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Home Artificial Intelligence

Create Your Provide Chain Analytics Portfolio to Land Your Dream Job

Admin by Admin
April 1, 2025
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Provide chains are below stress like by no means .

From climate-driven disruptions to geopolitical shifts, companies should adapt to rising prices, new commerce obstacles and rising sustainability calls for.

On this new world the place provide chains face uncertainty, Provide Chain Analytics is crucial to maintain resilient operations.

Samir, are you able to advise me on the best way to construct a provide chain analytics portfolio with precise initiatives?

Since publishing my first publish on In the direction of Information Science on August fifth, 2020, I’ve regularly acquired this query from readers on LinkedIn or YouTube.

On this article, I’ll share my perspective—after 9 years within the business—on how I might use my Provide Chain Analytics Cheat Sheet to construct a portfolio if I have been beginning out as a junior knowledge scientist.

The Provide Chain Analytics Cheat Sheet

What’s Provide Chain Analytics?

Let’s begin by defining the phrases we use.

Provide Chain Analytics refers to a set of instruments and methodologies used to extract insights from knowledge throughout all processes within the worth chain.

Methods of a Provide Chain — (Picture by Samir Saci)

As an example, a retail firm could use:

  • An ERP to handle procurement, finance and gross sales
  • A Warehouse Administration System to handle its distribution centres
  • A Transport Administration System to handle inbound and outbound freight
4 varieties of Provide Chain Analytics to Reply Questions — (Picture by Writer)

As a Provide Chain Resolution Supervisor and Information Scientist within the logistics business, I’ve used analytics in worldwide initiatives to design and optimize provide chain options.

I’ve shared many of those methodologies and instruments in over 75 articles printed on In the direction of Information Science.

I’ve compiled them into this concise and complete Provide Chain Analytics Cheat Sheet.

Screenshot of the Provide Chain Analytics Cheat Sheet together with 70+ case research: Hyperlink – (Picture by Samir Saci)

What’s Contained in the Provide Chain Analytics Cheat Sheet?

Whether or not you wish to scale back distribution prices, decrease your organization’s environmental impression, or maximize profitability, you’ll discover the solutions to your questions right here.

How Can Analytics Assist Enhance Profitability?

Information Analytics to Increase Enterprise Profitability

The primary part of the cheat sheet is about knowledge analytics for Enterprise Technique.

Information Analytics for Enterprise Technique — (Picture by Samir Saci)

It consists of sensible case research on the best way to use knowledge to assist enterprise executives of their strategic decision-making.

As an example, the sequence of articles, “Enterprise Planning with Python”, is predicated on an actual instance of a enterprise managed by my good friend.

Instance used within the Enterprise Planning with Python articles — (Picture by Samir Saci)

“We’ve to refuse orders as we don’t have sufficient money to pay suppliers for inventory replenishment.”

I constructed a simulation mannequin primarily based on this perception to assist him perceive weaknesses in his worth chain and uncover development alternatives.

They illustrate how one can add worth to small, medium, and enormous enterprise homeowners.

What About Optimizing Provide Chain Operations?

Provide Chain Analytics for Logistics Operations

Having spent years designing, monitoring, and optimizing provide chain options, I’ve compiled many case research targeted on warehousing and transportation operations.

Part of Logistics Operations Optimization — (Picture by Samir Saci)

On this part, most case research are primarily based on an precise reengineering mission I’ve performed in Asia or Europe.

Nation Supervisor: “Samir, we have to scale back warehousing prices by 15% if we wish to renew the contract with the retail firm XXX.”

They concentrate on optimizing a particular course of in a warehouse (order preparation, value-added providers) or transportation operations (routing, scheduling).

Go to the closest warehouse and ask: ‘What are your issues?’ You might be certain they may discover some for you.

Right here’s the best way to get began:

  1. Overview the case research to know the issue assertion and the answer.
  2. Pull the supply code from my GitHub repository.
  3. Search for the same drawback in your organization
  4. Adapt the code to construct an answer to your particular drawback

The code is normally a easy Python script or a jupyter pocket book that may be simply tailored.

What if you wish to have a higher impression? Deal with a circulation optimization.

Information Analytics for Provide Chain Optimization

The primary driver of the reengineering initiatives I’ve performed was price.

Examples of Enterprise Indicators alongside the worth chain — (Picture by Samir Saci)

Normally, prospects tracked logistics prices, i.e. the proportion of turnover spent on logistic operations.

Due to this fact, we wanted to seek out options (as a third-party logistic service supplier) to cut back this proportion with out impacting our profitability.

What if we delivered to the U.S. East Coast from a warehouse in Charlotte?

The options offered within the earlier part are too localized. We have to take a step again and think about circulation optimization.

Examples of Provide Chain Optimization — (Picture by Writer)

These case research concentrate on the optimization of products circulation utilizing

  • Replenishment guidelines and forecasting algorithms to optimize stock
  • Linear/Non-Linear programming to match the provision with demand on the lowest price
  • Statistical instruments for diagnostic and enchancment of particular processes

For some case research, I’ve deployed the fashions in an online software developed for my startup, LogiGreen.

