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  "documentTitle": "The Future of Procurement: Why is Technology Lagging Behind?",
  "authorId": "Kearney",
  "authorName": "ATKearney",
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  "notes": "The slide includes a table titled 'Figure 3: Selected start-ups to watch'.",
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      "text": "We estimate collectively they have raised nearly half a billion dollars in investment funding with more likely to come.",
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      "text": "Investment ($M): 0.5bn",
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      "text": "Despite the bleakness of the suite solutions, a number of procurement technology start-ups have emerged during the past few years (see figure 3). Scout burst onto the scene in 2014 with a fresh take on sourcing tools built on modern architectures and updated sourcing concepts. The sourcing functionality compares to previous systems, but it is much more intuitive, faster, and easier to use. Then, building off the analytics revolution, advanced analytics companies such as Tamr began to apply machine learning to challenges such as spend management and complexity reduction. Consequently, the once-onerous analysis of tail spend is vastly sped up and simplified, potentially unlocking tens of millions of dollars in opportunity. These companies represent the most current and advanced technologies. We estimate collectively they have raised nearly half a billion dollars in investment funding with more likely to come.",
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      "kind": "source-note",
      "text": "Source: A.T. Kearney analysis",
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      "kind": "table",
      "text": "Table of start-ups including Tamr, Bonfire, LevaData, Procurify, Concord, Scout, Xeeva, Suplari, Supplier.ai, Globality, and Chatz.ai with investment and category data.",
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      "kind": "title",
      "text": "The Revolution Begins",
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      "kind": "title",
      "text": "Figure 3\nSelected start-ups to watch",
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      "evidence": "The problem statement and strategic options suggest a cost of inaction loop",
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      "structure": "The Status Quo -> The Hidden Costs Accumulating -> The Future State of Inaction -> The Tipping Point",
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      "evidence": "The thesis headline and market landscape suggest a jobs-to-be-done loop",
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      "structure": "The Customer's Job -> Current Solutions (Hired/Fired) -> Unmet Needs -> Our Solution Fit",
      "confidence": 0.6,
      "description": "Reframe the problem around what the customer is trying to accomplish, not what they're buying"
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