3
assess the robustness of different innovation options under
various scenarios. This capability allows for more robust
and resilient decision- making, reducing the likelihood of
unforeseen consequences.
MCDA could assist the mining industry by provid-
ing strategic thinking by aligning innovation selection
criteria with the company’s long-term objectives and core
values. By including sustainability considerations, such
as environmental impact and social responsibility, in the
decision-making process, mining companies can prioritize
innovations that align with their commitment to responsi-
ble mining practices. MCDA helps integrate sustainability
as a core criterion, thereby driving the industry toward a
more sustainable and socially responsible future.
Innovation projects in the mining industry often
involve multiple stakeholders, including employees, com-
munities, regulatory bodies, and investors. MCDA facili-
tates stakeholder engagement by providing a structured
framework for collecting and incorporating their prefer-
ences and perspectives into the decision-making process.
This inclusive approach brings transparency, accountability,
and collaboration, leading to greater acceptance and sup-
port for the selected innovations.
Mining companies face resource constraints, both in
terms of financial and human capital. MCDA ould assist in
optimizing resource allocation by identifying innovations
that provide the highest utility or value for the allocated
resources. By considering the trade-offs between different
attributes and their associated costs, MCDA helps maxi-
mize the return on investment and improve the overall effi-
ciency of resource allocation.
MCDA can be used as a continuous improvement
tool within the mining industry. By regularly reviewing
and updating the selection criteria and weights, compa-
nies can adapt to changing market conditions, technologi-
cal advancements, and evolving stakeholder expectations.
MCDA provides a flexible framework that allows for
iterative decision-making, ensuring that the innovation
selection process remains relevant and effective over time.
Campos, V. (2022).
THEORETICAL APPROACH TO USING
MULTICRITERIA DECISION ANALYSIS
FOR SELECTING HIGH IMPACT
INNOVATION PROJECTS
Below is the framework of the theoretical approach to using
MCDA for selecting the best option among several innova-
tion projects: (Nieto, 2020).
Definition of the Decision Problem
Clearly define the decision problem being faced, which
in this case is selecting the best R&D innovation project
among several options. Determine the specific criteria or
attributes that are relevant to evaluating these projects.
Definition of the Attributes and Weights
Identify the attributes or criteria that are important for
evaluating the R&D innovation projects. These attributes
could include factors such as economic attributes (such as
cost, time, revenue, profit), environmental, social and gov-
ernance attributes (such as safety, health, carbon emissions),
strategic attributes (such as supply risk, intensity use, etc.)
and, innovation-tech attributes, (such as safety, simplifica-
tion, smart, and other technologies).
Economic Attributes in MCDA
• NPV
• IRR
• Market
• Feasibility
• Project timeline
• Revenue
• Cost
• Profit
• Payback
• Revenue
ESG Attributes in MCDA
• Environmental
• Shareholder expectation
• CO2-e emissions
• Discharge
• Noise
• Footprint
• Sustainable
• Tailings
Strategic Attributes in MCDA
• Strategic fit
• Portfolio management
• Regulatory Risk
• Reputation risk
• Market and Business risk
• Resource requirement/Supply Risk
• Intensity use
• Scarcity
• Disruption
assess the robustness of different innovation options under
various scenarios. This capability allows for more robust
and resilient decision- making, reducing the likelihood of
unforeseen consequences.
MCDA could assist the mining industry by provid-
ing strategic thinking by aligning innovation selection
criteria with the company’s long-term objectives and core
values. By including sustainability considerations, such
as environmental impact and social responsibility, in the
decision-making process, mining companies can prioritize
innovations that align with their commitment to responsi-
ble mining practices. MCDA helps integrate sustainability
as a core criterion, thereby driving the industry toward a
more sustainable and socially responsible future.
Innovation projects in the mining industry often
involve multiple stakeholders, including employees, com-
munities, regulatory bodies, and investors. MCDA facili-
tates stakeholder engagement by providing a structured
framework for collecting and incorporating their prefer-
ences and perspectives into the decision-making process.
This inclusive approach brings transparency, accountability,
and collaboration, leading to greater acceptance and sup-
port for the selected innovations.
Mining companies face resource constraints, both in
terms of financial and human capital. MCDA ould assist in
optimizing resource allocation by identifying innovations
that provide the highest utility or value for the allocated
resources. By considering the trade-offs between different
attributes and their associated costs, MCDA helps maxi-
mize the return on investment and improve the overall effi-
ciency of resource allocation.
MCDA can be used as a continuous improvement
tool within the mining industry. By regularly reviewing
and updating the selection criteria and weights, compa-
nies can adapt to changing market conditions, technologi-
cal advancements, and evolving stakeholder expectations.
MCDA provides a flexible framework that allows for
iterative decision-making, ensuring that the innovation
selection process remains relevant and effective over time.
Campos, V. (2022).
THEORETICAL APPROACH TO USING
MULTICRITERIA DECISION ANALYSIS
FOR SELECTING HIGH IMPACT
INNOVATION PROJECTS
Below is the framework of the theoretical approach to using
MCDA for selecting the best option among several innova-
tion projects: (Nieto, 2020).
Definition of the Decision Problem
Clearly define the decision problem being faced, which
in this case is selecting the best R&D innovation project
among several options. Determine the specific criteria or
attributes that are relevant to evaluating these projects.
Definition of the Attributes and Weights
Identify the attributes or criteria that are important for
evaluating the R&D innovation projects. These attributes
could include factors such as economic attributes (such as
cost, time, revenue, profit), environmental, social and gov-
ernance attributes (such as safety, health, carbon emissions),
strategic attributes (such as supply risk, intensity use, etc.)
and, innovation-tech attributes, (such as safety, simplifica-
tion, smart, and other technologies).
Economic Attributes in MCDA
• NPV
• IRR
• Market
• Feasibility
• Project timeline
• Revenue
• Cost
• Profit
• Payback
• Revenue
ESG Attributes in MCDA
• Environmental
• Shareholder expectation
• CO2-e emissions
• Discharge
• Noise
• Footprint
• Sustainable
• Tailings
Strategic Attributes in MCDA
• Strategic fit
• Portfolio management
• Regulatory Risk
• Reputation risk
• Market and Business risk
• Resource requirement/Supply Risk
• Intensity use
• Scarcity
• Disruption