In our latest installment of the Data Sherlock series, we find our Sherlock meeting with a Splunk administrator who works at a manufacturing company. In this example, the administrator was frustrated because she felt her efforts were not being appreciated by the larger organization.
To get the conversation started, our Data Sherlock asked the administrator to describe what she had done with the Splunk platform to date.
This question was answered with a long list of accomplishments that included leveraging Splunk to search and investigate across all tier 1 applications, adopting Splunk as a SIEM and, finally, being the data platform linking all application teams and operations. Our Data Sherlock was very complimentary as this is an impressive list of accomplishments, but he did have one question.
What is the key “service” that runs your organization?
The Splunk administrator tried to answer this question by offering up various applications or technologies, but finally gave up and admitted she wasn’t sure what the service was. Although our Data Sherlock wasn’t completely sure of the answer, he offered up a suggested service that he felt was their most critical.
Specifically, he proposed that at most manufacturing companies the production line is the most critical service, because when that stops, revenue stops. This comment hit our Splunk administrator like a bolt of lightning, and she admitted that he was right and that she had overheard rumblings in the past when the manufacturing line was down. However, given it wasn’t her area or in IT, she never really dug in and had instead just moved on. Our Data Sherlock then exclaimed, “Exactly!”
“Now that we both agree that the production line is the most critical service to your manufacturing company, what can you do about it?” The administrator didn’t quite see the connection, so our Data Sherlock explained further. “Have you ever thought about ingesting the machine data from across your production line? Have you ever thought about Splunking the various handhelds that operators use on the production line? How about tying machine data from the production line to client returns, shipping errors, configuration options, maintenance issues, etc?”
To this, the Splunk admin said, “No, but I get it now and I know we leverage a lot of tools across our production line that produce machine data. I see how that data could then be used for maintenance, cost control, revenue generation and quality control.”
But the Splunk administrator did have one last question: “Do you have an example of what might this look like?” Our Data Sherlock indicated that he was happy to share an example, but cautioned that each manufacturing organization should execute their own Glass Table Workshop (free of charge) to find out what it might look like for their organization. At which point he turned his laptop around and showed the Glass Table example below.
“In this example, we are ingesting data in each 'Bay' and we have established Key Performance Indicators for each area.”
Now the Splunk Administrator was very excited, understood how she could take Splunk to the next level and, most importantly, how she could gain visibility within her broader organization by tackling her organization’s most critical service—the production line.
Our Data Sherlock ended the conversation with one final note. “I’m glad we had this talk, and if you want to dive in more you should contact your Splunk sales rep and ask for a Splunk IT Service Intelligence Glass Table Workshop. These are client-specific workshops and our sales reps are happy to help draft what is possible across your specific critical services.”
Z – Data Sherlock