Monte Carlo Simulation – GleeYM https://www.gleeym.com GleeYM offers complete risk management , PMO, Mind Mapping, Training and Digital Transformation Servces! Tue, 14 Jan 2025 03:59:32 +0000 en-CA hourly 1 https://wordpress.org/?v=6.9.4 https://www.gleeym.com/wp-content/uploads/2022/01/cropped-gleelogo-1-1-32x32.png Monte Carlo Simulation – GleeYM https://www.gleeym.com 32 32 166212591 5 Data-Driven Insights to Slash Churn and Boost Growth for Your E-Commerce Startup https://www.gleeym.com/2024/12/14/churnrate-ecommerce-startup/ https://www.gleeym.com/2024/12/14/churnrate-ecommerce-startup/#respond Sat, 14 Dec 2024 05:59:56 +0000 https://www.gleeym.com/?p=7268

In the world of e-commerce startups, customer acquisition is a critical milestone, but retaining those customers is what drives long-term growth and profitability. Many startups find themselves caught in the churn trap—acquiring customers only to lose them at a rapid rate. Understanding and mitigating customer churn is not just a survival strategy; it’s a growth accelerator.

Using Monte Carlo Simulation, one startup uncovered powerful insights about how to balance customer acquisition and retention over a 5-year period. The result? A data-driven blueprint to slash churn rates, boost growth by 60% annually, and scale up to 7,596 customers by Year 5.

Here are the 5 key insights from their journey.

Insight 1: Understand the True Impact of Churn

Churn—when customers leave your platform—directly affects your bottom line. For startups, even a small churn rate can have a compounding effect over time.

In this simulation, churn was modeled with:

  • Monthly churn rate: 5% for new customers.
  • Year-end churn rate: 20%, assuming retention improves as the customer base stabilizes.

Key Finding:

  • By Year 5, churn could account for 413 to 901 lost customers annually, as shown in the Pareto Plot for Year 5 Churned Customers. This range highlights the importance of proactive retention strategies to minimize attrition.

Takeaway:

The startup realized that lowering churn by just 5% could add hundreds of customers to their base annually, making churn reduction a top priority.

Churn Rate - gleeym

Insight 2: Leverage Data for Predictive Growth

The startup set ambitious targets:

  • 200 customers by Month 3.
  • 1,000 customers by Year-End.
  • Exponential growth to 7,596 customers by Year 5.

To meet these goals, they used Monte Carlo Simulation to model customer acquisition and churn under different scenarios. The simulation projected:

  • Median churn rate: 15% by Year 5.
  • Median customer base: 7,596, assuming steady growth and controlled churn.

Visualization:

The Trend Plot for Year-End Customers revealed the exponential growth trajectory, with a potential range of 6,000 to 10,000 customers by 2028.

Takeaway:

Modeling customer behavior allowed the startup to predict best- and worst-case scenarios, empowering them to plan for growth confidently.

Trend Chart by gleeyM

Insight 3: Churn Increases as Your Business Grows

While growth is exciting, it brings challenges:

  • As the customer base increases, the number of churned customers grows proportionally.
  • Churn rates rose from 2.67% in Year 1 to 15.18% by Year 5, even as retention efforts improved.

Key Metrics:

Year

Start Customers

Churned Customers

Churn Rate (%)

2024

0

85

2.67%

2025

3,089

363

9.17%

2026

3,927

461

11.74%

2027

5,119

601

13.51%

2028

6,612

776

15.18%

Takeaway:

Growth without retention strategies leads to customer leakage. The startup focused on loyalty programs and personalized campaigns to curb churn as the customer base expanded.

Insight 4: Retention Pays Bigger Dividends than Acquisition

Acquiring new customers is costly—retaining them is far more cost-effective. By modeling retention rates at 80% annually, the startup ensured steady growth even as churn rates climbed.

Retention Strategies:

  1. Engagement Campaigns: Tailored email and SMS reminders to keep customers active.
  2. Loyalty Programs: Rewarded repeat customers with discounts and exclusive offers.
  3. Proactive Support: Solved customer issues before they escalated into churn.

