This article originally appeared in The European Business Review on November 20, 2012. We've obtained the permission to repost this along with some of our own thoughts, comments, and outside research. You can read our notes and commentary when you click on "Notes and Commentary" (the text box will expand). Otherwise, you can read the article in its entirety without interruption. We welcome, and greatly appreciate, all dialogue, questions, and answers, so don't be shy! Let's get to it.
From the 1960s up until the 1990s Western manufacturing companies were out-performed by new levels of quality, cost and efficiencies emanating from Japan. Upon realizing that this new competition from the Far East was playing to a different set of rules, the West endeavored to catch up by understanding and applying principles such as Kaizen, TQM and Lean themselves.
This process took decades, caused partly by assumptions that Japan’s success could be replicated simply from copying the techniques, rather than understanding that it was more an inter-woven series of principles and beliefs. Going through the motions by sitting in Quality Circles and talking ‘zero defects’ did little until the activities were aligned with the strategies and management of the organization. Even now, many Western manufacturing companies struggle to implement these principles and achieve the desired efficiency savings.
Following on from the Japanese management revolution, Michael Hammer’s concept of ‘Reengineering the Corporation’ became very popular, which, alongside the Y2K issue, helped create worldwide demand for integrated ERP systems like SAP. Once again, different companies obtained significantly different levels of ROI from these initiatives and investments. Likewise in the early 2000s the dot.com boom saw many companies jump headfirst into this digital revolution, without fully establishing the best way for this new technology to be used.
I now believe we are about to move into the next significant period of change – this time from automated systems. Recent months have seen the introduction of a number of new inventions that when viewed individually may appear to be just interesting but disparate tools – however, all is not as it seems.
Let’s go through the different innovations in each area of the Supply Chain…
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Kaizen is a lean production management system that originated in post-WWII Japan – it means “continuous improvement”. Every single employee is encouraged to come up with small improvements regularly. The goal? To always improve productivity, safety, and efficiency, while also reducing waste.
Top Quality Management (TQM) emphasizes long-term success through customer satisfaction. All employees participate. Decision-making and strategies must depend on hard evidence, data, and statistical analyses.
The Year 2000 Problem (Y2K) was also known as the Millennium problem or Y2K bug. It was a programming crisis in which computers could not distinguish between the year 2000 and 1900.
Enterprise Resource Planning (ERP) runs on computer hardware, networks, and uses online databases as an information repository. Business management software used to collect, store, manage, and interpret data from activities such as:
-product planning, cost, development
-marketing and sales
-shipping and payment
ROI is short for Return on Investment.
At the turn of the 80s till early 2000s, Japan’s newly articulated business ideology of continuous improvement steered its industries towards profit and success, most notably the automobile and manufacturing sectors. So much so that the West began to adopt the Japanese-influenced Kaizen, TQM, Lean, and Six Sigma systems. Fast forward to 2014 and we see a dip in Japan’s growth – competitors from China, South Korea, and elsewhere have quickly displaced Japan as the top dog in the East Asian sphere of influence. The electronics and automobile industries were the quickest to suffer. In 2012 alone, Japan’s major electronic firms were estimated to have lost $21 billion to other competitors.
Over the years, these large companies have learned that heavy investment and strict adherence to the values of “continuous improvement” have actually harmed innovation as opposed to fostering it. According to economist and professor at Dartmouth’s School of Business, Vijay Govindarajan:
“The more you hardwire a company on total quality management, the more it is going to hurt breakthrough innovation. The mindset that is needed for discontinuous innovation, are fundamentally different.”
What is missing in continuous improvement schools of thought boils down to (but is not restricted to):
-A certain degree of flexibility and responsiveness to changes within the market
-Considerations of how an organization can change to adapt or survive a disruptive or threatening scenario
-Room for creativity
-Room for human considerations/decision-making (albeit with a degree of inconsistency and flaws) within a system based almost entirely on data, statistics, numbers, and calculations of efficiency.
How can businesses implement management systems that balance both continuous improvement and innovation? What sorts of changes can we make to existing beliefs about the ways in which we manage numbers, people, products, and services as a whole?
