I have a background in operations research and analysis so, as you might expect, I am biased toward optimization and other types of analytical models for supply chain planning and operational decision-making. Of course, you know the obvious and running challenges that users of these models face:
- The data inputs for such a model are never free of defects
- The data model that serves as the basis for a decision model is always deficient as a representation of reality
- As soon a model is run, the constantly evolving reality increasingly deviates from the basis of the model
Still, models and tools that help decision-makers integrate many complex, interrelated trade-offs can enable significantly better decisions.
But, what if we could outperform very large complex periodic decision models through a sort of “existential optimization” or as a former colleague of mine put it, “humalytics“?
Here is the question expressed more fully:
If decision-makers within procurement, manufacturing and distribution and sales had the “right time” information about tradeoffs and how their individual contributions were affecting their performance and that of the enterprise, could they collectively outperform a comprehensive optimization/decision model that is run periodically (e.g. monthly/quarterly) in the same way that market-based economies easily outperform centrally planned economies?
I would call this approach “humalytics” (borrowed from a former colleague, Russell Halper), leveraging a network of the most powerful analytical engines – the human brain, empowered with quantified analytical inputs that are updated in “real-time” or as close to that as required. In this way, the manager can combine these analytics with factors that might not be included in a decision model from their experience and knowledge of the business to constantly make the best decisions with regard to replenishment and fulfillment through “humalytics”, resulting in constantly increasing value of the organization.
In other words, decision-maker would have instant, always-on access to both performance metrics and the tradeoffs that affect them. For example, a customer service manager might see a useful visualization of actual total cost of fulfillment (cost of inventory and cost of disservice) and the key drivers such as actual fill rates and inventory turns as they are happening, summarized in the most meaningful way, so that the responsible human can make the most informed “humalytical” decisions.
Up until now, the answer has been negative for at least two reasons:
A. Established corporate norms and culture in which middle management (and maybe sometimes even senior management) strive diligently for the status quo.
B. Lack of timely and complete information and analytics that would enable decision-makers to act as responsible, accountable agents within an organization, the same way that entrepreneurs act within a market economy.
With your indulgence, I’m going to deal with these in reverse order.
A few software companies have been hacking away at obstacle “B.”, and we may be approaching a tipping point where the challenge of accurate, transparent information and relevant, timely analytics can be delivered in near real-time, even on mobile devices, allowing the human decision-makers to constantly adjust their actions to deliver continuously improved performance. This is what I am calling “humalytics”.
But the network of human decision-makers with descriptive metrics is not enough. Critical insights into tradeoffs and metrics come through analytical models, particularly, optimization models. So, two things are necessary:
1. Faster optimization and other analytical modeling techniques from which the essential information is delivered in “right time” to each decision-maker
2. An empowered network of (human) decision-makers who understand the quantitative analytics that are delivered to them and who have a solid understanding of the business and their part in it
In current robotics research there is a vast body of work on algorithms and control methods for groups of decentralized cooperating robots, called a swarm or collective. (ftp://ftp.deas.harvard.edu/techreports/tr-06-11.pdf) Maybe, we don’t need robots. Maybe we just need empowered decision-makers who not only engage in Sales and Operations Planning (or, if you will, Integrated Business Planning), but integrated business thinking and acting on an hourly (or right time) basis.
What think you?
More on this topic in a later post. But, if you think this might make sense for your business, or if you are working on implementing this approach, I’d be very interested to learn your perspective and how you are moving forward.
I leave you with these words from Leo Tolstoy, “There is no greatness where there is no simplicity, goodness, and truth.”
I’m off for a little vacation. Have a wonderful weekend!