Running a full stack data shop

Aaron Gorham, Senior Director of Data and Analytics at J.R. Simplot, shares insights on navigating full-stack data operations and evolving legacy organizations. In a traditional setup, different data functions operate as separate entities within the organization, leading to silos and communication challenges. However, amidst the rapid pace of technological advancements in the data space, aligning data personnel across the organization emerges as a strategic move. Today, Aaron discusses running a full-stack data shop.
About the speaker

Aaron Gorham

J. R. Simplot

 - J. R. Simplot

Aaron is Senior Director of Data and Analytics at J.R. Simplot

Show Notes

  • 01:54
    Running a full stack data shop
    Running a full-stack data shop involves centralizing various data functions like data quality, master data, data services, data and analytics, and data science teams. This integrated approach facilitates knowledge sharing, and synergies, and accelerates learning and innovation.
  • 02:56
    Organizational setup for data functions
    The setup of having all data functions under one organization, as in a full-stack data shop, is less common. More frequently in organizations, data teams tend to be siloed from each other, lacking the tight grouping and connection found in a full-stack approach.
  • 03:41
    Transitioning to a full stack data shop
    J.R. Simplot unintentionally integrated its master data, data conversion, and data quality teams with the enterprise data and analytics organization during a large SAP initiative. Eliminating the silos between data functions enabled a seamless and more efficient data conversion process.
  • 06:02
    Overcoming the challenges of integrating different data teams
    Divergent missions among master data, data quality, data analytics, and data science teams often result in communication challenges. Fostering trust, informal relationships, and a collaborative culture ensures teams know how and when to communicate with each other.
  • 07:08
    The value of unified data teams in legacy data transfers
    By integrating the data teams into a data quality team, J.R. Simplot streamlined the process of preparing legacy data for SAP transfer. This unified approach significantly reduced the time between production and reporting by avoiding duplicated efforts in data transformation.
  • 08:21
    The benefits of a centralized data and analytics team
    These teams offer speed to market and consistent delivery of results. In addition, having in-house system and data expertise reduces friction within the IT organization, enabling quicker responses to business unit requests.
  • 09:20
    Advocating for the centralization of data functions
    The rapid evolution of the data space demands consistency and efficiency. Highlight centralizations ability to facilitate people working in the same way, enable fluid movement of personnel across teams, and enhance organizational flexibility.
  • 12:44
    Onboarding in a complex data environment
    Onboarding new team members in a complex data environment with multiple ERPs is a significant challenge. Centralizing data operations can streamline onboarding processes, making the team more efficient and effective in innovating and providing insights.
  • 13:34
    Change management for data centralization
    In transitioning to a centralized data system, communicate the value of the change and manage people's expectations within the organization. It's crucial to focus on what can be done now and learn from mistakes rather than waiting for all the answers before taking action.

Quotes

  • "Technology is changing so fast in the data space that aligning your data folks across different disciplines within your organization gives you the ability to do more faster, and more consistently than in the past." - Aaron Gorham

  • "There's something powerful about just getting in there, learning it, and making mistakes for free before it's in front of the business, and you're making decisions with that data." - Aaron Gorham

  • "One of the perks of having all the data functions under one organization is, the level of system and data expertise within the team reduces friction within the IT organization and allows us to deliver a lot faster." - Aaron Gorham

About the speaker

Aaron Gorham

J. R. Simplot

 - J. R. Simplot

Aaron is Senior Director of Data and Analytics at J.R. Simplot

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