![Page 1: Administrative Data - the Statistical Potential Alan Cave Business Director, Capita](https://reader035.vdocuments.us/reader035/viewer/2022072008/56649d755503460f94a55e6a/html5/thumbnails/1.jpg)
Administrative Data - the Statistical Potential
Alan Cave Business Director, Capita
![Page 2: Administrative Data - the Statistical Potential Alan Cave Business Director, Capita](https://reader035.vdocuments.us/reader035/viewer/2022072008/56649d755503460f94a55e6a/html5/thumbnails/2.jpg)
Price and Risk
• A successful contract is based on a price that accurately reflects both parties risk judgements and appetites.
• The key dimensions of risk are:– Delivery– Cost– Legal– Reputational
![Page 3: Administrative Data - the Statistical Potential Alan Cave Business Director, Capita](https://reader035.vdocuments.us/reader035/viewer/2022072008/56649d755503460f94a55e6a/html5/thumbnails/3.jpg)
How does a bidder reach a price?
1. Understand the “As-Is”: operating model, liabilities, cost allocation.
2. Understand customer requirements and the changes/novelty involved.
3. Build a Solution, a Target Operating Model and a financial model.
4. Price the solution:– Within the customer’s cost envelope– With an acceptable return– Building in contingency for risk
![Page 4: Administrative Data - the Statistical Potential Alan Cave Business Director, Capita](https://reader035.vdocuments.us/reader035/viewer/2022072008/56649d755503460f94a55e6a/html5/thumbnails/4.jpg)
Issues in assessing and managing risk
Scenario 1: Outsourcing a well-established service (3G)
• Example: Local Authority services• Base line and improvement possibilities are clear and well-
known• Benchmark data widely available• Data is trusted
![Page 5: Administrative Data - the Statistical Potential Alan Cave Business Director, Capita](https://reader035.vdocuments.us/reader035/viewer/2022072008/56649d755503460f94a55e6a/html5/thumbnails/5.jpg)
Issues in assessing and managing risk
Scenario 2: Innovating in an already outsourced service (2G)
• Example: DWP Work Programme• Base line partially clear• Commercial model contains element of hypothesis/pilot• Benchmark data not widely available• Data is largely trusted (but typically separate sets of Admin
data)
![Page 6: Administrative Data - the Statistical Potential Alan Cave Business Director, Capita](https://reader035.vdocuments.us/reader035/viewer/2022072008/56649d755503460f94a55e6a/html5/thumbnails/6.jpg)
Issues in assessing and managing risk
Scenario 3: Initial outsourcing of a service (1G)
• Example: MoJ Transforming Rehabilitation programme• Base line clear• Commercial model rests on predictions based on modelling
the customer’s Admin data• Bidders required to make assumptions/take data on trust
![Page 7: Administrative Data - the Statistical Potential Alan Cave Business Director, Capita](https://reader035.vdocuments.us/reader035/viewer/2022072008/56649d755503460f94a55e6a/html5/thumbnails/7.jpg)
Administrative data in a commercial context
Clear strengths:• Reflects “operational reality”• Frequency and regularity• Subject to quality controls/audit
Drawbacks:• One-sided• Worries about quality• Defensiveness
![Page 8: Administrative Data - the Statistical Potential Alan Cave Business Director, Capita](https://reader035.vdocuments.us/reader035/viewer/2022072008/56649d755503460f94a55e6a/html5/thumbnails/8.jpg)
How to handle trust and uncertainty issues?
1. Price it in2. Ignore it3. Adjust over time: “True Up”
Above all: a more mature approach