“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were dealing with out-of-date information and, because we used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 reduced SLA breaches
by 80% and saved $225,000 a year through automated data collection
and analysis.
- 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.