Interview with Melissa Drew, Associate Partner, IBM

We thank Melissa Drew from IBM for taking part in the Data Science Interview Series and sharing several insights, including:

  • Her role as an Associate Partner at IBM and the challenges she faces
  • Importance of Data in Procurement and supply chain
  • Applications of Data Science and ML in this domain
  • Areas in Procurement and Supply Chain that need improvement


I have been fortunate to collaborate with teams who have become more competitive in their industry, or built a foundation to support their 1st acquisition, or eliminated the needs for layoffs during a pandemic.

– Melissa Drew

CK: Tell us something about your role as a Partner at IBM. What does your day-to-day work look like?

MD: My focus at IBM is providing value in digital procurement and supply chain transformation strategies. Since that is a bit of a mouthful, I help companies become more informed, a decision-based organization so they can achieve their short and long-term corporate goals.

I have been fortunate to collaborate with teams who have become more competitive in their industry, or built a foundation to support their 1st acquisition, or eliminated the need for layoffs during a pandemic.  It is those moments that are so inspiring, to know I am helping make a difference and have an impact.

On any given day, I prioritize my time across work, endless questions from twin girls, setting aside quiet moments to myself, and making sure there is enough food for all (e.g. family, chickens, cat). When possible, I learn whenever and wherever which helps me look at challenges from different perspectives.



I have found breaking challenges into smaller components allows me to focus on the subsets before reshaping the whole.

– Melissa Drew

CK: What are the top challenges that you face at work? How do you go about tackling them?

MD: We are in a constantly changing global landscape from technological, economical, and/or customer-driven demands.  As a consultant, we not only bring forward disrupting technologies such as blockchain, Artificial Intelligence, and BOTs to our customers but we also use them ourselves. Where we transform customers to become a more agile organization – so they can adjust more quickly to the global landscape – we are also transforming what it means to be a consultant.

The Covid pandemic pushed the world to adopt technology on a faster timeline. For example, instead of taking years to adopt Slack, companies have achieved that in months. For a consultant, this requires developing a more flexible mindset to adopting new technologies today and accepting possibilities of new technologies tomorrow.

I have found breaking challenges into smaller components allows me to focus on the subsets before reshaping the whole.  When temporarily breaking down these larger obstacles, it improves the opportunity to develop a creative solution at the root cause and may reshape what the larger solution looks like when it is all stitched back together.



If procurement and supply chain make up the backbone of an organization, then data is the heart.

– Melissa Drew

CK: What are the various processes involved in the Digital Transformation of a process? In what areas do ML and DS complement this process?

MD: If procurement and supply chain make up the backbone of an organization, then data is the heart. Everything we do in a company will always come back to data: Where and how much data is collected?  What does the data tell us? Is the confidence in the data at a threshold we can tolerate? How do I interpret the data? Or Is the data actionable?

Machine Language and Data Science are becoming a larger part of the procurement and supply chain organizations, in sometimes very subtle but impactful ways. The most common use is Analytics.

Automating the classification and enrichment of spend data through grammar-based natural machine language and deep learning enables a better understanding of historic and future trends with minimal interaction from the user. Visibility of this spend leads to more-informed buying decisions and greater savings but also highlights and mitigate risks.

Additional use cases include but certainly not limited to consumer analytics supporting hyper-personalization marketing initiatives; predictive analytics in presales & sales cycles for improved targeted marketing, and data monitoring which analyzing receipts to detect anomalies that can lead to fraud in expense management.


CK: What are the areas in Procurement and Supply Chain that lack innovation and need improvement?

MD: An area where I am seeing an increase is the use of BOTs which has a direct, but positive impact on the procurement user. Today, cloud-based applications have modules supporting the entire supplier lifecycle from supplier onboarding, sourcing, contract management, invoicing, buying, compliance, risk, performance, reporting, etc. 

There are still so many smaller steps in those applications that require a procurement person to manually interact with the system, performing non-value tactical activities. BOTs use machine learning to automate repeatable steps that need to be performed frequently. In the next 6-12 months, I expect we will see a substantial increase in BOT development and it will become a differentiating factor for both consulting firms and organizations.


CK: What are the various ways in which Data Science and Machine Learning are impacting the Procurement and Supply Chain domain? How does the future look like to you?

MD: There are always opportunities for improvement in Procurement and Supply Chain. Machine Learning will expand more into supplier relationships.

  • We are just starting to see applications provide a predictive review of the accuracy of Suppliers to deliver across the supply chain, detect a variance, outline the impact across the entire supply chain and provide a list of alternative supplier options.
  • Expanding into Supplier Risk is also in the earlier stages to developing real-time risk scores based on current changes using public data from around the world.
  • Supplier identification and evaluation beyond who the organization has in their corporate databases is certainly a need. Organizations have an invisible and unavoidable leakage simply because they don’t know about all the mid-size companies with innovating technologies that can better support their organization.

CK: What have been your 3 key learnings in an almost 3-decade long career? What suggestions/advice do you have for beginners?

MD: I have worked in organizations both as a procurement and supply chain professional and as a consultant.  Five years ago, there was a wider gap between lessons learned for procurement professionals versus lessons learned for a procurement consultant. That gap is almost completely closed now.

  • Staying true to your authentic self. Do not believe wavering from your authentic self will bring you success
  • Do something you absolutely love, even if it means changing job/careers
  • Learn to empower others and share your knowledge
  • Practice self-awareness until it becomes natural
  • Become flexible to change

Associate Editor

Chayan is a creative Data Scientist with an eye for details. An everyday learner and blogger, he has extreme eagerness to share knowledge and support the Data Science community. Connect with him on LinkedIn to get in touch and don’t forget to check out his Medium blogs.

Data Science | Machine Learning | Tech Blogger – upGrad

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About Chayan Kathuria

Chayan is a creative Data Scientist with an eye for details. An everyday learner and blogger, he has extreme eagerness to share knowledge and support the Data Science community. Connect with him on LinkedIn to get in touch and don't forget to check out his Medium blogs. Data Science | Machine Learning | Tech Blogger - upGrad

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