The aim of these learning journeys is to explore the parables of Jesus. The project will involve Bloom's higher order thinking and will focus on a progression of skills from early to fourth level. ⢠This part of the project will be developed at sec
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Idea Transcript
Competitive Progression Theory and Service Agility: Reflections on the ”Sand Cone” Model Chao Wang, Andrea Masini Management Science and Operations Department London Business School 12th, July, 2007
The value of agility
Why “agility”? One “core” capability? For more?
What is agility?: the ability to coordinate multiple
capabilities associated with quality, delivery, cost, and flexibility (D’Aveni & Gunther 1994, Yusuf et al. 1999, Menor et al. 2001). • Business Agility: the ability of a business unit to achieve low
cost, high quality, responsive, and flexible services by inputting its resources and efforts.
Theoretical background
How to achieve agility? To be effective, competitive capabilities should be built cumulatively.
– Competitive Progression Theory (CPT) (Roth 1996) – “Sand Cone” Model (Ferdows & de Meyer 1988, 1990)
4. Flexibility 3. Cost 2. Delivery 1. Quality
A feedback model Reflection: Reflection Firms have limited resources. Does the existing capabilities base change when a new capability needs to be added?
Opportunity: Opportunity A fleet maintenance and repair company (ServCo) with
consolidated capabilities on quality, delivery, and cost needs to target new customers.
Research Question: Question How does the achievement of service flexibility affect the existing and consolidated competitive capabilities? 4. Flexibility
?
3. Cost 2. Delivery 1. Quality
Existing capabilities base
Hypotheses
Three types of flexibility •
• •
Volume: indicating the ability to handle yield variation (Field & Sinha 2005). Mix: representing the ability to respond to the required level of and the changes in the types of various services (Zhang et al. 2003). Customer: indicating the ability to respond to changes in the customer basis.
Data - Context: 86 workshops within the service company - Observation window: May 1st, 2006 – June 18th, 2006 - Data: objective data for 34,000 jobs from 33 different business customers - Unit of analysis: sub-SBU
Operationalization of Independent Variable - Flexibility (D’Souza & Williams 2000, Pagell & Krause 1999) Volume
Mix Customer
Volume Range
s.d. of number of tasks made across the seven weeks
Volume Mobility
s.d. of the weekly utilization rate of the workshop
Mix Range
s.d. of the weekly service types for each workshop
Mix Mobility Customer
s.d. of the estimated time for each type of job for each workshop s.d. of weekly number of workshops each customers deal with
Dependent Variable: DEA Model Input: Total labour hours
Business agility (multidimensional efficiency)
Output: Total number of tasks (Cost) % of on-time jobs (Quality) Average job earliness (Speed – Delivery)