Demand Capture and Creation
Any innovation that supports both marketing and operations is going to have an impact – and the introduction of intelligent vending machines like the Coca-Cola Freestyle has certainly done that. Designed by Pininfarina, the Italian car design firm, it is a transformational innovation; a game changer for the FMCG industry. First introduced 3 years ago, the Freestyle allows users to choose more than 120 soda brands or create new combinations simply with the touch of a screen, using pharmaceutical micro-dosing technology derived from the medical industry.
As arch-rival PepsiCo struggles to retain market share and Reuters describes its share price as “languishing”, Coke’s creation of a new business model via the Freestyle machine has seen the company prosper once more. It is in widespread use in America and has proven widely popular, with restaurants clamoring to have the Freestyle installed, as those outlets that have installed the machine have recorded hundreds of percentage points increases in sales.
The machine is much more than a simple dispenser; it is a data capture tool and a marketing device. It also transmits supply and demand data to Coca-Cola and to the machine owner, including which brands are sold and at what time of day. The Freestyle has also demonstrated the effectiveness of releasing new trial recipes in select markets, gathering consumer feedback and then beginning full-scale production. This is a powerful concept and moves the business ahead of its competitors in terms of its drive to be truly demand driven. A Coca-Cola spokesman stated that,
Freestyle’s data tracking technology gives us the ability to gather consumption data to optimize our product offering and assess where there are opportunities to create new retail brands. These machines also help our trade customers to manage their beverage inventory more effectively so they have the right brands in stock.
Coke Freestyle machines are GPS-enabled, supporting location management and movement; they self-diagnose, sending alerts when it encounters a problem, allowing for remote diagnostics and repair capabilities. They also self-replenish, sending an alert with ingredients are low.
Retailers are also changing the way they interact with their customers, and being more strategic about segmenting their offerings to suit the different needs.
Social media has been used as well by Coca Cola via ‘Virtual Freestyle’ Facebook apps that let fans interact with the dispenser before ever visiting one in real life. They could also request a dispenser to be added to a location near them, resulting in requests for dispensers in more than 1,500 towns and cities across the US – the ultimate Demand Driven Supply Chain.
Like Coke, Unilever has seen the opportunity from intelligent vending machines. Their ice cream brand Wall’s is rolling out a digital vending machine, called ‘Share Happy’, which uses face-reading technology and provides them with a dense set of sales data such as the type and number of items sold, the time of day that sales take place as well as the user’s age bracket, gender and ethnicity via face recognition software. This ‘in-the-field’ research is already being used for future product development, marketing and media buying activity.
Retailers are also changing the way they interact with their customers, and being more strategic about segmenting their offerings to suit the different needs. Long gone are the days of mass marketing where every customer was assumed to want the same thing. In Seoul, HomePlus, Tesco’s South Korea brand has established ‘virtual stores’ in the city’s underground subway, aimed solely at busy professionals who have little time to shop, and conveniently located on their route to and from work.
Using a virtual display of shelves of products selected specifically for this segment of customer, this channel allows the customer to scan the relevant QR code of the desired items with their HomePlus Smartphone App in order to procure them and organize home delivery. HomePlus’s App is now the #1 shopping App in Korea, with over 900,000 downloads since it launched in April 2011.
The whole concept has proven so successful amongst 20 to 30 year olds that HomePlus is expanding the concept out of the subway to more than 20 bus stops close to local university and other pedestrian areas.
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Although Pepsi beverage sales did not increase as much as Coke during 2010-2012, partly due to Coke’s popular Freestyle machine, Pepsi did announce first quarter 2013 profits that were almost twice as high as that of Coke. In fact, Pepsi took home about $5 billion more than Coke did in year 2013. Why? Diversity. 3/4 of Coke’s revenue comes from carbonated drinks; for Pepsi that market makes up only a quarter of its revenue. Pepsi is a food brand more so than it is a beverage one.
There is no doubt that as Coke comes up with novel and entertaining technologies to reformat the brand’s offerings, its revenue will climb. However, it’s still to be seen whether the steady growth is sustainable and lasting. People are increasingly put off by sugary carbonated drinks, which make up 75% of Coke’s sales.
Will superficial innovations such as the Freestyle machine continue to stave off loss and irrelevance? Does purely technological and data-driven methods be enough?
