Ava Ex Machina and the Retail Supply Chain

There is a lot of buzz about the “autonomous” supply chain these days.  The subject came up at a conference I attended where the theme was the supply chain of 2030.  But, before we turn out the lights and lock the door to a fully automated, self-aware, supply chain “Ava Ex Machina”, let’s take a moment and put this idea into some perspective.

The Driverless Car Analogy

From CBC News https://www.cbc.ca/news/business/driverless-cars-stratford-1.3390279

I’ve heard the driverless vehicle used as an analogy for the autonomous supply chain.  However, orchestrating the value network where goods, information and currency pulse freely, fast, and securely between facilities, organizations, and even consumers, following the path of least resistance (aka the digital supply chain), may prove to be even more complex than driving a vehicle.  Digital technologies, such as additive manufacturing, blockchain, and more secure IoT infrastructure, advance the freedom, speed and security of these flows.  As these technologies makes more automation possible, as well as a kind of “autonomy”, the difficulty and importance of guiding these flows becomes ever more crucial.  

Most sixteen-year-old adolescents can successfully drive a car, but you may not want to entrust your global value network to them.

Even Elon Musk says that Tesla autopilot will never be perfect.

Before you can have an autonomous supply chain, you need to accelerate the Detect, Diagnose, Direct Cycle – let’s call it the 3-D Cycle, for short, not just because it’s alliterated, but because each “D” is one of three key dimensions of orchestrating your value network.  In fact, as you accelerate the 3-D Cycle, you will learn just how much automation and autonomy makes sense.

Figure 1

Detect, Diagnose, Direct

The work of managing the value network has always been to make the best plan, monitor issues, and respond effectively and efficiently.  However, since reality begins to diverge almost immediately from even the best plans, perhaps the most vital challenges in orchestrating a value network are monitoring and responding.

In fact, every plan is really just a response to the latest challenges and their causes.

So, if we focus on monitoring and responding, we are covering all the bases of what planners and executives do all day . . . every day.

Monitoring involves detecting and diagnosing those issues which require a response.  Responding is really directing the next best action.  That’s why we can think in terms of the “Detect, Diagnose, Direct Cycle”:

1. Detect (and/or anticipate) market requirements and the challenges in meeting them
2. Diagnose the causes of the challenges, both incidental and systemic
3. Direct the next best action within the constraints of time and cost

The 3-D Cycle used to take a month, in cases where it was even possible.  Digitization – increased computing power, more analytical software, the availability of data – have made it possible in a week.  Routine, narrowly defined, short-term changes are now addressed even more quickly under a steady state – and a lot of controlled automation is not only possible in this case, but obligatory.  However, no business remains in a steady state, and changes from that state require critical decisions which add or destroy significant value.   

You will need to excel at managing and accelerating the 3-D Cycle, if you want to win in digital economy.

There is no industry where mastering this Cycle is more challenging than in retail, but the principles apply across most industries.

 

Data Is the Double-edged Sword

The universe of data is exploding exponentially from growing connections among organizations, people and things, creating the need for an ever-accelerating 3-D Cycle.  This is especially relevant for retailers, and it presents both a challenge and an opportunity for competing in the digital economy with a digital value network.  Redesigned, retail supply chains, enabled with analytics and augmented reality, are not only meeting, but raising consumer expectations.

Figure 2

Amazon’s re-imagination of retail means that competitors must now think in terms of many-to-many flows of information, product, and cash along the path of least resistance for the consumer (and not just to and from their own locations).  This kind of value network strategy goes beyond determining where to put a warehouse and to which stores it should ship.  Competing in today’s multi-channel world can mean inventing new ways to do business, even in the challenging fashion space – and if it is happening in fashion, it would be naive to think rising consumer expectations can be ignored in other retail segments, or even other industries.  Consider a few retail examples:

Zara leverages advanced analytics, not only to sense trends, but also to optimize pricing and operations in their vertically integrated supply chain.

Stitch Fix is changing the shopping model completely, providing more service with less infrastructure.

Zolando has been so successful in creating a rapid response supply chain that they are now providing services to other retailers.

Nordstrom, of all organizations, is opening “inventoryless” stores.

Walmart has been on an incredible acquisition and partnership spree, recently buying Flipkart and, as early as two years ago, partnering with JD.com.  And, then, there is the success of Walmart.com.

Target is redesigning the way their DC’s work, creating a flow-through operation with smaller replenishment quantities.

Yet, many companies are choking on their own ERP data, as they struggle to make decisions on incomplete, incorrect and disparate data.  So, while the need for the 3-D Cycle to keep pace grows more ever more intense, some organizations struggle to do anything but watch.  The winners will be those who can capitalize on the opportunities that the data explosion affords by making better decisions faster through advanced analytics (see Figure 2).

The time required just to collect, clean, transform and synchronize data for analysis remains the fundamental barrier to better detection, diagnosis and decisions in the value network.  A consolidated data store that can connect to source systems and on which data can be consolidated, programmatically “wrangled”, and updated into a supra data set forms a solid foundation on which to build better detection, diagnosis, and decision logic that can execute in “relevant time”.  This can seem like an almost insurmountable challenge, but it is not only doable with today’s technology, it’s becoming imperative.  And, it’s now possible to work off of a virtual supra data set, but that’s a discussion for another day.

