AI-powered, Data-driven Supply chain - Part 1.
Krishna Pera
Top Management Professional | Author | Consultant | Visiting Faculty at IIMs | Investor-Mentor for Startups | GCCs | Data-driven Org. | AI | Analytics |
(Published in Data Science Central earlier)
Part-1 of this article traces the history and evolution of data-driven decision-making in supply chain; right from the first rudimentary decision-support-systems, specifically i2 Technologies and SAP-APO, all the way to the supply chains of the future which are expected to leverage the Bigdata, AI-ML and Generative AI extensively. Part-2 of this article explains how the enterprise value chain is not one simple, unitary supply chain, but rather a complex network. & How resolving the bottlenecks in the information-supply-chain is the key to a successful TOC (theory of constraints) implementation for maximizing the throughput from the enterprise value-chain. Part-3 of this article explains the immediate and pressing need for digitizing your supply chain & a broad roadmap for building an AI-powered, data-driven supply chain.
Part-1: History & Evolution
Is the concept of 'data driving decisions' new?
It turns out the concept of “data supporting decisions” is not new. Business intelligence (BI) has been around since the 1960s. However, the amount and availability of data are now far greater than ever, and businesses are relying on data-driven decision-making more heavily than ever before. For those in doubt, I recommend an excellent article from the Journal of Knowledge Economy that chronicles the evolution of the ‘Information-driven decision-making process’ from 1950 to 2020 (Parra. X & Ors, J Knowl Econ, 2022).
Those of us who went to college in the 90s (when Peter Drucker was still alive) may recall being taught that “a manager’s job is to make rational decisions based on whatever data is available at one’s disposal”. Drucker was supposed to have pioneered the use of decision trees to depict the decision-making process (DMP) (Drucker, 1967). Some of the computational models now being extensively used in Artificial Intelligence like Expert Systems, Neural Networks, etc. were originally proposed in the ’70s, but real progress was made in the ’80s and 90’s as computers became more powerful and more affordable. As more and more data became available to support decision-making in the 1990s, decision-support systems were developed (DSS). Among the most popular applications for DSS in the manufacturing industry were in logistics & supply chain management.
Decision Support Systems (DSS) for Supply-chain: The Story of i2 Technologies
A quarter century ago, I used to be a fairly busy SAP consultant, and after several successful full-cycle implementations, I moved companies and switched over to supply-chain consulting…. mostly because I wanted to do something different. Besides, I was not exactly new to supply-chain management given I had substantial domain experience in Logistics and Distribution-Packaging.
Those days, i2 Technologies dominated the supply-chain and, more specifically, the decision support systems (DSS) space. My employer soon ensured that I was not only trained in the software but also certified as a ‘trainer’ by i2 (Besides consulting, ‘training’ was a major source of revenue for the fledgling new business unit I worked for). However, I could notice something was odd about the whole i2 business, right from day one… ‘i2’ struck me as a poorly thought-out, clumsily designed product; especially when compared to a wondrous and brilliantly designed product like SAP. Most of the i2 product implementations were done by i2 Technologies themselves, and occasionally an odd consultant (like me) was brought in from the newly inducted partners (like my company), to learn on the job.
I quickly learned that the i2 consultants charged exorbitant fees, flew only business-class+, stayed in five-star hotels, and flaunted the latest gadgets. …but whenever customers tried asking pointed questions, they simply threw some jargon at them; while what they said sounded impressive and important, it rarely made sense. Within a few months, I knew enough to deduce there was no real value being delivered to the clients…ironically i2 used to claim they delivered over $ 75 Billion in ’audited savings’ to their customers. Whatever the authenticity of the number, it definitely helped them “sell” their products.
In the meanwhile, I was asked to attend their (i2) annual meet in Malaysia… a fancy event at the fanciest hotel. Following the customary dance, drama, and entertainment, they held an open house for the implementation partners… Right on cue, someone senior representing a global consulting firm openly complained his customers are not happy with the value being delivered. In response, the then CTO who chaired the meeting in the absence of Sanjiv Sidhu, lamented most partners do not implement their product well, and that’s the reason why it fails to deliver value. He could have been right, except that most i2 implementations were owned by i2 themselves, with implementation partners contributing a few odd resources. I was cautious (given our revenues depended on i2’s blessing) but I couldn’t hold myself from asking him if he has a list of do’s and don’ts… and what exactly in his opinion was being missed by the implementation partners? I was immediately shushed by a number of his deputies, but the CTO was clearly caught off-guard. A little red-faced, he assured me that they definitely do… If I could meet his team offline, they would ensure that I get a copy. I didn’t get to ask him why a document they should be sharing with every partner is such a ‘secret’. To cut to the chase, there was no such document and if there was one, it was never shared with me. But, I was invited to have a drink with their senior sales guys that evening. We didn’t talk shop… they insisted we mustn’t.
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SAP initially worked closely with i2. I remember some of their products were integrated into the SAP and could be configured within SAP. But they eventually fell out for reasons that were never made public, and SAP soon developed and launched APO — a far better-designed product that actually works and delivers value.
Some of you may remember how i2 was caught and fined by SEC for misstating their revenues by over $ 1 billion for a five-year period up to 2002. Not sure who their external auditor was, and if they also ‘audited’ the savings of $ 75 Billion.
The first decade of the new millennium saw the introduction of a host of new tools and technologies for business intelligence, data warehousing, data visualization, etc., as well as CRM and SRM. Among the best-known are SAP BI-BO, Oracle, Siebel, Ariba, etc. Tableau made its debut in 2003 (it was called Polaris then).
The supply chain software market has seen significant innovation over the past decade with the advent of Big data, Advanced Analytics Platforms, AI-ML, IOT — Connected Products, self-driving trucks, drones for delivery, and the cloud. Now the Generative AI is expected to revolutionize it further.
#data-driven, #AI, #supply-chain #Decisions
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you dont pull any punches, do you? interesting reading on use of (i2) technologies..