The Winding Road toward the “Autonomous” Supply Chain (Part 2)

3d-matrix

Last week, I began this train of thought with The Winding Road toward the ‘Autonomous’ Supply Chain (Part 1)”.  Now, as this weekend approaches, I conclude my piece, but I hope to spur your ideas.

Detect, Diagnose, Decide with Speed, Precision & Advanced Analytics

Detection of incidental challenges (e.g. a shipment that is about to arrive late, a production shortfall, etc.) in your value network can be significantly automated to take place in almost real-time.   Detection of systemic challenges will be a bit more gradual and is based on the metrics that matter to your business, capturing customer service, days of supply, etc., but it is the speed (and therefore, the scope) that is now possible that drives more value today from detection.

Diagnosing the causes of incidental problems is only limited by the organization and detail of your transactional data.  Diagnosing systemic challenges requires a hierarchy of metrics with respect to cause and effect (such as, or similar to, the SCOR® model).  Certainly, diagnosis can now happen with new speed, but it is the combination of speed and precision that makes a new level of knowledge and value possible through diagnosis.

With a clean, complete, synchronized data set and a proactive view of what is happening and why, you need to decide the next best action in a timeframe where it is still relevant.  You must optimize your tradeoffs and perform scenario (“what-if”) and sensitivity analysis.

Ideally, your advanced analytics will be on the same platform as your wrangled supra data set.  The Opalytics Cloud Platform (OCP) not only gives you state of the art data wrangling, but also provides pre-built applications for forecasting, value network design and flow, inventory optimization, transportation routing and scheduling, clustering and more.  OCP also delivers a virtually unlimited ability to create your own apps for decision modeling, leveraging the latest and best algorithms and solver engines.

Speed in detection, speed and precision in diagnosis, and the culmination of speed, precision and advanced analytics in decision-making give you the power to transpose the performance of your value network to levels not previously possible (see Figure above).  Much of the entire Detect, Diagnose, Decide cycle and the prerequisite data synchronization can be, and will be, automated by industry leaders.  Just how “autonomous” those decisions become remains to be seen.

As yet another week slips into our past, I leave you with a thought from Ralph Waldo Emerson, “There is properly no history, only biography.”

Have a wonderful weekend and thank you, again, for stopping by.

The Time-to-Action Dilemma



dreamstime_m_26639042If you can’t answer these 3 questions in less than 10 minute
s
(and I suspect that you can’t), then your supply chain is not the lever it could be to
 drive more revenue with better margin and less working capital:
1) What are inventory turns by product category (e.g. finished goods, WIP, raw materials, ABC category, etc.)?  How are they trending?  Why?
2) What is the inventory coverageWhat will projected inventory be at by the start of a promotion or season.  Within sourcing, manufacturing or distribution constraints, what options do I have if my demand spikes or tanks?
3) What proportion (and how many) of your customer orders (or margin or revenue) shipped at 99% on-time and in-full?  How many at 98%? And so on . . . Do you understand the drivers?

The slack time that global competition is allowing you to have between planning and execution is collapsing at an accelerating rate.

You need to know the “What?” and the “Why? so you can determine what to do before it’s too late.  

You need to answer the questions that your ERP and APS can’t so your supply chain makes your business more valuable.

Since supply chain decisions are all about managing interrelated goals and trade-offs, data may need to come from various ERP systems, OMS, APS, WMS, MES, and more, so unless you have a platform that consolidates and blends data from end-to-end at every level of granularity and along all dimensions, you will always be reinventing the wheel when it comes to finding and collecting the data for decision support.  It will always take too long.  It will always be too late.

You need the kind of platform that will deliver diagnostic insights so that you can know not just what, but why.  And, once you know what is happening and why, you need to know what to do — your next best action, or at least viable options and their risks . . . and you need that information in context and “in the moment”.

In short, you need to detect opportunities and challenges in your execution and decision-making, diagnose the causes, and direct the next best action in a way that brings execution and decision-making together.

If you don’t have all three now – Detect, Diagnose and Direct – in a way that covers your end-to-end value network, you need to explore how you can get there.

As we approach the weekend, I’ll leave you with this thought to ponder:  Leadership comes from a commitment to something greater than yourself that compels maximum contribution, whether that is leading, following, or just getting out of the way.”

“Moneyball” and Your Business

MV5BMjAxOTU3Mzc1M15BMl5BanBnXkFtZTcwMzk1ODUzNg@@__V1__SY317_CR0,0,214,317_It’s baseball season again!  A while back, the film “Moneyball” showed us how the Oakland A’s built a super-competitive sports franchise on analytics, essentially “competing on analytics”, within relevant business parameters of a major league baseball franchise.  The “Moneyball” saga and other examples of premier organizations competing on analytics were featured in the January 2006 Harvard Business Review article, “Competing on Analytics” (reprint R0601H) by Thomas Davenport, who also authored the book by the same name.

