Management of Tech Study Guide

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Stop changing the planning in favor of Rio (the biggest brand) → losses on other brands

Distribute the nb of project like in the 3M case.

Increase the size of R&D

- They have small budget and based on % of previous year sales → No, it’s based on how much money each brand gave[a] - it’s also based on previous year sales so it’s past facing, when should be forward facing based on forecasted demand (and prioritized a bit by brand profit contribution)

- Improve the coordination between R&D and marketing / Improve communication with marketing team, stop the “throw over the wall” thing = more integration and pulling variables of demand

-They cross-train each group so they can understand and move around within groups

- Overall procedural standardization

-They can set priorities for projects and prevents risk of sending out unstable formulas in product

- Aggregate project management to choose investment strategy between groups (coordination)

- Base the budget on what they wanna be.

- Corporate should put more money in specific R&D (more than 5%)

- Pbs to centralize : brands have their specificities -- decide how much uniqueness each brand should have

Be more focused on future projects (products/processes) rather than looking backwards (like M&S they are spectators, not changing anything)

Overlap steps to gain time and efficiency rather than waiting for “what should we change?,what is not right?” before acting.

(b) More generally, what can you suggest to improve the utilization of the workforce in a knowledge-intensive job shop?

Decreasing the utilization rate of job shops

Since people from job shops are versatile, move them around so they can see the big picture / have new ideas - crosstrain

- Understand the bottleneck and allocate resources accordingly

- Reducing/ managing variability and uncertainty (product/process development needs to talk, introduce a project manager, integration of marketing/R&D, capacity cushion/buffer 20%, cross training workers, go to source or become very reactive)

- Increase capacity (increase fulltime staff, use temporary workers, improve technical support, outsource the work, allows R&D to prioritize/postpone/stop jobs, charge RIO for changes)

- Strategic performance improvements (what are the factors driving your product portfolio, RIO 60% sales 60% contribution to R&D budget, fund new projects, project allocation reflects current sales should reflect future sales)

- Outsourcing of some activities and focus on the core activity

5. (a) What are three tangible measures used to justify the investment in resource-based change?

Reduce time-to-market / Adapt to demand quicker

Adapt to competitor

Improve after-sale services

Quality improvement, less down time (=more reliable), reduce waste, economy of scale

Better product mix/variety

Tangible benefits :

Market based

Operational based

Earlier market entrance

Adapt to demand/competitors quicker (intan.?)

New capabilities

Demand volume expand

Improving customer service

Impact on production cost (economies of scale..) and IT investment

Quality, less down time, less waste

Capacity

Sustainable issues

Benefits measured by : Revenue, demand volume, actual time to market, product mix variety.

(b) What are three intangible measures?

Ability to deter/anticipate competition

Capacity to absorb/integrate knowledge gathered from experience

Security of IT system

Goodwill for being first innovator

Opportunity cost

Reputation

(c) Why may implementation of resource-based change lead to short-term deterioration in performance and why may long-term gains be limited?

Short-term deterioration:

- Training is needed

- Unpredictable events occur during the transition phase (murphy’s law)

Limitation of long-term gains

- Maximum potential reached, need to change again (?)

- Murphy’s curve (no preparation)

[pic 1]

(d) What can be done to improve the implementation of resource-based change? (You may find insights from “Beating Murphy’s Law” helpful.)

Focus on knowledge creation:

Look for the implementation difficulties (not only the final results)

See the implementation as R&D

Simulate the future results (not only on the process but also on the organization)

Estimate the risk (assume everything is gonna go wrong)

Vicarious learning

Simulation learning

Prototype