• Lisa Schlecht
    Lisa Schlecht
    schedule 8 months ago
    Sold Out!
    45 mins
    Talk
    Intermediate

    Does any of this sound like you?

    • You’re a changemaker working on a complex problem either as an entrepreneur or intrapreneur. You have some resources for making change but will need to work with partners, policymakers, or others to scale your impact.
    • You’re a product manager, business analyst, designer, architect, or systems engineer in a large organization.
    • You’re working on a difficult problem which will need to be solved in phases over months or years.
    • You’re managing a portfolio of work that spans multiple time phases or teams.

    Are you running into any of these problems?

    • The product design cycle is taking too long.
    • You’re delivering value but getting a lackluster response from customers and stakeholders.
    • You have great ideas and the customer likes them, but there's no roadmap to get them into production.
    • You have multiple stakeholders, none of whom are on the same page.
    • You don’t have one single, completely informed decision maker who can make the final call.
    • You’re having difficulties reconciling modern experiences with legacy systems and business processes.
    • You have “wicked problems” to tackle but your organization is ignoring them in favor of low-hanging fruit. And you’re starting to run out of low-hanging fruit.
    • You’re having difficulty helping other people focus on anything beyond the latest fire.

    If any of that resonated with you, an Enterprise Design Sprint might be exactly what you’re looking for. Combining elements from agile, design thinking, enterprise architecture, and systems engineering, Enterprise Design Sprints will help you make sure that you're delivering value over the long term. This talk will cover the theory and mechanics behind planning and running your own sprint, with examples from the U.S. Department of Veterans Affairs. 

  • Liked Atif Salam
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    Cracking the Code... Implementing SCRUM at Scale within Enterprise Data at Fannie Mae

    Atif Salam
    Atif Salam
    PHILLIP MANKETO
    PHILLIP MANKETO
    Dave McMunn
    Dave McMunn
    schedule 8 months ago
    Sold Out!
    45 mins
    Case Study
    Intermediate

    Fannie Mae, a leading source of residential mortgage credit in the U.S. secondary market, provides reliable, large­scale access to affordable mortgage credit across the country so people can buy, refinance, or rent homes. In November 2014, Fannie Mae’s Enterprise Data Warehouse completed a multi­year project to implement several thousand data attributes across numerous interfaces which were then integrated with various development organizations working in parallel; the results were sub­optimal. In January 2015, Fannie Mae undertook a brownfield initiative to transform Fannie Mae’s Enterprise Data Warehouse, responsible for sourcing, vending and provisioning data attributes, which informed numerous interfaces, as part of a larger Federal compliance mandate, to SCRUM. Initially, starting with two teams using SCRUM, the initiative progressed to six-teams implementing SCRUM­OF­SCRUMS, within 6 months. Thereafter, the SAFe framework was adopted encompassing twelve­teams (130+ team members) on a single Agile Release Train. As a result of transforming from Waterfall to Agile, Fannie Mae experienced a significant boost in productivity and reduction in delivery risks through the relentless focus on innovation and automation to ship "production ready" code with high and higher frequency. The transformation to Agile has revolutionized how the firm plans for the delivery of large scale ($100 million plus investment/year) programs, has significantly mitigated risk inherent in complex in integration between legacy and new architectures/applications, as well as between internal and external systems. Within the larger context of the transformation to Enterprise Agility, this Experience Report will focus on the changes to the organization, architecture, and technical practices required to implement data attributes every two­-weeks and the corresponding benefits realized.

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