Data Business Models

Context: FIT1043_MOC · how organisations create/capture value from data · traditional IT models vs models unique to data · (Ray Wang, HBR)

Quick Revision

  • 🎯 Objective: classify how a data business makes money ➔ four data-specific models plus the traditional IT ones.
  • ⚡ Key Constraint: many DS firms reuse traditional IT models (SaaS/consulting/CRM); only four models are genuinely unique to the data world.

📝 Core

  • Business model ➔ the rationale of how an organisation creates, delivers, and captures value (economic/social/cultural).
  • Traditional IT models ➔ many DS companies fit these: SaaS, consulting, CRM (e.g. SAS = software vendor and consultancy).
  • Four data-specific models (Ray Wang, HBR):
    • Information brokering ➔ buys and sells data/information for others.
    • Information-based differentiation ➔ a differentiated service built on the data (superior reviews/range) — Amazon.
    • Information-based delivery network ➔ delivers data/information for others — Reuters, Plentisoft.
    • Information provider ➔ sells the data/information it collects — Nielsen.
  • Amazon case ➔ an “assembly line for retail”: info-based differentiation (superior reviews/range) + info-based delivery network (directs customers to marketplace retailers, provides their support/logistics).

⚖️ Core Decision Matrix

Data modelValue moveExample
Information brokeringbuy & sell others’ datadata marketplaces
Info-based differentiationbetter service built on dataAmazon
Info-based delivery networkdeliver data for othersReuters
Information providersell data it collectsNielsen

⚠️ Common Mistakes

  • 💡 Most DS firms aren’t novel business-wise ➔ they run traditional IT models (SaaS/consulting/CRM); only the four above are unique to data.
  • 💡 One firm can span models ➔ Amazon is both differentiation and a delivery network; classify by the value move, not the company.

🧠 Active Recall