Takeaway:

Retention efforts compounded over time, significantly improving customer lifetime value (CLV) and reducing overall churn.

Insight 5: Plan for Uncertainty with Monte Carlo Simulation

Startups operate in a world of uncertainty. Will your marketing campaigns perform as expected? Will your churn rate stay within manageable limits? Monte Carlo Simulation helped this startup navigate these uncertainties.

Pareto Plot for Year 5 Churn:

  • Best Case: 413 churned customers (5th percentile).
  • Worst Case: 901 churned customers (95th percentile).

Trend Plot for Year-End Customers:

  • Median projection: 7,596 customers by 2028.
  • Variability increases over time, emphasizing the need for dynamic planning.

Takeaway:

By running simulations, the startup could account for variability and build contingency plans for both conservative and optimistic scenarios.

Pareto Chart for Year-5

5-Step Strategy to Slash Churn and Boost Growth

  1. Understand Customer Behavior:
    • Use tools like Monte Carlo Simulation to model churn and growth.
  2. Engage Customers Proactively:
    • Create personalized campaigns to keep customers engaged.
  3. Improve Retention Metrics:
    • Track Net Promoter Score (NPS) and Customer Lifetime Value (CLV).
  4. Optimize Onboarding:
    • Ensure customers see value immediately upon joining.
  5. Invest in Scenario Planning:
    • Prepare for uncertainties by modeling best- and worst-case outcomes.

Conclusion: Data Is the Path to Growth

For e-commerce startups, balancing customer acquisition with retention is the key to unlocking exponential growth. By analyzing churn rates and running simulations, this startup moved beyond guesswork to build a scalable, data-driven strategy.

The results speak for themselves: by 2028, the business achieved its ambitious goal of 7,596 customers, despite increasing churn challenges. For your startup, the lesson is clear—measure what matters, predict the future, and act decisively.

With tools like Monte Carlo Simulation and a focus on retention, you can confidently navigate the uncertainties of growth and build a thriving e-commerce brand.

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]]> https://www.gleeym.com/2024/12/14/churnrate-ecommerce-startup/feed/ 0 7268 Are Caring about the Penalty Clause in a Mega Construction Project? 3 Questions Need to be Addressed! https://www.gleeym.com/2021/02/21/penalty/ https://www.gleeym.com/2021/02/21/penalty/#respond Mon, 22 Feb 2021 00:00:10 +0000 https://www.gleeym.com/?p=2844

Construction Project - Better way to Envisage Your Project's Future. How? 4 Graphs are Enough to Illustrate!

Key Words

Construction, penalty, Delay, Contractor, Client, Owner, Construction Project, Project Delivery, Project Controls, Brown Field, Green Field, Cost Estimates, Schedule, Integrated Cost Risk Analysis, Risk Register, Execution, Planning, Remote Area, Skilled Labor, Material Handling, Bulk Material, Construction Equipment

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QUANTITATIVE RISK ANALYSIS

Summary

Delays in construction projects can lead to hefty penalties. These cost implications shouldn’t be overlooked and should be planned for in a variety of ways by both contractors and subcontractors. The importance of understanding and planning for these delays shouldn’t be underestimated, considering that contractors and subcontractors are often the ones responsible for paying the penalties. By understanding the consequences of delays, you can work to prevent those delays and avoid paying the penalties!

Read article on Project Cost and Risk analysis: 

https://www.gleeym.com/2021/02/16/accessroad/

Case Study

Access Road Construction Project that is required to be done well before commencing process plant construction. The project schedule, schedule and cost risk analysis have already been discussed in the previous article.

As per the penalty clause in the contract, $5,000/day penalty will be imposed to the contractor in case of delay for each day after the target date. Interestingly, there is no cap on penalties.

Top Risks

The top identified risks are:

  1. Flash Flood
  2. Delay in Delivery of Material
  3. Unavailability of Skilled Labor

 

Is it important to focus on Access Road Construction for mega Complex remote project? 4 Figures Depict a Complete Story!

