6
Normalize Scores
Normalize the scores to ensure that they are on a common
scale. This step is important to eliminate any biases result-
ing from differences in the measurement scales of the attri-
butes. Different normalization methods can be used, such
as linear normalization or logarithmic normalization.
Application of Weights and Value Calculation
Apply the weights assigned to each attribute to the nor-
malized scores of the corresponding innovation project.
Multiply each attribute score by its weight to calculate
the weighted score for each attribute. Then, sum up the
weighted scores across all attributes to obtain the overall
utility or value for each innovation project.
Table 4 shows and example for three projects (A, B,
and C) with different specific weights.
Monte-Carlo Simulations and Sensitivity Analysis
Perform sensitivity analysis and Monte Carlo (MC) simula-
tions to assess the risk and impact of variations in the attri-
bute weights. From the results of MC simulations and by
adjusting the weights, you can observe how the rankings of
the innovation projects change and understand the robust-
ness of your decision. (Nieto, 2009).
Best Innovation Option Selection
Based on the calculated utilities or values, rank the innova-
tion projects from highest to lowest utility/value. Select the
project with the highest utility/value as the best option. It
is important to consider other factors such as budget con-
straints, resource availability, and organizational goals when
making the final decision.
For a mining company focusing in promoting a sustain-
able implementation of an innovation strategy to consider
executing at least one R&D innovation imitative within
each of the five innovation drivers as described in the five
‘S’ innovation model (Nieto 2019). Below is a list of inno-
vation projects for each innovation driver to be considered.
Safety Mining R&D Initiatives
Safety Mining R&D Initiatives aim to achieve an ulti-
mate safety condition in mining operations by leveraging
advanced technologies. These initiatives include the use of
virtual and augmented reality for training and maintenance,
allowing workers to simulate hazardous scenarios without
real-world risks. Remote and automated systems enable the
control of equipment from safe locations, reducing exposure
to dangerous environments. Real-time mapping and track-
ing enhance situational awareness, while real-time ground
control sensors monitor structural integrity to prevent acci-
dents. Through-the-ground communications ensure reli-
able connectivity even in deep underground settings. Rapid
borehole drilling techniques expedite emergency responses,
and biosensor applications provide real-time health moni-
toring of personnel, contributing to proactive safety mea-
sures. Table 5 shows the safety ultimate conditions.
Simplification Mining R&D Initiatives
Simplification Mining R&D Initiatives focus on achieving
a simplified optimal operational condition by streamlining
processes and reducing complexity. Implementing modular
mining systems allows for flexible and scalable operations
that can adapt to changing demands. Quality control and
quality management practices ensure consistent standards
Table 3. Score column for each attribute
Economic e es ESG g gs Strategic t ts Innovation Enablers s ss
NPV e1 #1 Environmental g1 #1 Strategic fit t1 #1 Safety innovation s1 #1
IRR e2 #2 Shareholder
expectation
g2 #2 Portfolio management t2 #2 Simplification
innovation
s2 #2
Market e3 #3 CO2 Emissions g3 #3 Regulatory risk t3 #3 Smart innovation s3 #3
Feasibility e4 #4 Discharge g4 #4 Reputation risk t4 #4 Stealth innovation s4 #4
Project timeline e5 #5 Noise g5 #5 Market and business risk t5 #5 Sustainable innovation s5 #5
Revenue e6 #6 Footprint g6 #6 Resource requirement/
Supply risk
t6 #6 Partnerships with
universities/ industry
s6 #6
Cost e7 #7 Sustainable g7 #7 Intensity use t7 #7 IP, patent
opportunities
s7 #7
Profit e8 #8 Tailings g8 #8 Scarcity t8 #8 Disruption s8 #8
Payback e9 #9 Disruption t9 #9 Scalability s9 #9
Revenue e10 #10
Normalize Scores
Normalize the scores to ensure that they are on a common
scale. This step is important to eliminate any biases result-
ing from differences in the measurement scales of the attri-
butes. Different normalization methods can be used, such
as linear normalization or logarithmic normalization.
Application of Weights and Value Calculation
Apply the weights assigned to each attribute to the nor-
malized scores of the corresponding innovation project.
Multiply each attribute score by its weight to calculate
the weighted score for each attribute. Then, sum up the
weighted scores across all attributes to obtain the overall
utility or value for each innovation project.
Table 4 shows and example for three projects (A, B,
and C) with different specific weights.
Monte-Carlo Simulations and Sensitivity Analysis
Perform sensitivity analysis and Monte Carlo (MC) simula-
tions to assess the risk and impact of variations in the attri-
bute weights. From the results of MC simulations and by
adjusting the weights, you can observe how the rankings of
the innovation projects change and understand the robust-
ness of your decision. (Nieto, 2009).
Best Innovation Option Selection
Based on the calculated utilities or values, rank the innova-
tion projects from highest to lowest utility/value. Select the
project with the highest utility/value as the best option. It
is important to consider other factors such as budget con-
straints, resource availability, and organizational goals when
making the final decision.
For a mining company focusing in promoting a sustain-
able implementation of an innovation strategy to consider
executing at least one R&D innovation imitative within
each of the five innovation drivers as described in the five
‘S’ innovation model (Nieto 2019). Below is a list of inno-
vation projects for each innovation driver to be considered.
Safety Mining R&D Initiatives
Safety Mining R&D Initiatives aim to achieve an ulti-
mate safety condition in mining operations by leveraging
advanced technologies. These initiatives include the use of
virtual and augmented reality for training and maintenance,
allowing workers to simulate hazardous scenarios without
real-world risks. Remote and automated systems enable the
control of equipment from safe locations, reducing exposure
to dangerous environments. Real-time mapping and track-
ing enhance situational awareness, while real-time ground
control sensors monitor structural integrity to prevent acci-
dents. Through-the-ground communications ensure reli-
able connectivity even in deep underground settings. Rapid
borehole drilling techniques expedite emergency responses,
and biosensor applications provide real-time health moni-
toring of personnel, contributing to proactive safety mea-
sures. Table 5 shows the safety ultimate conditions.
Simplification Mining R&D Initiatives
Simplification Mining R&D Initiatives focus on achieving
a simplified optimal operational condition by streamlining
processes and reducing complexity. Implementing modular
mining systems allows for flexible and scalable operations
that can adapt to changing demands. Quality control and
quality management practices ensure consistent standards
Table 3. Score column for each attribute
Economic e es ESG g gs Strategic t ts Innovation Enablers s ss
NPV e1 #1 Environmental g1 #1 Strategic fit t1 #1 Safety innovation s1 #1
IRR e2 #2 Shareholder
expectation
g2 #2 Portfolio management t2 #2 Simplification
innovation
s2 #2
Market e3 #3 CO2 Emissions g3 #3 Regulatory risk t3 #3 Smart innovation s3 #3
Feasibility e4 #4 Discharge g4 #4 Reputation risk t4 #4 Stealth innovation s4 #4
Project timeline e5 #5 Noise g5 #5 Market and business risk t5 #5 Sustainable innovation s5 #5
Revenue e6 #6 Footprint g6 #6 Resource requirement/
Supply risk
t6 #6 Partnerships with
universities/ industry
s6 #6
Cost e7 #7 Sustainable g7 #7 Intensity use t7 #7 IP, patent
opportunities
s7 #7
Profit e8 #8 Tailings g8 #8 Scarcity t8 #8 Disruption s8 #8
Payback e9 #9 Disruption t9 #9 Scalability s9 #9
Revenue e10 #10