Data driven product engineering
We help our customers optimize costs and increase profitability through more effective and data-driven product engineering decision-making processes
Value for customers
Even if the engineering and innovation processes of the product determine and constrain about 60% of the costs associated with it, in recent decades few companies in the industrial sector have activated dedicated programs to improve its performance. We have collaborated with industrial groups on programs to improve decision-making processes in the engineering and product development area with measurable economic results that are difficult to obtain with improvement programs in other areas.
The challenges
An advanced pricing management allows to obtain an improvement in profitability and turnover that is difficult to obtain with the most classic cost optimization initiatives.
Monetizing innovation
How we can best use data and Expert Judgment to maximize the return on investment of Product Innovation projects
How can we use the data to reduce and prevent the excessive proliferation of components and products while improving costs and value for the end customer?
Complexity reduction
Value engineering and cost reduction
How can we create a virtuous cost reduction process through value engineering by appropriately involving engineering, purchasing, and operations?
Business intelligence for engineering
How can we use the data to maximize the effectiveness of the decision-making processes of the Engineering and Product Development department?
How we help our customers
Idea generation processes (market pull / technology push)
Classification of the ideas of innocation
Innovation ideas scoring tool (qualitative / financial)
Quantitative / financial evaluation model
Design of the idea Evaluation and Approval processes
Data driven
Innovation
Product engineering capability diagnostics:
product cost reduction
innovation, value to customer
complexity management, Value Engineering
metrics and decision-making processes
project portfolio management
impact on engineering warranty
process design (As is vs To Be)
Support implementation of interventions
Product engineering process improvement
Model for determining the Technology Readiness Level
Agile Execution based on TRL increment
R&D productivity reporting and indicators
Technology readiness level & reporting Innovation
Quantitative models for the identification of opportunities
Ideas scoring tool (financial, qualitative)
End to end process design and implementation
Reporting process on economic results
Training and communication
Deployment process for periodic review
Value Engineering and product Complexity reduction
Expected results
Product cost reduction
Implementation of data-driven Value Engineering and Complexity reduction processes for continuous cost improvement
ROI of innovation projects
Qualitative / financial scoring model, reporting on the project portfolio and "agile" approach based on the Technology Readiness Level (TRL)
Metrics and decisions
Development of metrics and KPIs for engineering to improve decision-making processes with greater impact
Why Alyant
Experience : many years of experience with major players in the automotive sector or adjacent sectors on engineering process improvement projects
Data models for engineering : field implementation of analytical and predictive models to support decision-making processes for engineering
Integration : development of cross-functional projects (engineering as a service center for external and internal customers)