Important Consideration

The construction industry is a high-risk, high-reward industry. It’s important for builders, contractors, and subcontractors to have a thorough understanding of the full cost implications of delays in construction projects. Understanding the potential penalties for delays can help your business plan better and potentially reduce your overall cost.

Construction delays can be a result of many different factors, but they are rarely the fault of the contractor doing work. The best way to avoid being placed in that situation is to make sure your project is documented with proper project controls. One of the factors to consider when maintaining project controls is the role that cost plays. It’s hard to estimate cost without knowing the impact of the delay you’re facing, which is why it’s so important to analyze the cost risks before projects begin. It’s also vital to integrate the risk analysis into your schedules and plans so that you can have well-executed plans that are also cost conscious. By making sure you understand cost implications before you plan, you can be sure that you have a plan that works well for your business!

Risk assessment for a mega complex construction project-www.gleeym.com/qra
Pic. 1 - Risk Assessment for Mega Complex Projects

Delays can happen to anyone who’s involved in construction projects. Contractors, subcontractors, and builders are required to understand the cost implications of delays. Knowing the penalties associated with uncompleted projects can provide valuable insight into how much money is available to complete a project. If you’re involved in a construction project, you should be aware of the different types of penalties that may be implemented. The most notable of these penalties are completion delays, mobilization delay, and liquidated damages.

Construction risk assessment-www.gleeym.com/qra
Pic. 2 - Construction Risk Assessment Services by GleeYM

Project Scenario

Project complete target date is 26-8-2021 with the cost estimates of $9 M.

The project owner put a penalty clause that if the project delays after the contractual deadline i.e., 26-9-2021, then there will be a penalty of five thousand ($5,000) dollars per day.

This analysis provides an equal opportunity to the client and the contractors including subcontractors to revise the schedule accordingly and negotiate the timelines and the budget.

Why to develop a model and run a Monte Carlo simulation? The simple answer is to forecast your project execution while planning in present.

QUANTITATIVE RISK ANALYSIS

There are three important questions that can be addressed for a client and a subcontractor:

  1. What are the chances that the project schedule will be delayed, and cost overrun?
  2. What will be the 50th percentile for a penalty in case of project delay?
  3. What will be the probabilities of occurrence of different possible outcomes for a penalty?

Quantitative Risk Analysis

GleeyM Offer services to identify risks and perform Quantitative Schedule Risk Analysis (QSRA) and Quantitative Cost Risk Analysis (QCRA) for mega complex projects!
Click Here
Probability distribution graph by www.gleeym.com/qra
Pic. 3 - Probability Distribution for a Project Schedule

There is 50% (mean) chance that project will be delayed by 62 days. Furthermore, there is 80% chance that project will be delayed by 85 days.

Project cost overrun distribution graph by www.gleeym.com/qra
Pic. 4 - Probability Distribution Graph for a project Cost

There is 50% chance that the project cost overrun will be $4.474 M. Whereas cost overrun will be $3.194M between P50 – P80.

Penalty

Penalty S-Curve by www.gleeym.com/qra
Pic. 5 - Penalty S-Curve

It’s crystal clear that based on the current schedule and mapped uncertainties and risks; the penalty will be substantial.

As per the contract, the penalty will be $5,000 per day. Therefore, there is a 50% chance that the penalty will be $160 K in case of project delay beyond the contractual deadline of 26-9-2021.

What if a project delays further? Then from a distribution graph, there is an 80% chance that the penalty will be $325 K.

The question is what will be the monetary benefit to the contractor? How to address it while negotiating the contract and mitigate plans during the project planning? In case of delay, will there be an impact on CAPEX? Will there be an impact on OPEX?

Kindly give your comments and like our articles for more updates!

Contact us for decision making under uncertainty services!

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Conclusion

Integrated risk analysis is an equally important for both Client and Contractor. Risk Based Decision Making is required to demonstrate ALARP/ALARA. By incorporating what if analysis in ITB, contracts and planning will definitely help to forecast project health and EVM.