Big Data, Cloud Computing and APS
These new and innovative ways of capturing consumer information and demand generate huge amounts of data. According to the EMC Corporation, by the end of 2012, 2.7 zettabytes of global digital data will exist. What has become known as ‘Big Data’ is about the opportunity that today businesses can turn this huge amount of data into business value. Luckily the capability to collect and analyze these huge amounts of data is also growing exponentially, with numerous software companies creating new analytical tools designed to extract that business value, spawning a new technology sector in itself.
The rise of Cloud Computing has helped to drive this technological advancement, as the ‘Cloud’ offers resources without having to acquire knowledge of the systems that deliver it. Which is important as Big Data requires significant management, advanced technologies, new skills, huge amounts of external data and lots of data services – things which businesses would seriously question whether they need (or want) to manage when the real task is to focus on analysis to unlock the key insights and business value.
So now businesses are able to liaise with customers and consumers in different ways, extracting, storing and analyzing huge amounts of previously unavailable information in order to specifically tailor products and services – but what about the planning and replenishment of these goods and services?
In order to handle this ever increasing data volume and demand complexity, ERP software companies like SAP have developed Advanced Planning Systems (APS) that include complex demand planning and forecasting capabilities, supplier network planning, production planning, distribution planning, as well as activities such as automated procurement, replenishment, fulfillment and billing. Again, all this is now available in the Cloud.
The entire landscape can now be considered a network with nodes representing devices with varying capabilities and various functional capabilities. Planning of routes with p-to-date information from smart machines enables more detailed distribution planning, dramatically reducing costs and time to replenishment – but only for those companies with their data management and systems under control.
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Advanced Planning Systems (APS):
Techniques that deal with analysis and planning of logistics and manufacturing over the short, intermediate, and long-term time periods. APS describes any computer program that uses advanced mathematical algorithms or logic to perform optimization or simulation on finite capacity scheduling, sourcing, capital planning, resource planning, forecasting, demand management, and others. These techniques simultaneously consider a range of constraints and business rules to provide real-time planning and scheduling, decision support, available-to-promise, and capable-to-promise capabilities. APS often generates and evaluates multiple scenarios. Management then selects one scenario to use as the “official plan.” The five main components of APS systems are demand planning, production planning, production scheduling, distribution planning, and transportation planning.
In his 2007 article ‘A Robot in Every Home’ Microsoft founder predicted that we were on the verge of a robotics revolution that would have a similar impact as the rise of the PC in the 1970s and 1980s. “When I talk to people involved in robots and look at the trends that are now starting to converge, I can envision a future in which robotic devices will become a nearly ubiquitous part of our day-to-day lives.”
Robotics is not new – according to the International Federation of Robotics there are now 1.1 million working robots in the world, and in car manufacture about 80% of the production is completed by machines. Most industrial robots are large, heavy, expensive one-armed machines capable of repeatedly performing a set of precise steps, such as lifting heavy objects, cutting metal or welding. Expensive to program, incapable of handling even small deviations, and so dangerous that they have to be physically separated from human workers by cages, they remain impractical to other types of manufacturing.
Baxter is the first of a new generation of smarter, more adaptive industrial robots. Baxter’s developer, Boston based Rethink Robotics, has designed the 3-feet tall, two-armed robot with a computer-screen face, animated eyes, and the capability to automatically adapt to changing environments through cameras, sensors and software that enable it to ‘see’ objects, ‘feel’ forces and ‘understand’ tasks.
So what can Baxter do? For now, Rethink Robotics founder, Dr. Rodney Brooks states that Baxter is designed for things like material handling, line loading and unloading, product inspection, light assembly, sorting and packaging – manual jobs typically done by people. Its marketing tagline is ‘Meet tomorrow’s workmate’.
Whereas traditional industrial robots perform one specific task with superhuman speed and precision, Baxter is neither particularly fast nor particularly precise. But it excels at just about any job that involves picking stuff up and putting it down somewhere else while simultaneously adapting to changes in its environment, like a misplaced part or a conveyor belt that suddenly changes speed.
Here’s the game changing aspects:
- Price: Baxter is priced at $22,000; around the same as the average salary for a US warehouse or production worker. Only Baxter can work all day and night, doesn’t get sick, require breaks or need holidays.
- Safety: Baxter can work seamlessly alongside its human counterparts, and constantly senses and adapts to what is going on in its environment.
