Create Your Provide Chain Analytics Portfolio to Land Your Dream Job

Provide chains are beneath strain like by no means .

From climate-driven disruptions to geopolitical shifts, companies should adapt to rising prices, new commerce boundaries 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 right way to construct a provide chain analytics portfolio with precise initiatives?

Since publishing my first publish on In the direction of Knowledge 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 trade—on how I might use my Provide Chain Analytics Cheat Sheet to construct a portfolio if I have been beginning out as a junior information 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 information throughout all processes within the worth chain.

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

As an illustration, a retail firm might 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 Creator)

As a Provide Chain Answer Supervisor and Knowledge Scientist within the logistics trade, 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 revealed on In the direction of Knowledge 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 cut back distribution prices, reduce your organization’s environmental affect, or maximize profitability, you’ll discover the solutions to your questions right here.

How Can Analytics Assist Enhance Profitability?

Knowledge Analytics to Enhance Enterprise Profitability

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

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

It contains sensible case research on the right way to use information to help enterprise executives of their strategic decision-making.

As an illustration, the collection of articles, “Enterprise Planning with Python”, relies on an actual instance of a enterprise managed by my pal.

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

“Now we have 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 progress alternatives.

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

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 centered 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 carried out in Asia or Europe.

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

They concentrate on optimizing a selected 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 may be positive they’ll discover some for you.

Right here’s the right way to get began:

  1. Evaluate 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 downside in your organization
  4. Adapt the code to construct an answer to your particular downside

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 better affect? Concentrate on a stream optimization.

Knowledge Analytics for Provide Chain Optimization

The principle driver of the reengineering initiatives I’ve carried out was price.

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

Often, prospects tracked logistics prices, i.e. the share of turnover spent on logistic operations.

Subsequently, we would have liked to search out options (as a third-party logistic service supplier) to scale back this share 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 stream optimization.

Examples of Provide Chain Optimization — (Picture by Creator)

These case research concentrate on the optimization of products stream utilizing

  • Replenishment guidelines and forecasting algorithms to optimize stock
  • Linear/Non-Linear programming to match the availability 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 utility developed for my startup, LogiGreen.

LogiGreen App publicly accessible — (Picture by Samir Saci)

The demo model is publicly accessible so that you can take a look at the fashions; extra info right here.

What about sustainability?

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

Provide Chain Analytics for Sustainability

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

Sustainable Provide Chain Optimization — (Picture by Samir Saci)

Subsequently, you could find 17 examples of optimization options utilizing this strategy to attenuate 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 aspect of sustainability with analytics for Life Cycle Evaluation, CO2 emissions calculations or ESG reporting.

If you happen to want help getting began with sustainability initiatives, you’re coated.

Now It’s Your Flip to Construct!

If you happen to want a extra detailed presentation of the cheat sheet, try this quick YouTube tutorial.

Within the subsequent part, I’ll share how I might strategy 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 information scientist aiming to affix a significant retailer’s Provide Chain Analytics crew.

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

Recommendation 1: Begin with a Easy Mission

For many corporations, information maturity in provide chain departments may be very low.

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

Subsequently, I might concentrate on:

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

Subsequently, I might choose the subject of ABC Evaluation and Product Segmentation.

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

This text supplies 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 information to feed the algorithms and visuals generated.

You’ll be able to enrich this information by adapting it to the trade you’re concentrating on.

  • Vogue retailers normally have seasonality and complicated grasp information
  • Cosmetics product classes are a vital 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 research and adapt it to your imaginative and prescient of the issue to unravel.

Recommendation 3: Code Refactoring and Packaging

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

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

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

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

Recommendation 4: Enhance the UI and add insights

Keep in mind, your abilities might be judged by the affect of the analytics merchandise you design and deploy.

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

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

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

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

If you happen to observe these steps, your portfolio is not going to be a replica of my GitHub repository however a mirrored image of your abilities and how one can affect 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 take a look at the fashions and get inspiration: extra info right here.

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

Conclusion

I hope this transient 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 revealed.

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!

In case you have used any case research for a few of your initiatives, I might be comfortable to study extra in regards to the outcomes.

About Me

Let’s join on Linkedin and Twitter; I’m a Provide Chain Engineer utilizing information analytics to enhance Logistics operations and cut 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 | Knowledge Science & Productiveness
A technical weblog specializing in Knowledge Science, Private Productiveness, Automation, Operations Analysis and Sustainable…samirsaci.com