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]]> https://www.gleeym.com/2021/02/21/penalty/feed/ 0 2844 Is it important to focus on Access Road Construction for mega Complex remote project? 4 Figures Depict a Complete Story! https://www.gleeym.com/2021/02/16/accessroad/ https://www.gleeym.com/2021/02/16/accessroad/#respond Tue, 16 Feb 2021 18:56:01 +0000 https://www.gleeym.com/?p=2646

Real Estate Development Project - Better way to Envisage Your Project's Future. How? 4 Graphs are Enough to Illustrate!

Keywords

Access road construction, Mega complex project, Construction project, Schedule delay, Cost overrun, Sensitivity analysis, Uncertainty, Risks, Weather, Flash flood, Energy, Oil & Gas, Mining, Monte Carlo simulation, What if analysis, Distribution graph, Cost risk analysis, Risk drivers, Schedule risk analysis, Integrated risk analysis

Summary

Energy and mining projects are complex and mostly being executed in remote areas. Site accessibility, weather, uneven terrain, and mobility are the factors that make it more difficult to execute remote area projects. After asset acquisition and getting all necessary permits, the construction of an access road to actual site area is a topmost priority.

Flash flood is unpredictable and can be showstopper in hilly terrain. Analyzing the impact of flash flood, using Monte Carlo simulation, helps to examine the various scenarios and plan mitigation actions to minimize the risk.

Case Study

The construction of access roads is an extremely important that needs to be done at the right time. Any delay in construction can delay the site access and mobilization of team and equipment for field development, and It also needs to be done with the best equipment and materials available, keeping in mind the specific needs of the client.

Flash Floods are unpredictable. Mostly, water follows its path, but it changes its direction depending upon the water quantity and pressure, etc.

Project Schedule

Level I project schedule is shown in fig. 1:

Level I Schedule developed by Gleeym for schedule and cost risk analysis
Fig. 1- Level 1 Schedule

Uncertainty and Risk

There can be a long list of  risks but considered only three (3) top risks.

  1. Flash Flood – Recurring flash flood from May to Sep to hamper Access Road Construction and Plant site.
  2. Delay in delivery of Bulk Material to site
  3. Unavailability of Skilled Labor

Risks were mapped to the activities along with the uncertainties.

Monte Carlo Simulation

After schedule check, mapping uncertainties and risks to schedule activities ran the Monte Carlo Simulation. The “Distribution Graph” is showing the results for a schedule in fig. 2:

Access Road S curve performed by GleeYM
Fig. 2 - Distribution Graph (S Curve) for a Schedule

With uncertainties and risks, the chances of meeting target date are almost 0%. The distribution graph shows that there will be a 50% (mean) chance that the project will be completed on 22-10-2021 i.e., 57 days.

What about the time-phased cost? The “Distribution Graph” is showing the results for a cost in fig. 3:

Time phase distribution graph for cost by Gleeym
Fig.3 - Distribution Graph (S Curve) for a Cost

With uncertainties and risks, the chances of meeting target estimated costs are almost 3%. The distribution graph shows that there will be 50% (mean) chance that extra cost will be $ 1,445,705. Furthermore, there will be an 80% chance that total project cost will be around $11.72 M.

Probability Cash Flow performed by Gleeym
Fig. 4 - Probabilistic Cash Flow (PCF)

What if to visualize the impact of Flash flood to schedule only? The “Distribution Graph” is showing the impact of Flash flood to a schedule in fig. 5.

Analyzing impact of single risk to a schedule. What if analysis
Fig. 5 - What if Analysis with Flash Flood Risk Only

With only Flash flood risk, the chances of meeting target date are almost 0%. The distribution graph shows that there will be 50% (mean) chance that schedule overrun will be 29 days. Furthermore, there will be an 80% chance that project completion date will be 29-10-2021 i.e., 34 days.

 While access roads can be constructed by any means necessary, it is much more cost-effective to use specialized contractors trained in their construction. Each contractor has specific standards that must be met before they begin any work.