The noted German doctor, pathologist, biologist, and politician, Rudolph Ludwig Karl Virchow called the task of science “to stake out the limits of the knowable.”  We might paraphrase Rudolph Virchow and say that the task of analytics is to enable you to stake out everything that you can possibly know from your data.

That’s what competing on analytics really means.

In your business, you strive to make the highest quality decisions today about how to run your business tomorrow with the uncertainty that tomorrow brings.  That means you have to know everything you possibly can know today.  In an effort to do this, many companies have invested, or are considering an investment, in supply chain intelligence or analytics software.  Yet, many companies who have made huge investments know only a fraction of what they should know from their ERP and other systems while they are mired in long, costly projects that are rapidly losing momentum and delivering little or no value.

Take operational excellence as an example.

Are you able to see a bottleneck build in your order-to-cash process at exactly the step or steps where it is occurring, immediately comprehending the impact because you are seeing hard data in an intelligent context?

What about visibility of supply chain performance?

Can you see that what proportion of your perfect order performance is being caused by days of supply which has been recently impacted by changes in customer order request dates or forecast error?

If operational excellence or supply chain visibility and performance sit high on your list of priorities, your wish list should include the following:

  • Pre-built connectors to your ERP system from a secure, scalable, speedy cloud platform for immediate plug-in and start-up
  • Fast harmonization across multiple ERP instances or data models
  • Comprehensive, domain-specific (supply chain and maybe industry) interrelated metrics that focus new light on the levers for revenue, margin and working capital
  • Simple, but powerful, self-service configuration beyond out-of-the-box metrics
  • Root cause analysis
  • Role-based views with collaboration
  • (Almost) zero learning curve
  • A continuous stream of new value-added services (e.g. what-if scenario analysis, predictive and prescriptive analytics, etc.) based the fact that your provider is now the secure custodian of your enterprise data

Are you competing on analytics?

Are you making use of all of the data available to support better decisions in less time?

Can you instantly see what’s inhibiting your revenue, margin and working capital goals across the entire business in a context?

Do you leverage analytics in the “cloud”?

As always, thanks for stopping by and having a quick read.  I hope you found this both helpful and thought-provoking.

As we enter this weekend, I leave you with one more thought that relates to “business intelligence” — this time, from Socrates:  “The wisest man is he who knows his own ignorance.

Do you know yours?  Do I know mine?

Have a wonderful weekend!

Whither Supply Chain Analytics?

IBM has just released a study “Digital operations transform the physical” (capitalization theirs).

Citing client examples the report states,

“Perpetual planning enables more accurate demand and supply knowledge, as well as more accurate production and assembly status that can lower processing and inventory costs . . .

Analytics + real-time signals = perpetual planning to optimize supply chain flows

They are describing the space to which manufacturers, retailers, distributors, and even service providers are rapidly moving with value network analytics.  This is a challenging opportunity for software providers, and the race is on to enable this in a scalable way.  The leading software providers must rapidly achieve the following:

1)      Critical mass by industry

2)      Custody of all the necessary data and flows necessary for informing decision-makers of dynamic, timely updates of relevant information in an immediately comprehensible context

3)      Fast, relevant, predictive and prescriptive insights that leverage up-to-the-minute information

Some solution provider (or perhaps a few, segmented by industry) is going to own the “extended ERP” (ERP+ or EERP to coin a phrase?) data.  Whoever does that will be able to provide constantly flowing intelligent metrics and decision-support (what IBM has called “perpetual planning”) that all companies of size desperately need.  This means having the ability to improve the management of, working capital, optimize value network flows, minimize value network risk, plan for strategic capacity and contingency, and, perhaps most importantly, decision-making that is “in the moment” that spans the entire value networkThat is the real prize here and a growing number of solution providers are starting to turn their vision toward that goal.  Many are starting to converge on this space from different directions – some from inside the enterprise and some from the extra-enterprise space.

The remaining limiting factor for software vendors and their customers aspiring to accomplish this end-to-end, up-to-the-moment insight and analysis remains the completeness and cleanliness of data.  In many cases, half of this information is just wrong, incomplete, spread across disparate systems, or all of the above.  That is both a threat and an opportunity.  It is a threat because speedily providing metrics, even in the most meaningful visual context is worse than useless if the data used to calculate the metrics are wrong.  An opportunity exists because organizations can now focus on completing, correcting and harmonizing the data that is most essential to the metrics and analysis that matter the most.