- Intelligence: Baxter learns. To teach Baxter a new job, a human guides its arms to simulate the desired task, and presses a button to program in the pattern. If the robot does not understand, it responds with a confused expression. Equipped with sensors and other software to help it see and understand its environment, Baxter has also been programmed to apply common sense to its environment. For example, if it drops an object, it ‘knows’ it has to get another one before trying to finish the task.
- Ease of use: Rethink positions Baxter as being more like an application than a traditional industrial robot; a plug-and-play machine that small manufacturers can use without lengthy training of employees.
Brooks claims that the robot will acquire more skills as new software comes out and third parties invent functions, making it ideal for doing some of the most boring and physically tiring factory chores. Brooks likens Baxter to the iPhone stating that they both represent a sea change in computing technology, and like the iPhone Baxter will become a platform for others to develop new applications for.
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Robots like Baxter are only the first prototypes of the machines that will take over repetitive and laborious tasks. At the end of 2013, Rethink Robots laid off a quarter of its employees due to its decision to focus on markets that have been the most receptive to Baxter – plastics manufacturing, consumer goods, warehousing and logistics.
According to founder Rodney Brooks, “Our customers are not about replacing workers. They are about increasing their productivity. We’re making it more pleasant to work in factories – the grunt work is done by these machines.” Despite Baxter’s impressive learning capabilities, it must still be taught by people first. Training, maintenance, management, and repairs are nevertheless still the domains of human workers.
Pick, Pack and Put-away
Whereas robots have been used in manufacturing for some time, robots are also coming of age in a different area of the Supply Chain – the warehouse. Reducing the time that workers spend retrieving products from shelves for packing has long been a priority for many companies in order to be more responsive. The problem: traditional warehouses rely on fixed shelving, bad placement algorithms and error-prone humans. The result is an expensive operation with at best 95-98% operational excellence that has to scale linearly – the more you want to ship, the more warehouse space you need.
Like Dr. Brooks, Kiva founder Mick Mountz realized that there had to be a breakthrough in cost reduction for large scale distribution businesses to move to the next level.
The solution: a warehouse that took advantage of all the technological advances such as advanced algorithms, robotics and sophisticated software to tie it all together. Have the shelves come to the packing stations at the warehouse, rather than having workers go and retrieve each product from the shelves.
That simplicity belies the amazing economic power that a robotic warehouse system – including the necessary logistics, control systems, and software – can have in streamlining the mundane but vital task of getting goods where they are going. Kiva’s system uses game-changing automation technology that Kiva calls its “magic shelf,” or the Kiva Mobile-robotic Warehouse Automation System. Instead of having human workers walk through aisles of items across huge warehouse floors, robots do the moving and the workers stand still.
The average retail warehouse needs 20-40 people working a single shift. Kiva robots cut that down by 60-80%.
To achieve this, Kiva and its competitors have had to innovate in navigation, control systems and warehouse equipment. Kiva’s ‘bots’ can operate in multi-level facilities through the use of robot-operated elevators, making them practical in high-cost areas where warehouse owners need to save floor space. Empty bots are programmed to travel under the specially-designed pods when possible, leaving the aisles open not for the humans, but for other bots carrying pods. Behavioral programming techniques allow the bots to be working on several different objectives at once – traverse the floor, avoid other bots, align their guidance systems, and get recharged as needed. Parallel programming allows many different robots to simultaneously work on different parts of the same order.
All this technology has delivered three major benefits:
- Cost: The average retail warehouse needs 20-4 people working a single shift. Kiva robots cut that down by 60-80%.
- Increased throughput and capacity: Kiva’s robots actually self-organize and optimize the product shelves more optimally than in human-based fixed warehouses, leaving more capacity for storage and increased number of orders shipped.
- Decreased errors: Kiva’s software tracks every order and constantly monitors error-prone humans.
- The impact these benefits has had on one of the companies that used this technology was obviously significant – for on the 19th March 2012 Amazon announced that it had bought Kiva Systems for $775 million in cash.
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True, robots such as Baxter and Kiva can perform mundane, repetitive, and often “dirty” tasks better than people, but at this point, they are not developed enough to completely eliminate human touch from its spheres of industry. They do, however, redefine the nature of human labor in those settings.