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QUANTITATIVE RISK ANALYSIS

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Conclusion

Access roads are crucial for any oil and gas project, not just for safety but also to allow construction equipment to enter the site, move materials, and complete the project. 

This is a story of a project that will be started out with a big dream and ended with great success. Nothing is easy; everything is challenging, but the results will be rewarding.

Question

Question: What if to build a bridge to over come the impact of a Flash Flood?

 

Answer: I will discuss it in the next article.

 

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]]> https://www.gleeym.com/2021/02/16/accessroad/feed/ 0 2646 Digital Product Development and Decision Making Under Uncertainty https://www.gleeym.com/2020/10/20/digitalproduct/ https://www.gleeym.com/2020/10/20/digitalproduct/#respond Wed, 21 Oct 2020 03:05:26 +0000 https://www.gleeym.com/?p=1961

Digital Product Development and Decision Making Under Uncertainty

Digitization is dominating in this era of 2nd machine age. A webinar. Worth watching it. Isn't?

The failure rate is high in case of product Development. Technology, competitors, and market dynamics are the key factors, but one can’t ignore cost and schedule.
Cost and schedule model development is the starting point to plan the development of a digital product.
Whether it’s agile, scrum, or waterfall, planning is utmost to avoid financial loss.

@RISK helps to model uncertainty to cost and schedule. @RISK has the capability to analyze the schedule without using any scheduling software and apply uncertainty.

Whether it’s agile or scrum or waterfall methodology, developing schedule and cost estimate are essential.  

 

<div id=”wi105″><div class=”sq_wiki_content” style=”position: relative;clear: both;background: white;font-size: 14px;color: #333;max-width: 500px;margin: 5px auto 5px auto;padding: 13px;border: 1px solid #DDD;-webkit-box-shadow: 0 1px 0 #DDD;-moz-box-shadow: 0 1px 0 #ddd;box-shadow: 0 1px 0 #DDD;”><a id=”w_0″ class=”sq_wiki” href=”//en.wikipedia.org/wiki/Decision_theory” title=”Decision theory” style=”display: block;font-weight: 700;color: #0074B7;line-height: 1.4em;margin-bottom: 5px;text-decoration: none;”>Decision theory</a><div class=”sq_wiki_text” style=”font-style:italic;color: #333;”>re-evaluation of what useful <span class=”searchmatch”>decision</span>-<span class=”searchmatch”>making</span> requires. The area of choice <span class=”searchmatch”>under</span> <span class=”searchmatch”>uncertainty</span> represents the heart of <span class=”searchmatch”>decision</span> theory. Known from the 17th</div></div></div><div><br style=”clear:both” /></div>

<a href=”https://www.gleeym.com/2021/02/11/5waysrisk/” title=”5 Ways Risk Management Software Can Help Your Business. Are You Still Not Considering Risk Software?” style=”font-style:italic;color: #333;”>https://www.gleeym.com/2021/02/11/5waysrisk/</a>

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Capital Project Petrochemical Process Plant, IRR, and NPV Analysis – Webinar

Digital product development and decision making under uncertainty - www.gleeym.com/qra
Pic-1 Digital Product Development
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GleeyM Offer services to identify risks and perform Quantitative Schedule Risk Analysis (QSRA) and Quantitative Cost Risk Analysis (QCRA) for mega complex projects!
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]]> https://www.gleeym.com/2020/10/20/digitalproduct/feed/ 0 1961 Capital Project Petrochemical Process Plant, IRR, and NPV Analysis – Webinar https://www.gleeym.com/2020/08/25/capitalproject/ https://www.gleeym.com/2020/08/25/capitalproject/#respond Tue, 25 Aug 2020 22:10:20 +0000 https://www.gleeym.com/?p=1607

Capital project for the petrochemical process plant (downstream) is slightly different from other capital projects. It requires estimating Total Installed Cost (TIC) plus Owner cost in order to find the complete project cost. Cost estimation for petrochemical process plant is comprised of equipment specification and definite plant facility information.