 

Detect, Diagnose and Direct with Speed, Precision & Advanced Analytics

Detection of incidental challenges (e.g. demand is surging or falling based on local demographics, a shipment is about to arrive late, a production shortfall at a vendor, etc.) in your value network can be significantly automated to take place in almost real-time, or at least, in relevant time.   Detection of systemic challenges will be a bit more gradual and is based on the metrics that matter to your business, such as customer service, days of supply, etc., but it is the speed and, therefore, the scope, that is now possible that drives better visibility 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 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 understanding possible through diagnosis.

With a clean, complete, synchronized data set that is always available and always current, as well as a proactive view of what is happening and why, you need to direct the next best action while it still matters.  You need to optimize your trade-offs and perform scenario and sensitivity analysis.

Figure 3, below, shows both incidental/operational and systemic/strategic examples for all three dimensions of the 3-D Cycle.

Figure 3

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.  Much of the entire 3-D 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.

Fortunately, you don’t need Ava Ex Machina, but your ability to develop a faster and better (and, I will even say more autonomous) 3-D Cycle is fundamental to your journey toward the digital transformation of your value network.

The basic ideas of detecting, diagnosing and directing are not novel to supply chain professionals and other business executives.   However, the level of transparency, speed, precision and advanced analytics that are now available mandate a new approach and promise dramatic results.  Some will gradually evolve toward a better, faster 3-D cycle.  The greatest rewards will accrue to enterprises that climb each hill with a vision of the pinnacle, adjusting as they learn.  These organizations will attract more revenue and investment.  Companies that don’t capitalize on the possibilities will be relegated to hoping for acquisition by those that do.

Admittedly, I’m pretty bad at communicating graphically, but I’ve attempted to draft a rudimentary visual of what the architecture to support a state-of-the-art 3-D Cycle could look like (in Figure 4 below), as a conceptual illustration for facilitating discussion.

The convergence of cloud business intelligence (BI) technology and traditional advanced planning solutions supports my point, and that is definitely happening.

As the unstoppable train of time pulls us into the weekend, I leave you with this thought to ponder: 

“Life is short, so live it well, in gratitude, honesty and hope, and never take it for granted.”

Figure 4

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Digital Transformation of Supply Chain Planning

A couple of years back, IBM 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 (like say, health care delivery) need to move rapidly with value network planning.  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, make decisions that are “in the moment”, spans the entire value network.  That 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, too much of this data 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!

The Supply Chain of the Future

Source: Consumer Goods Forum

At last week’s conference of the Council of Supply Chain Management Professionals, John Phillips, Senior Vice President, Customer Supply Chain and Logistics for PepsiCo, presented findings from Building Strategies for the New Decade – Future Value Chain 2020.  The report is definitely worth a look and to whet your appetite and stimulate your thinking, I have summarized the twelve root trends below (supporting stats are sourced in the Report):

Increased Urbanization – By 2050, roughly 70% of the world’s population will live in urban centers.

Aging Population – Consumers 50 and older may soon represent the majority of the voting public.

Increasing Spread of Wealth – The population in low- and middle-income countries with purchasing power parity (PPP) is expected to triple by 2030.

Increased Impact of Consumer Technology Adoption – By 2013, more than 2 billion mobile users globally will have made a purchase via their handsets.

Increase in Consumer Service Demands – Over the next decade, the online channel will grow to 25% to 30% of total retail sales, up from the current 4% to 15%.

Increased Importance of Health and Wellbeing – In the U.S., for example, the “Lifestyles of Health and Sustainability” market is estimated to comprise approximately 19% of the adult population, representing a market of 41 million consumers.

Growing Consumer Concern about Sustainability – According to the Natural Marketing Institute (NMI), the green marketplace in the U.S. is predicted to grow from $420 billion in 2010 to $845 billion by 2015.

Shifting of Economic Power – China will overtake the U.S. to become the world’s largest economy as early as 2017.  And by 2012, India will have overtaken Japan.

Scarcity of Natural Resources – By 2030, the world’s population will reach 8.3 billion, with the demand for food and energy increasing by 50% and for fresh water by 30%.

Increase in Regulatory Pressure – Over the next decade regulatory pressure is expected to increase.

Rapid Adoption of Supply Chain Technology Capabilities – In the coming decade, improved collaboration together with new supply chain/logistics technologies and information transparency will enable a more synchronized value network with greater visibility and traceability.

Impact of Next Generation Information Technologies – Information technology will no longer be just an indispensable support function, but an expansion of the organization’s intelligence, a universal connector, the way to become adaptive.

This list brings up two questions:

1)      Are you seeing any of these trends today?

2)      What are you doing within your value network to capitalize on these trends – that’s right – capitalize on them, not just mitigate their effects.

With all this talk of trends and change, I will leave you with my favorite quote on change.  It was Leo Tolstoy who said, “Everybody thinks of changing humanity, and nobody things of changing himself.”

Have a wonderful weekend!