On a recent cross country flight, I found myself watching one of my favorite movies to pass the time, Moneyball.
If you love Baseball, Analytics, or Brad Pitt you're probably familiar with the story. Billy Beane, the general manager of the Oakland Athletics, is asked by ownership to field a competitive team with the fraction of the budget than that of the other teams in the league.
It's the classic "Do more with less" story that unfortunately many of us are all too familiar with in our own organizations.
The twist here is how Billy Beane's new assistant GM, who had an economics degree from Harvard and not a lifetime of baseball experience, bucked the traditional approach and started to look at baseball from the standpoint of data, analytics, and outcomes.
Baseball is a business. And just like in business it's a good idea to start with the outcome you are looking to achieve and then design and execute a plan to achieve that outcome.
For a baseball team, the ultimate outcome is to win the World Series, from a business perspective the outcome that ownership wants to achieve is profitability. Winning the World Series would in most cases be a big contributing factor to the business outcome. Remaining competitive later into a season drives attendance, which in turn means more ticket, merchandise, and vending sales.
Moneyball details how the Oakland A's used historical data and analytics to get an understanding of the most effective and efficient way to achieve the outcomes that they wanted.
The assistant GM broke it down like this — in order to win the World Series, we have to be in the playoffs. To be in the playoffs historical data suggests we will need X number of wins. To get those wins we will likely need to score X number of runs. So they created a series of connected outcomes that were necessary for them to reach their goal.
It's at this point they started to break with traditionalist approaches to building a team. Historically, organizations measured and built their teams on statistics like Homeruns and RBIs, but what the data told Billy Beane was that these were not the biggest contributing factors to scoring runs which was the initial outcome they were looking to achieve. The data suggested that On Base Percentage and Slugging Percentage were bigger contributors to offensive success and the goal of scoring runs which influences wins and so on and so forth up the chain.
Since employing the Moneyball approach, the Oakland A's have consistently been competitive and one of the more profitable teams in all of baseball.
The success the A's have had with this approach has ultimately changed the game of baseball.
No matter what business you're in, this concept of outcomes and using data to better understand what actions you can take to influence those outcomes can be applied.
At ServiceNow we provide a cloud based platform to help organizations change the way they work by adding structure and automation to the business services they provide. The structure the platform provides generates a tremendous amount of data about how efficiently these services are being provided and can be used to give us insights on just where in the process there are opportunities to make adjustments to achieve the business outcomes we want.
ServiceNow's Performance Analytics offering is "Moneyball" for Service Management.
Performance Analytics allows you to align and communicate the business outcomes you are looking to achieve to an entire organization and provide the insights individuals need to adjust their actions to influence those outcomes.
For example, let's look at the Service Desk. The business outcome is to deliver a great experience for customers in a cost effective way. In order to achieve that outcome, I need to continually improve the quality of that service by aligning it to changing business needs and streamlining the overall engagement process to reduce costs.
Anywhere we can improve in either of those areas would be the equivalent of a win in the baseball analogy.
What data can I use to understand how I'm doing in terms of wins, and more importantly what data can I use to identify how to positively influence these outcomes?
Mean Time to Resolve(MTTR) is a popular metric used to understand the overall quality of a Service Desk. It's a measure of the elapsed time from when an incident was reported to when it was resolved. Reducing the average MTTR will go along way improving the customer experience and in turn reducing costs. (Similar to the World Series, Profitability relationship).
What actions can I take or where should we invest to reduce our MTTR? In other words, what is my On Base and Slugging Percentage for the Service Desk?
Well, they are stats like First Call Resolution Rate, Reassignment Counts, and Self Service Adoption Rates — all these are areas that if I improve upon they are going to impact my MTTR, which impacts my quality of service, and ultimately helps deliver a great experience for my customer in a more cost effective way.
Performance Analytics on ServiceNow not only gives you real time access to these types of insights, it gives you the ability to understand how the actions you take are influencing the different outcomes you are looking to achieve. This visibility allows you to make the necessary "in game" adjustments.
A CIO colleague of mine once said to me — "We have three types of projects we work on here, projects that allow us to be in the game, projects that will help us win the game, and then the projects that will change the game".
Performance Analytics is Moneyball for ServiceNow - it changes the game when it comes to Service Management.
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