In this case study, there are 2 products that will be sold in two regions. The price strategy is different so the IRR and NPV will be calculated for base case and under uncertainties and risks. Then we’ll compare the IRR and NPV under different scenarios.

Also visit following link to watch recorded webinar

Digital Product Development and Decision Making Under Uncertainty

Petrochemical plant project management - www.gleeym.com/qra
Pic-1 Project Management
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https://www.gleeym.com/qra/ – for services detail

 

Quantitative Risk Analysis

GleeyM Offer services to identify risks and perform Quantitative Schedule Risk Analysis (QSRA) and Quantitative Cost Risk Analysis (QCRA) for mega complex projects!
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Unique Services for Software Selection and Implementation

GleeYM can help you with a valuable service to pick and incorporate risk management software for decision making and meeting strategic goals!
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Want to tell your story in a creative and memorable way? Well, the GleeYM can help you.
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]]> https://www.gleeym.com/2020/08/25/capitalproject/feed/ 0 1607 Integrated Cost and Schedule Risk Analysis (IRA). Why? 5 visuals explain it! https://www.gleeym.com/2020/03/12/ira/ https://www.gleeym.com/2020/03/12/ira/#respond Thu, 12 Mar 2020 15:42:02 +0000 https://www.gleeym.com/?p=1423

Summary

In Oil & Gas industry projects are always complex whether onshore or offshore. Remote locations, site access, communities, resource constraints and long lead items (LLI), etc. can be challenging to execute the project. Performed schedule and cost risk analysis with uncertainty using Monte Carlo simulation for Condensate Process and Storage Facility Project. 

Developing a schedule model for a level-I schedule is challenging and time-consuming. Then level-II & level-III schedule models will take more time and effort. After developing the model, it is a common understanding to use “index finger” to run simulations and that’s it. Although it’s required to run simulations many times to analyze the data and spread of the distribution. Adding time-dependent cost plays an important role in displaying the Schedule –cost Joint confident level (JCL). 

It is more challenging when schedule using different calendars and assign weather probabilistic calendar to one specific activity. Developing a schedule and cost stochastic model for risk analysis using Monte Carlo simulation requires time to work with key stakeholders including planners. Activity links also play a vital role in output.

visit www.gleeym.com/qra for more details

Keywords

Oil & Gas, Condensate, Processing Facility, Schedule, Cost, Level -1 Schedule, JCL, Risk, Risk Register, Quantitative, Qualitative, Quantitative Schedule Risk Analysis (QSRA), Quantitative Cost Risk Analysis (QCRA), Integrated Cost & Schedule Risk Analysis (IRA), Probability distribution, Cumulative probability Distribution, Monte Carlo Simulation (MCS) , Iteration, Uncertainty, Data, Data Analysis, data gathering, Calendar, Construction, Engineering, procurement, FEED, Resources, Resource Risk, 

Project Schedule for Condensate Storage Facility

Schedule risk analysis (SRA) helps to analyze the uncertainty in the project schedule using Monte Carlo Simulation. Deterministic schedule duration and finish date don’t provide enough information to answer the following questions:

  1. What is the probability of completing the project on the target date?
  2. What if the predecessor of an activity finishes late?
  3. What is the eighty (80%) chance of finishing the project?

SCR scope is:

  1. Schedule Risk Analysis (SRA) to analyze uncertainty
  2. Correlating the activities
  3. Probabilistic Branching
 

Level – I schedule is required to perform cost and schedule risk analysis during the feasibility or initial stage of the project. Level – I schedule is given with cost estimates below:

Level Schedule for Integrated cost and schedule risk analysis. www.gleeym.com
Pic 1 - level - I Schedule

Project Uncertainty and Risk

uncertainty to project activity can be a result of lack of information, sudden market up and down, inflation and inaccurate estimation etc. 

