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Why IT operations needs new metrics
At a time when CIOs can use cloud infrastructure to turn on new money-making services for customers overnight, how should should we measure IT success? Hint: It's not about uptime
In 2020, a year like no other, is it still useful to measure IT value based on green, yellow, or red lights on a screen?
Now that infrastructure is everything – powering productivity, cutting OPEX, and providing the flexibility to support digital initiatives that may change overnight – flashing lights on a monitor are no longer enough to keep the wheels moving. It’s time to develop new metrics based on an increasingly digital world.
While availability is still profoundly important – count on users to complain loudly when an app or site is down or glitching out – traditional IT metrics such as server capacity, I/O, utilization, and network throughput are now table stakes for survival. In organizations with hefty cloud-based investments, those data center metrics are less relevant because infrastructure components are abstracted and delivered as a service.
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Cloud infrastructure, however, is measured on response time, scalability, security, and cost per customer/user. For CXOs, the cloud is a mellifluous notion enabling them to turn on new money-making services for customers overnight.
Another trend supporting new metrics is the advent of intelligent, automated infrastructure monitoring systems that abdicate the need to supervise those flashing lights all day. IT engineers and admins can finally shift their focus from outages and data call fire drills to optimizing technology based on user needs and business priorities.
Forrester Research analyst Rich Lane writes about the problem with old metrics in his blog: “Measures such as MTTR are antiquated in environments where systems have been built to be highly resilient and automatically scalable. If I&O is doing its job correctly, the low-complexity, high-volume incidents are being rooted out of the system.”
From servers to sales and satisfaction
In the grander scheme of things, IT operations must give users (including end customers) measurable value. Whether that value is improved productivity, an incredible experience, or a novel product offering, it all comes down to metrics: Do you have the right metrics to demonstrate value for users and stakeholders? Do you know how (and why) users prefer one service or app over another? Can the work of IT help frontline employees make better decisions to grow revenues, loyalty, and customer satisfaction?
I’d like to say yes, yes, and yes. But this takes some work and reorientation.
Thinking about the new metrics
No matter your industry, IT operations leaders can start by uncovering the critical use cases for driving organizational success. These are the digital initiatives and technologies that support customer-facing products and services along with the tools that enable employees to best serve your market. With this knowledge, IT operations can begin creating the new metrics and correlating them to the “old metrics” of availability and performance.
Let’s look at some examples:
E-commerce: For online retailers, the focus of the last several years has been understanding buyer intent: What are customers buying and why? What might they buy and when? Which factors play into the customer leaving the site and not buying? Why do customers come back as a repeat customer?
Therefore, metrics could include the number of items purchased in an order, the dollar value of an order, shopping cart abandon rates, and transaction time from when the customer hits the site until purchase.
Understanding these metrics could inform decisions such as: Do web pages load fast enough? Is our recommendations engine working properly? Are products out of stock or is the purchasing process difficult? Do we need to optimize cloud services or select new ones to support all of the above?
Banking: Cross-selling and upselling is a vital revenue-building tactic in financial services. Therefore, one might want to measure the number of banking products and services consumed per customer.
Another measure of customer satisfaction is the quality of digital services. How many electronic transactions and interactions are customers conducting per week and how does that correlate to lower attrition or increased revenue per customer? Again, negative results could indicate IT performance issues while conversely, positive results confirm the current strategy and technology portfolio.
Automotive: Replacing the sticker on your window saying change oil by this date, in-vehicle technologies like OnStar can send alerts to customers based on their driving behavior and let them know when their oil needs to be changed or when it’s time for recommended maintenance. This is an example of customer value in the form of issue avoidance and user experience. Measuring the accuracy and impact of these monitoring technologies would be valuable, especially if connected to customer satisfaction metrics and total cost of ownership for the vehicle.
IT operations professionals need to maintain a close eye on capacity, availability, and reliability. But to deliver business value, we need to start thinking about how everything we do affects employees, customers, and revenues.
Work back to the IT metrics. For each service you’re measuring, you’ll need to break it down into steps and processes, and from there, down to the underlying technologies (network, database, storage, VM, instance, transactional systems) that enable it. Engaging with power users, business process owners, and/or developers is often necessary to obtain this view.
Look for automatic service mapping features in IT operations tools, which can provide easy visuals and drill-down capabilities when analyzing performance. The devil’s in the details, as they say; being able to rapidly pinpoint a brewing problem to the root cause where it can be fixed before it affects users is a competitive advantage.
Find new forms of analytics. Tools that gather customer usage data (such as Pendo) can serve as a starting point for creating new metrics and goals. Having data science skills on your team is a boon; adopting business metrics requires the ability to make new correlations and conclusions.
How can disparate data sets of user/customer activity be used to improve customer adoption of digital tools, inform new features, or reduce investment in less-used ones?
Measure lagging indicators. In our e-commerce example, revenue per customer is the outcome measure – otherwise known as the lagging indicator. Capture those metrics (which should be easy to get from the sales and marketing team) and use them as a benchmark to continually work against and improve.
Identify the leading indicators. Customer usage and behavior are two critical leading indicators for most organizations. By obtaining end-user data stored across various front and back-office systems, you can start to make correlations with performance metrics.
But first, a holistic understanding of the overall business requirements and core processes that support them is imperative. Understanding the ways in which the bottom line is affected could lend opportunities for improving it. Cross-functional groups such as Centers of Excellence (COE) can be useful in these efforts.
Refine. As you learn more about user behavior and digital service performance, you can optimize your reporting metrics by improving on leading indicator performance and thereby, business outcomes. The satisfaction of knowing how IT operations changes impact broader organizational metrics and KPIs will be well worth the effort—and your boss will applaud the insights and results that can materialize in time.
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