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IT Metrics/Dashboards at Duke: Curation, Automation, Aggregation? CSG January 11, 2012.

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Presentation on theme: "IT Metrics/Dashboards at Duke: Curation, Automation, Aggregation? CSG January 11, 2012."— Presentation transcript:

1 IT Metrics/Dashboards at Duke: Curation, Automation, Aggregation? CSG January 11, 2012

2 2 Background  Initiated metrics effort in 2008 (1 FTE dedicated)  Aligned with finance initially, now integrated with service management team  Focused on availability, capacity, service usage/demand, internal resources  Consult with units on what metrics they should capture  Help with collection and analysis of metrics  Ensure consistent, universal reporting of data

3 3 Initial scope and progress  Monthly reporting process for managers and community  Internal: Data collection, report development, management review, publication of detailed report  External: availability, usage, performance summaries  Limited range of services historically  Email, network/voice, paging, HR, IT security, telepresence

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6 6 The challenges of our “curation” process  Labor-intensive  Monthly periodicity limits immediacy  Fine for long-term trending, but less immediate  Reliance on local units to self-report  Leveraging Duke’s post-incident review (PIR) process, but remaining data still sui generis Curation: work by content specialists immersed in a specialized discipline and imbued with analysis

7 7 Metrics and newsgathering: Classic curation processes?

8 8 Duke’s metrics curation challenges  No one wants to read “yesterday’s news”  Hard to avoid with curation  The stories are too long  New monthly exec-summary focused on trends has helped (like the WSJ’s “What’s News” box) to a point  Focus on putting out a daily paper takes away from the “longreads”  Time required to produce manual reports takes away time expected to be spent on consulting with units to help them be primary data-gatherers

9 9 Curation vs. automation

10 10 Automation: leveraging monitoring data  System/network monitoring produces thousands of data points a day – how can we use them?  Left: Daily low-level alert analysis (SPC methodology)  Not shown: Loss of redundancy reports

11 11 Automation: Leveraging monitoring data

12 12 Duke’s metrics automation challenges  Automation a great start, but plenty of “curation” still occurs!  Monitoring’s “service dashboard” useful, but not ready to be directly published  Monitoring events don’t/can’t catch everything  Human adjustment still needed to raw data  Low-level alert reports are automated… and reviewed by daily operational staff  Ultimately, there’s infinite ways to leverage data, but what do you care about?

13 13 Curation, automation, aggregation

14 14 Duke’s aggregation questions  What data mix should appear?  Curated data from monthly metrics, live report on high- priority user tickets, performance graphs, availability measures against targets on one screen  Broad enough to be watched; specific enough to be useful  What platform should we use?  SharePoint? Improve collection, visualization  ServiceNow? Leverage dashboards, APIs, data structure; easy access to support tickets  Javascript/JSON components for easily customized dashboards? – node.js and d3.js


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