What Supply Chain Management Folks can Learn from Wall Street
I live in New York and as you can imagine I’m surrounded by finance professionals working at hedge funds, big banks, and boutique funds. As I have conversations with my finance friends, I think about how I can apply their tactics to supply chain.
They are doing really cool stuff to make money from the stock market using expansive data sets, high end algorithms, and using the latest advances in computing power than I could ever imagine.
Here are some of my learnings from my casual conversations with them.
Knowledge is Power
Financial folks scour the internet to get the most comprehensive sets of data faster than the next guy. They will collect, beg for, and buy the data. They look at data like stock and bond prices, company events and announcements, commodity prices, housing starts, employment, wages, demographics, and retail sales.
What if supply chain professionals used every piece of data to make better decisions that ensure they satisfy their end customers? What kind of data would they look at? Would they use the same data as financial professionals do?
Some examples include adjusting production plans and product availability dates by knowing that a raw material shipment is late or that a machine is down. Early action can be taken to respond to a promotion that is stocking out stores.
In a recent blog “Know what your consumers are thinking, before they do!”, Richard Howells talked about how “big data” can be used to gather the true picture of actual demand by capturing both structured and unstructured data about customers and products.
Smarter is Better
My quant friends spend their weekends studying the latest and greatest on financial algorithm modeling. They code in C++, Python, R, and MatLab. They do research of financial algorithms through “Backtesting” and “Signal Generation” ie. generating a set of trading signals from an algorithm and sending these orders to the market.
Shouldn’t supply chain professionals spend more time developing and leveraging high end algorithms to find correlations of macro and micro demand and supply signals on their mission critical supply chains? I see lots of opportunity by better optimizing transportation routes, purchase prices, re-deploying inventory based on changes in local needs such as weather and consumer sentiment.
Faster = Richer
You should check out the caliber of the hardware engineers at high frequency traders. They get into the guts of the chips, networks, and servers so they can process and act faster than their competition. Being the first person at a micro-second sale, means the difference between making money or losing money. They are building custom hardware using High-Performance MicroProcessor Design and VHSIC Hardware Description Language. They use field-programmable gate arrays, exchange co-location and kernal/network interface tuning to tweak performance to the most optimal levels.
Can supply chain professionals go beyond in memory storage to get faster calculations? Have they considered all the I/O issues such as network bandwidth and latency? Have they explored parallelized computing, optimized algorithmic execution speed, scaling, and caching strategies?
SAP’s HANA platform is an excellent example of how software vendors are leveraging newer technologies to push the boundaries of supply chain systems. This is enabling capabilities never seen before. See Re-thinking Your Supply Chain with SAP HANA.
Clearly, there is a lot for all of us to learn from my Finance Quant friends. Perhaps, us Supply Chain Quants can figure out how to extract value out of more comprehensive data analysis, better algorithms, and faster analysis. I look forward to taking these learnings to the bank!
Learn more about SAP’s Supply Chain Solution Strategy at the SAP SCM Webcast Series.
I don't see the value of this argument:
1. Finance is a business, supply chain is a function within the business
2. Finance has extensive lobbying so that it can write its own rule book, if most other companies acted as the finance sector does, they would be in jail.
3. The collaborative requirements of most supply chains make the 'knowledge is power' tip of the finance sector not just counter productive but actually harmful to the business
4. Faster does not equal richer, it equals errors in processing, failure to achieve quality and to meet required standards.
Only 7 years ago Wall Street took a $2 trillion bailout because its practices were so bad and corrupt that it crashed and threatened the world. Its activities are still shrouded in secrecy, with respected journalists threatened with lawsuits for publishing details of their behavior - bullying interns, long working hours, criminal negligence in financial transactions (including drug and gun running).
Nobody should take lessons from an industry that is endemically corrupt, lacks empirical evidence to justify its structure and has a revolving door to political power, enabling it to manipulate legislation.