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Machine Colony

Engagement Cycle

Eng cycle discovery


  • Pain points: What are the bottlenecks and inadequacies of the current approach
  • Usage Patterns: What does the typical cycle look like on the current process
  • Vision: When your ideal system is in place, what capabilities will it provide
Eng cycle data mapping

Data Mapping

  • Current data strategy (if exists)
    - Steps in business process that could be data production/transaction points (even if currently manual)
  • Data Sources
    - Private (transactions, call center tickets, etc)
  • Desired
    - Usually public sets (financial markets, demographics, macroeconomic metrics, industry-specific indexes)
Eng cycle pilot


  • Identify key line of business/section of work ripe for showing early value
  • Set expectations/milestones that prove out capabilities prior to production version
Eng cycle data pipeline

Data Pipeline

  • Integrate all data sources into unified structure
    1. Private data
    2. Public
    3. Pre-processing
Eng cycle scale


  • Building production-grade systems is just the first-step
  • Develop and implement change management plan to embed technology in relevant business processes
    1. Data ingestion from relevant producers (Acct. Managers, Customer Relations specialists, etc) in addition to APIs and programmatic sources
    2. Transition brokers and executives to appropriate interfaces (mobile, dashboard, etc) for platform
Eng cycle review support

Review and Support

  • Identify innovation leadership personnel to guide optimizations of system
  • Programmatic user feedback system
    1. Digital suggestion ticketing
    2. Focus groups
    3. support ticket tracking
    4. User survey (for broadly adopted tools)
  • Dedicated Customer Success Specialist