Following risk events has been identified after risk workshop with key stakeholders. risk management is an iterative process and new risks are identified during the complete project life cycle.  List of identified risk is:

Pic 2 - Schedule Risk
Cos risk - www.gleeym.com
Pic 3 - Cost Risk

Quantitative & Schedule Risk Analysis

Cost and schedule risk analysis is performed using Monte Carlo simulation. cost and schedule risks are linked to activities. Activities are correlated to avoid merge biased. It is very important to re-run the simulation and visualize the result. Before running simulation perform checking:

1- Schedule activity relationship and linkage.

2- Check for any soft and hard constraint. 

3- validate cost estimate.

4- Resource allocation, resource over allocation and resource leveling.

5- Project calendar(s) and linking of calendar to project activities.

6- It is recommended to perform DCMA 14 points analysis to validate the schedule.

Results are:

Probability Density Chart - www.gleeym.com
Pic 4 - Quantitative Schedule Risk Analysis Results
S curve - ww.gleeym.com
Pic 5 - Quantitative Cost Schedule Risk Analysis Results

Joint Confidence Level (JCL) is an integrated uncertainty analysis of   joint cost, schedule, uncertainty and risk. It helps to visualize schedule and cost results to make decision under uncertainty. 

Joint Confidence level for cost and schedule - ww.gleeym.com

Conclusion

Integrated Cost and Schedule Risk (IRA) is performed to analyze the complete project scenario as a whole with associated uncertainty and risk. It also helps to validate the project estimates and budget. It also useful to calculate contingency reserves to manage risks.

Thank You

@RISK

]]> https://www.gleeym.com/2020/03/12/ira/feed/ 0 1423 Decision Tree Analysis for Making Decision Under Uncertainty https://www.gleeym.com/2020/03/06/decisiontree/ https://www.gleeym.com/2020/03/06/decisiontree/#respond Fri, 06 Mar 2020 18:03:26 +0000 https://www.gleeym.com/?p=1291

Why Decision Tree Analysis?

Product Development:

Before discussing anything on product development let us discuss what is the product? Precisely, a product is ‘Any Thing or Things produced’. More precisely, as per engineering and manufacturing perspective, products are purchased as a raw material and sold as finished goods. In a real world, Product can be tangible or intangible.

Typically, either conceiving a design using CAD/CAM tools or reverse engineering is practiced as the best methods for a product development. Although these either conventional processes save time and cost to a launch product, but because of poor product feasibility and financial analysis product fails earlier before meeting the foresee financial gains. So what needs to be followed to develop the product? Are designers really following the correct path to develop the product? Do designers ever think to follow Product Life Cycle tools & techniques to achieve optimum solutions? What are the significance of following Product Life Cycle phases in terms of cost, efficiency, quality, reliability, durability, productivity and much more? It requires a lengthy topic to cover all answers to these questions. In brief Product life Cycle and its significance are described in the next section.

Product Life Cycle:

Traditionally, it is deemed to visualize the product life cycle with engineering perspective only as shown in figure-1:

Free trade, rapid product evolution and increase demand for a cheap product have changed the way to product development concept and visualization. In a broader spectrum, product Life Cycle is a process from product initialization to product sales & marketing.  Even today it covers CRM (Customer Relationship Management).

Product Life Cycle covers:

  • Introduction
  • Growth
  • Maturity (Where Product gets maximum penetration in the market)
  • Decline

Decline phase is also referred to as the evolution phase where the shift of technology or advancement in existing product may occur. For example, VCR was very popular during 90’s and now it has been replaced by the DVD player.

 

Pic 1 - Product Life Cycle
Pic 2 - Product Life Cycle

Decision Tree:

Decision Tree Analysis is widely used for product selection, alternative process selection and cost-benefit outcomes, etc. Decision Tree is one of the best quantitative decision-making methodologies. It helps to calculate the Expected Monetary Value (EMV).

                                                                           EMV = P X I

(Where P refers to probability and I refers to Impact)

Decision Tree is required to construct from left to right with all possible alternatives. Then put all the possible outcomes of each alternative. Decision and chance node are a constituent part of it. It is important to know that the sum of the probability of each alternative at a chance node should not be greater than 100% of 1 (0-1). The figure given below illustrates a basic concept of a Decision Tree.

