’t an option. Try to track availability in real time with Excel, and you’ll soon realize the enormous limitations of spreadsheets."
How Performance Analytics puts our customer service into high gear
Tracking availability was only one component of a broader issue. “As a rapidly growing company, we were adding new customers every day. Our growth was driving an increase in customer-related cases—not because of quality issues, but due to the sheer number of customers. We had to reduce and prioritize these case volumes before they overwhelmed our development teams—and, most importantly, before customer service was affected,” said Sandy.
That’s where Ian comes in. Customers use our customer service applications to report cases, which are addressed by the customer support team. They are then funneled back into our development team so they can take action to resolve the underlying issue—whether that’s by adding functionality into the next release, fixing software defects, or providing additional knowledge base articles to help customers.
“We had all the operational data, but we needed to understand what it meant. We needed a global view of how well we were performing so we could measure our progress. And we also needed to drill down into that operational data, analyzing it to identify problems and opportunities. That’s what Performance Analytics does,” said Ian.
Measuring red line performance
Ian and Sandy started simply, using Performance Analytics to create an overall “red line” dashboard showing the average number of cases per customer and how this was changing over time. With this real-time dashboard, executives could see historical trends and future case volume forecasts. This created a baseline to measure and drive improvement.
Next, they broke down the red line by product or service area, giving each development manager their own individual dashboard. With this dashboard, each manager could see how their individual area was performing—using Performance Analytics to profile the types of cases that customers were reporting.
Identifying automation opportunities
Ian gives an example from his own customer service team, saying that, “We found that customers were constantly raising cases to request password resets on test instances. That was driving a significant proportion of our volumes. So, we automated password reset and added it into our customer service catalog. That eliminated 650 cases a month and made password resets much faster and easier for customers.”
That’s just one example. Ian’s team has also automated many other customer requests, using Performance Analytics to identify high impact opportunities. These include activating plugins, resetting non-production ServiceNow instances, and removing demo data. The result? Ian’s team has reduced customer-related cases by 3,500 a month, freeing our customer support team to focus on more complex issues.
Delivering enhanced products and services
Keep in mind that this is just for our customer service cloud environment. Each of our development managers is driving similar results, using Performance Analytics to identify and prioritize problems based on the cases we receive from customers. And, it’s not just about problems. Performance Analytics allows us to identify creative product and service enhancements that improve the customer experience—in the same way that Ian has for our customer support application.
Using Performance Analytics across the enterprise
Customer Service is just one example of how we are using Performance Analytics to transform the way we work at ServiceNow. For instance:
- Our development teams use Performance Analytics to get our releases out on time. We analyze the status and activities of 60 scrum teams, identifying everything from showstopper issues through to burndown rates of sprints and stories. That means we can see whether our releases are converging and take early action when there’s an issue.
- Our internal IT support team uses Performance Analytics to forecast resolution times, generate leading indicators of issues, correlate service metrics, and generate real-time dashboards. As a result, the team has saved $1.6M a year through automated data collection and analysis plus 12,500 hours through real-time reports and dashboards.
- Our global Professional Services group uses Performance Analytics extensively to manage delivery of remote services to ServiceNow customers. This allows us to closely monitor and analyze performance, as well as identify resource bottlenecks and workload issues that could affect delivery.
That’s just a sample. Performance Analytics is delivering value across many ServiceNow departments, helping us to make better decisions and track our performance at the strategic, operational, and individual level. And as we continue our Performance Analytics journey, the momentum continues to build.
What have we learned?
As we have used Performance Analytics across our business, we have identified several best practices that contribute significantly to our success.
1. Start at the top
It’s important to start at the top of your organization with a few key metrics, as we did with our case red line.