Data Driven Decision Making on Pricing and Profitability

Track: Pricing & Profitability

Session Number: 2155
Date: Tue, May 15th, 2018
Time: 1:15 PM - 1:40 PM

Description:

Clocktimizer makes matter management and firm wide analytics simple. We can offer detailed data on pricing, scoping and budget monitoring at the click of a button. Our Natural Language Processing algorithms read time card narratives to support you in identifying efficiencies, quantifying improvement projects and creating data driven succession planning.

Session Type: Service Provider Demo

Body of Knowledge (BOK) Domain: Technology Management
Content Level: Advanced
Learning Objective 1: Learner will be able to:
- Understand how our Natural Language Processing algorithms can extract data from timesheets and why this presents the most accurate picture of work done in a firm.
- Construct a fee quote using our nearest neighbour algorithm; which is based on historical matters
- Identify a firm's most profitable activities
- Recognise 'low hanging fruit' - work which has a high revenue, but also highs associated costs, as offering the best opportunity for automation or streamlining.
Learning Objective 2: - Use Clocktimizer's social graphs to manage succession planning. Learners will be able to extract and identify key team members for each client to ensure each client does not have a 'single point of failure'.
- Identify profitability across a number of key areas: By matter, by seniority level, by client, by practice group etc. Learners will then be taught how to benchmark this information to test the success of innovation against profitability.
Learning Objective 3: - Learners will be able to build and manage a budget easily. Learners will identify tasks and phases associated with a matter, and assign costs to them to set the budget. They will then create their reports and dashboards to stay informed of budget use to avoid write-offs or unexpected costs.
Session Type: Service Provider Demo

Body of Knowledge (BOK) Domain: Technology Management
Content Level: Advanced
Learning Objective 1: Learner will be able to:
- Understand how our Natural Language Processing algorithms can extract data from timesheets and why this presents the most accurate picture of work done in a firm.
- Construct a fee quote using our nearest neighbour algorithm; which is based on historical matters
- Identify a firm's most profitable activities
- Recognise 'low hanging fruit' - work which has a high revenue, but also highs associated costs, as offering the best opportunity for automation or streamlining.
Learning Objective 2: - Use Clocktimizer's social graphs to manage succession planning. Learners will be able to extract and identify key team members for each client to ensure each client does not have a 'single point of failure'.
- Identify profitability across a number of key areas: By matter, by seniority level, by client, by practice group etc. Learners will then be taught how to benchmark this information to test the success of innovation against profitability.
Learning Objective 3: - Learners will be able to build and manage a budget easily. Learners will identify tasks and phases associated with a matter, and assign costs to them to set the budget. They will then create their reports and dashboards to stay informed of budget use to avoid write-offs or unexpected costs.