 

Pic 3 - Basics of Decision Tree

Decision Tree Analysis for Decision Making – Case Scenario:

In context to an earlier discussion, the right decision is important to achieve product objectives in a shorter time with minimum efforts. So I am going to discuss a real case scenario.

Company XYZ* decided to setup a manufacturing and assembling plant. They had available capital of more than $ 110 million. One of the directors of the company was a bit shaky to invest this amount because of the economic crunch, inflation, rapid trend changes, variety of similar products and decreasing buying capacity of the customers.

Therefore, company Top management decided to have an alternative solution and pick the best one on the basis of Quantitative Risk Analysis. It was decided to go with Decision Tree analysis along with other Quantitative Risk Analysis methodologies.

After initial assessment and research following data was obtained.

Data Sheet:**

  • Production:

Units/Day                    =                      3,000

Units/Month                =                      78,000

Units/Year                   =                      936,000

Units for 5 Year           =                      4,680,000

  • Cost***

Unit Price                    =                      $ 40

Unit Price excluding GST

(Ex Factory)                 =                      $ 25.70

Unit Cost                     =                      $ 13.70

Unit Profit                   =                      $ 12

  •  Internal Rate of Return (IRR) and Net Present Value (NPV)

As narrated earlier, factors that were taken-in-account for making right decision:

  • Economic Conditions
  • Capital In hand
  • Cash Flow
  • Loan Required
  • Interest Rate
  • Market Condition
  • Competitors etc.
Table-1: Setup Cost

Development of Decision Tree:

After thorough analysis, there were five proposed options to choose the optimum one. Options were:

  • Complete Product Development along with Sales and Marketing
  • Product Design
  • Prototyping
  • Production
  • Sales and Marketing

Solution one was a complete product development from product initialization to sales and marketing. Other options were product design, prototyping, production and Sales and Marketing respectively. The goal was to get maximum profit by spending less capital while catering other internal and external Constraints as described in the last paragraph of section-4. Collapsed Decision Tree is illustrated in figure 4.

Incomplete product development, a risk of financial loss was greater because of substantial capital as well as production costs.

Development of Decision Tree

                                                  Figure-4: Development of Decision Tree

Complete Decision tree

                                                   Figure-5: Complete Illustrated Decision Tree

 

Outcome of Decision Tree:

After analyzing Decision Tree got the following results. Table -2 illustrates Arrival Probability (This is the probability that this decision encountered, assuming you followed all the optimal choices.) and Benefit of Correct choice (This is the difference of expected values between the optimal choice and the worst choice for this decision.).

Outcome of Decision Tree:

After analyzing Decision Tree got the following results. Table -2 illustrates Arrival Probability (This is the probability that this decision encountered, assuming you followed all the optimal choices.) and Benefit of Correct choice (This is the difference of expected values between the optimal choice and the worst choice for this decision.).

Optimal Choice

Arrival ProbabilityBenefit of Correct Choice
Sales & Marketing100.0000%

     $ 31,173,826.80

                                                                   Table-2: Decision Table

 

Figure-6: Optimal Tree

‘Probability Chart’ and ‘Optimal Tree’ clearly supports the decision. The probability chart indicates the probability of the possible outcome of any decision. Figure-7 indicates that outcome for complete development and Sales and marketing in major. Graphically, it is evident, a possibility of financial loss with low and normal (medium) efforts to market and sell the Juicer Blender while aggressive generation revenue of more than $ 30 million in six years with marketing and sales only.

Figure-7: Probabilities for Decision Tree
Figure-8: Cumulative Probabilities for Decision Tree

Conclusion:

Expected Monetary Value (EMV) helped to select optimal part of Decision Tree. By sticking to Sales and Marketing only, the risk to financial loss minimized with a great opportunity to concentrate on one area only.

*Name of the company is not displayed as per request.

** Only shown relevant data.

Thank You

@RISK

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