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Week in the Life of an Analyst at Gartner US IT Symposium (virtual) 2021

By Andrew White | October 22, 2021 | 0 Comments

Gartner Symposium 2021

If you follow my blog for any period of time you will know that for most years I have attended our annual Gartner IT Symposium I do a day-in-the-life blog of an analyst.  This often starts with a graphic of my mind waves (courtesy of Muse) and then you get an hour by hour run down of what I do every day.  I then wrap it all up with a summary of my 1-1s.  This time, since we were virtual I only managed to close out the week with the 1-1 summary.  Here it is (below) along with the most often shared/used graphics throughout the week.

Industry: 35 (alphabetical)

  • Automotive 1
  • Business/Consumer Services 5
  • Chemicals 1
  • Consumer/Goods 3
  • Defense 2
  • Energy/Clean 1
  • Energy/Power 2
  • Financial Services 4
  • Food 1
  • Healthcare 4
  • Higher Ed. 3
  • HVAC 1
  • Conglomerate/Industrial 4
  • Logistics 1
  • Technology Vendor 2

Type: 35 (ordered in frequency)

  • Services 14
  • Manufacturer (process or discrete) 8
  • Distributor 7
  • Public Sector 3
  • Conglomerate 1
  • Retail 1
  • Public Sector (Military) 1

Topic: (ordered in frequency)

  • MDM and/or D&A Governance and Stewardship 26
  • Monetization/Link data to outcome (value pyramid) business value of data/business impact 20
  • D&A Strategy/infusing business with (overall) 16
  • Business Information Model/Arch compared to classic enterprise data model and how to relate it to catalogs and marketplaces and enterprise data models 13
  • Getting Started 14
  • CDO Leadership/Organization (roles, decentralized/business v centralized/IT) 11
  • Analytics Tactics (known outcome/known data/BI/analytics v unknown outcome/unknown data/data science/ML) 11
  • Data Hub Strategy 10
  • Digital Business connections to D&A/decision modeling 10
  • Lakehouse (data warehouse and data lake working together) 8
  • Data Literacy, training, coordination, collaboration 8
  • Business Innovation with D&A 6
  • Specific Vendor Questions 5
  • Portfolio Planning/Optimization 5
  • Data Management Infrastructure/Data Fabric 5
  • Data Integration tactics 4
  • Metadata Strategy 3
  • Build (SWEL) v Buy 1
  • Decision Making/GDI 1

Role: 35 (ordered in frequency)

  • Chiefs:
    • CIO VP/IT 9
    • CDO (data officer) 2
    • COO 1
    • Chief Medical Information Officer 1 (CIO)
    • Chief Data Strategist 1
  • Leaders:
    • Director IT 2
    • Director IM/IT 1
    • VP Data and Analytics 1
    • Senior Director 1
    • VP BI and Innovation 1
    • VP Demand Sciences 1
    • Director Enterprise Applications 1
    • VP Data Science 1
    • Director Enterprise Analytics 1
    • Director Product Marketing 1
    • Director IT Solutions Delivery 1
    • Director of Information Systems & Portfolio 1
    • Director Global Services 1
  • Managers:
    • Application Manager 1
    • Technical Manager 1
    • Enterprise Data Manager 1
    • Web and Data Services Manager 1
  •  Others:
    • Snr Architect 1
    • Snr Technical Advisor 1 (EA)
    • Unknown 1
    • Portfolio Manager 1

In terms of the most popular visuals/slides we explored during the week, here are the top three.

Figure 1: Data and Analytics Strategy and Operating Model

 

Most 1-1’s started here.  It often didn’t matter the opening situation since everyone needs a guardrail in which to organize next steps.  That is the beauty of our framework.  Central to every conversation was, “and what is the business outcome” which is explicit in our D&A Strategy and Operating Model (and often missing in alternative models in the industry).

Figure 2: Value Pyramid.

 

This is almost like an old fan-favorite.  This graphic and accompanying slides talk to a solid principle that remains elusive in many overly complex strategies and efforts: how to make diagnostic connections between specific data and a business outcome your leader cares about?  The slide alludes to a workshop and a skill that any D&A role can master and in so doing, it augments their communications ability with business leaders and also explore and explain to technologists more clarity over requirements for data, analytics, innovation, improvement, and governance.

Figure 3: The Data and Analytics (infrastructure) Continuum

 

This has never been published though it preceded what was, Adam Ronthal’s Data and Analytics Infrastructure Model.   This simpler view is what I use to explore with leaders how to gauge the needs of the business at a high level when comparing to traditional analytics and innovation with AI and ML and data science.  What I found most rewarding was that two chief’s said they loved the slide and planned to use it with their peers in their upcoming meetings since the graphic was simple to understand and it sent a powerful, clear message.  What more can an analyst want?

I said I would share the top 3.  But there is a fourth!

Figure 4: Connecting Catalogs/Marketplaces and Data Fabric to modern, outcome D&A governance.

This graphic has not been published and in fact is ongoing research.  However the idea is pretty simple (if incomplete for now).  A data fabric can help discover and inform about data across silos.  A data catalog can catalog that same stuff.  A marketplace too.  But as is, all such data is ungoverned.  The only way to effectively govern it is when business leaders and roles take on the responsibility of policy setting and enforcement – and that is where the value pyramid and other best practices come in.  The top-down, outcome-based approach is at the top of figure 4 and this can help explain why business roles will want to govern a glossary.  But IT has to manage the lower level technical data and that is represented as a dictionary.  And catalogs and data fabric can be used to build those out too.  So all these initiatives and capabilities can connect.  So “connect” was a powerful word this week at Symposium.

Hopefully you had some fun at Symposium and found it helpful.  I hope to see you all again – maybe in person – next year!

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