Administrative Data - the Statistical Potential

1. Administrative Data - the Statistical Potential Alan Cave Business Director, Capita

2. 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

3. How does a bidder reach a price? • Understand the “As-Is”: operating model, liabilities, cost allocation. • Understand customer requirements and the changes/novelty involved. • Build a Solution, a Target Operating Model and a financial model. • Price the solution: • Within the customer’s cost envelope • With an acceptable return • Building in contingency for risk

4. 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

5. 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)

6. 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

7. 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

8. How to handle trust and uncertainty issues? • Price it in • Ignore it • Adjust over time: “True Up” Above all: a more mature approach