What are you doing to achieve this capability for competitive advantage? 

Thanks for stopping by.  I’ll leave you with this thought of my own:

“Ethical corporate behavior comes from hiring ethical people.  Short of that, no amount of rules or focus on the avoidance of penalties will succeed.”

Have a wonderful weekend!

Unconventional Wisdom?

Over years of working with clients, I have found that the most effective way to evaluate an a strategic software project and assess its value has been through a small scale collaborative effort in which both client and vendor invest and participate.  Such an approach serves the best interest of both parties, not just the vendor.

This is true when a client-specific, use-case-specific solution is required for making very complex, very valuable decisions.  This collaborative approach provides several important benefits for the client:

A) Alignment – The vendor quickly gains deep insight into the client’s specific requirements.  In this way the vendor can be sure to capture all key requirements and fully test and demonstrate the value of the solution.  In many cases, the prototype can form the basis of the first phase of the implementation, so the project is ready to start, should the client decide to proceed.

C) Risk Reduction – Because of the learning that takes place prior to any major commitment on the part of the client, the risk associated with a decision to proceed with the overall project is greatly reduced.  The client’s decision regarding whether or not to proceed with the project is more informed than it could be in any other way.  For example, the estimate of the likely return on investment is much more precise.

D) Client Learning – The client learns the vendor’s software and its capabilities better than they could in any classroom setting and  in a very short period of time.

E) Time to Value – The alignment, risk reduction, and client learning drive a faster time-to-value for the overall project.

A joint investment in a small-scale collaborative effort is also a prudent approach.

As a case in point, consider an investment of $10K to evaluate a project costing say $200,000, with a potential ROI of $1 million or more per year.  One might say that it not only makes good business sense to invest the $10K, but that the value achieved in terms of alignment, risk reduction, learning, and time to value make it a bargain.

This seems like a wise approach to me, but unfortunately, it is far too infrequent.

Thanks for stopping by.  I’ll leave you with these few words to ponder from Sir Ronald Gould, “When all think alike, none thinks very much.”

Have a wonderful weekend!

Analytics vs. Humalytics

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:

  1. The data inputs for such a model are never free of defects
  2. The data model that serves as the basis for a decision model is always deficient as a representation of reality
  3. 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!

Part 5 – Finding the ROI for an Investment in an Analytical SCM Solution

Technologyevaluation.com published a piece of mine on this topic a few years ago, but the ideas are important, so I am recapitulating the them here.  The first post in this series introduced the topic of overcoming the challenges to calculating the return for an investment in an analytical supply chain software application.  This post deals with the last of four challenges.

Part 5 — Fourth Challenge — No Patience for Context — “Just give me the bottom line!”

This reaction to understanding the value of a software investment is reminiscent of some people who are in a hurry to know what stock they should buy. 

This person does not want to learn about industry performance.

She or he is not interested in the relative competitive strengths of one company versus those of other companies in the same industry.

Nor is this person motivated to research financial statements in order to understand what might be driving a company’s performance or whether that performance is getting better or worse.

This person simply wants to know if it will be a good investment and how much can be made at the end of 12 months if it is sold.

So he or she scans a list of stock picks in one of the many financial publications, chooses the company ranked at the top, and then “places a bet” because at that point, the decision is little more than a wager based on an uninformed hunch.

It is likely that this person will be sadly disappointed in the return.

The investor will probably try to recover the loss with an equally unconsidered investment decision, leading to a cycle of poorly informed decisions.  Obviously, this individual is putting the amount of money about to be invested at great risk because he or she has latched on to an answer without context.

In the same way, decision-makers in a company may rush to a “bottom-line” conclusion, only to have their efforts frustrated by poor results because they did not take the time and do the work necessary to gain some understanding of what is driving their pain and how their decision may affect those drivers.

This will often lead to additional decisions that are made without adequate research and consideration in an effort to recover from the first one.

Successful business is driven by quality decisions that can be executed in a timely fashion.

Some of these decisions relate to investing in software applications that support supply chain management.  At least four hurdles face those seeking to make a timely, but intelligent decision, as we have seen in this series of posts.

Reliable predictions of ROI will continue to evade decision-makers who react to these challenges with the responses we have studied here.  However, if you do not succumb to that temptation, some careful analysis can provide information that will guide your software investment strategy.

Companies invest in analytical supply chain management software to improve their decision processes.  You can read about my unique approach to prioritizing and accelerating the improvement of decision processes in “Finding the Value in Your Value Network“.

I leave you to ponder this final thought from Thomas Carlyle, “Work is the grand cure of all the maladies and miseries that ever beset mankind–honest work, which you intend getting done.”

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