LogiGreen App publicly accessible — (Picture by Samir Saci)

The demo model is publicly accessible so that you can check the fashions; extra info right here.

What about sustainability?

If you wish to assist the inexperienced transformation of your organization, I’ve some examples for you.

Provide Chain Analytics for Sustainability

Since my first mission targeted on sustainability, I used to be satisfied that inexperienced transformation was just like provide chain optimization.

Sustainable Provide Chain Optimization — (Picture by Samir Saci)

Due to this fact, yow will discover 17 examples of optimization options utilizing this method to reduce CO2 emissions or useful resource utilization.

Provide Chain Sustainability Part of the Cheat Sheet — (Picture by Samir Saci)

I additionally determined to cowl the reporting facet of sustainability with analytics for Life Cycle Evaluation, CO2 emissions calculations or ESG reporting.

For those who want assist getting began with sustainability initiatives, you’re lined.

Now It’s Your Flip to Construct!

For those who want a extra detailed presentation of the cheat sheet, try this quick YouTube tutorial.

Within the subsequent part, I’ll share how I might method constructing a portfolio if I have been a junior engineer—or somebody transitioning into analytics—seeking to land a job or freelance mission.

Beginning your Analytics Portfolio

Let’s assume I’m a junior knowledge scientist aiming to hitch a significant retailer’s Provide Chain Analytics staff.

I wish to begin a mission to showcase how I can use my expertise to assist retailers enhance their service and scale back prices.

Recommendation 1: Begin with a Easy Mission

For many firms, knowledge maturity in provide chain departments may be very low.

Which means the implementation of superior (and complicated) algorithms might be very difficult.

Due to this fact, I might concentrate on:

  • Delivering enterprise worth (visibility, insights, diagnostics)
  • Clean consumer expertise of your product or evaluation

Due to this fact, I might decide the subject of ABC Evaluation and Product Segmentation.

My Article titled Product Segmentation for Retail with Python – (Picture by Writer)

This text offers a number of examples of research to phase merchandise primarily based on their demand variability and contribution to the turnover.

Pareto Chart generated with Python – (Picture by Samir Saci)

The article features a hyperlink to a GitHub repository with a Jupyter Pocket book containing all the required code.

Recommendation 2: Add Enterprise Worth

My articles at all times use generic dummy knowledge to feed the algorithms and visuals generated.

You may enrich this knowledge by adapting it to the business you’re focusing on.

  • Style retailers normally have seasonality and complicated grasp knowledge
  • Cosmetics product classes are a necessary demand driver that may have an effect on the outcomes of your forecast engine

Earlier than leaping into the code, present which you can take possession of the case examine and adapt it to your imaginative and prescient of the issue to resolve.

Recommendation 3: Code Refactoring and Packaging

My GitHub code is usually within the type of Jupyter Pocket book or standalone Python scripts.

It is a nice alternative for our junior knowledge scientist to indicate that he can package deal the code into an API and even construct an online software round it.

Certainly, at the moment knowledge scientists are anticipated to ship their fashions in a type prepared for productization.

Think about studying about script packaging, Docker containerization, and API growth.

Recommendation 4: Enhance the UI and add insights

Bear in mind, your expertise will probably be judged by the impression of the analytics merchandise you design and deploy.

Due to this fact, don’t hesitate to enhance the outputs and insights of the fashions shared in my cheat sheet.

It is a wonderful alternative to ask your colleagues in provide chain operations how these instruments can assist them.

  • What KPIs are they monitoring?
  • What sort of insights do they lack to pilot their operations?

From right here, this case examine is yours to make your individual.

For those who observe these steps, your portfolio is not going to be a replica of my GitHub repository however a mirrored image of your expertise and how one can impression companies.

That is exactly what I did after I constructed the demo model of the LogiGreen Apps.

Screens of the ABC Evaluation Module: Hyperlink – (Picture by Samir Saci)

The demo model is publicly accessible so that you can check the fashions and get inspiration: extra info right here.

I’m trying ahead to seeing your model of it!

Conclusion

I hope this temporary introduction to the cheat sheet has helped make clear how one can begin constructing your analytics portfolio.

Updates Part of the Analytics Cheat Sheet – (Picture by Samir Saci)

Don’t hesitate to bookmark this cheat sheet as I’ll replace it every time a brand new content material is printed.

I wish to use this text and the YouTube video as a discussion board to gather your suggestions or questions.

Don’t hesitate to make use of the video’s remark part to ask questions!

You probably have used any case research for a few of your initiatives, I might be completely satisfied to be taught extra concerning the outcomes.

About Me

Let’s join on Linkedin and Twitter; I’m a Provide Chain Engineer utilizing knowledge analytics to enhance Logistics operations and scale back prices.

For consulting or recommendation on analytics and sustainable Provide Chain transformation, be at liberty to contact me by way of Logigreen Consulting.

Samir Saci | Information Science & Productiveness
A technical weblog specializing in Information Science, Private Productiveness, Automation, Operations Analysis and Sustainable…samirsaci.com



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