“Can you start with someone else?  I haven’t decided yet.”


This is my usual response when the waiter or waitress comes to take my dinner order at a restaurant.


I typically struggle with that most basic daily decision because there are so many important influencing factors.


What did I have last night and earlier in the day?

Am I very hungry and just need a light meal?

Should I be on a diet?

What does this restaurant do particularly well?

Do I want chicken, beef, or pasta?

What sides comes with each of the options?  I hate to admit it but I’ve ordered an entrée based on the sides before.

What type of wine is everyone at the table drinking and will it pair nicely with my order?

What am I likely to have tomorrow?

What is the person across from me thinking of getting, because if it happens to be the option I didn’t choose and it comes out looking and tasting better than mine I’m going to have regrets? (Or - if that person is the sharing type, then this could work in my favor…)


Then of course after I weigh all of the decision factors the waiter will offer up a few specials, that throws everything off.


All of the above factor into a single decision that I make on a regular basis.


Clearly, I suffer from – “analysis paralysis”. This is the state of over-analyzing (or over-thinking) a situation so that a decision or action is never taken, in effect paralyzing the outcome.


Now let’s think about how many intraday decisions people in your organization make and how many factors they could be dealing with on a decision by decision basis.


In order to help our organizations operate in the most efficient manner as possible we should strive to streamline as much of the decision making process as possible, while still leveraging all of the valuable data points that are at our disposal. An interesting balancing act for sure.


Enter the Performance Analytics “Spotlight” functionality.


CSI Dashboard.png


The Spotlight functionality allows you to assign a score to different aspects of a piece of work (any record) in the ServiceNow platform based on how much influence it has on the action that should be taken.  This declarative scoring helps you better prioritize work in the platform.


What does that mean?


Instead of using a single aspect of an incident - like priority - to determine where we should focus our attention, we can use multiple aspects of an incident – priority, state, age, criticality of the affected CI, etc. - to determine which incidents you should focus on first.


We use what is known as a Spotlight group(below is an example) to define which aspects or decision factors we want to weigh more heavily for an individual use case or decision. (In the dinner example above, perhaps the most important factor is that my wife is sitting next to me and “we” are supposed to be on a diet. )




The individual scores get aggregated on an incident by incident basis and we can then give the Service Desk Worker a ranked list of prioritized work.


We can apply this same approach to an external Customer Service example.


Let’s say we are releasing a new product and we want to make sure that cases coming in related to that product get prioritized accordingly, or we have certain customers that demand higher levels of support based on their loyalty, a paid premium, or maybe another unanticipated factor.   We simply adjust our Spotlight rules to apply more points to cases that contain that product or customer and the agents are now presented with the cases they should focus on without having to weigh those factors on their own.





The final example I’ll offer up has to do with where to focus automation efforts inside the organization.


One of the ways organizations look to drive costs out of the services they are providing is through automating frequent requests that come in to a service desk.   Too often organizations only focus only on the “volume” or count of those requests when they are making a decision on where to focus their automation efforts.





They’d most likely get a better return if they took a number of different factors into account.  For example, the “velocity” in which those requests are serviced is a key factor.  If we have a high volume of requests for a particular service but we are resolving them quickly, it might not be the best target for automation. So we could add velocity to the equation by measuring Mean Time to Resolve.





We’d also want to take into account the consistency in which we are seeing these requests against this service.  If it’s just a one-time spike of requests, is it worth automating?    So the trend or the “momentum” behind these requests is also a factor we’d want to take into account.





These are all contributing factors.



Spotlight allows me to take all of these factors into consideration, as well as others, score them, and rank the business services that would be the best targets for my automation efforts based on the different aspects of the requests that are coming in.





The data that gets generated as people work within the ServiceNow platform is a valuable asset that we can use to make better business decisions.


For most people, analyzing the data isn’t their job, but they need to act on the insights that the data provides. The Spotlight functionality in Performance Analytics streamlines the pathway from insights to action and drives efficiencies throughout the organization.


Now, if I only had a Spotlight application on my phone to help me figure out what I want to order for dinner tonight!


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