This begs the question: “What will happen to low-skill workers?”
The logical answer is: “Simple! They will acquire new skills that will be valuable and irreplaceable by robots in the foreseeable future.”
Easier said than done. The direction in which automation progresses, whether for better or worse, depends ultimately on how society responds and adapts.
With Baxter doing the “dirty” work, then presumably human workers have more opportunity to engage in more creative and managerial work. After all, Baxter must still be trained and programmed, looked after, directed, and organized. Ideally, this segregation would lead to increased innovation, efficiency, and the improvement of work conditions for humans.
On the flip side of the coin, there will be societal unrest, fear, and wariness over one’s livelihood, especially in the blue collar sector. In the face of rapid automation and progress in robotics, job insecurity rises. A factory that used to employ hundreds of people will come to have a task force comprised of fifty robots and only a handful of humans for management. The low-skill workers who have been replaced must now find another source of income – but in a world where automation has usurped their utility, these workers have very little options. To survive, they must evolve.
What does survival look like in a highly automated world?
There are many changes that must come about for society to adjust appropriately:
1. Personal – the workers learn a new set of skills that cannot be replaced by robots (yet). This is dependent on what education, especially adult education, looks like and how accessible it is to people who don’t have steady incomes. This can be an especially daunting task for those who have families and others who count on them for financial support. How does one take out the time and money necessary to learn new skills when his/her child must eat?
2. Societal – society must now accommodate a growing class of citizens who are trying to find their tiny financial footholds in the world. Education centers must be rethought and revamped; affordable living spaces and amenities must be provided despite a defunct housing industry; creative thinking as a skill/ability must take on the greatest value. In short, society must adapt in a way that lends support and training for the struggling workers.
3. Political – whereas families used to be the guarantors of an individual’s well-being, now governments have become the institutions that provide safety-nets and some sort of assurance, be it physical or monetary. National endeavors such as very low-cost or universal health coverage, social security benefits, and unemployment stipends must be redefined and updated. Allocating a sufficient percentage of the budget to fund smaller, independent local social benefit programs would also take the load off of governments. Governments are commonly the most resistant to change yet they must change, if only to prevent an upheaval or social revolt.
In the end, change will only be enacted when there seems to be an overwhelming demand for it in social discourse. Fortunately, the rapid growth of the Internet and social media can spread knowledge everywhere and facilitate the necessary discussions. Public opinion is ever more powerful and influential in this day and age, and will continue to greatly influence the decisions of tomorrow.
It’s not just the factory and warehouses being transformed to a place where people become passive observers. On the 23rd October 2012 California Governor Jerry Brown signed a new bill that allows autonomous cars on the state’s roads. “Today we’re looking at science fiction becoming tomorrow’s reality – the self-driving car,” Brown stated.
Autonomous cars use a combination of computers, sensors and lasers to operate without the guidance of a driver. Google has modified a fleet of Toyota Prius that drive themselves using video cameras, radar sensors, laser rangefinder and detailed maps, creating a ‘virtual buffer zone’ around obstacles that makes it more aware than human drivers. The fleet has just logged over 30,000 miles without an accident through a ‘wide-range of traffic conditions’, the equivalent of 12 round-the-world trips. Google suggest the cars could come to the market within three to five years, taking the car from being simply a mode of transport to a mobile office.
Most of the major car companies all have advanced self-driving car projects in the works – for example Volvo announced that in 2014 it will offer a traffic-jam assistance system that allows its cars to automatically follow vehicles ahead of them int raffia moving at speeds up to 30 mph (48 kph). The U.S. Transportation Department in August started a field test of almost 3,000 so-called connected vehicles in Michigan. The cars are equipped with wireless devices that use global positioning systems to communicate with other vehicles and roadside systems at intersections. Eventually, it will be so clear to everyone that the computer is safer without the human driver, the truly driverless cars will be legalized.
Chris Urmson, an engineering lead for Google, said: “With each breakthrough we feel more optimistic about delivering this technology to people and dramatically improving their driving experience. We’ll see you on the road.”
But it’s not just cars.
Australia, with hits sky-high labor costs, has driverless trucks, trains and drills being used in many mines, replacing perhaps the world’s highest paid truck drivers. Multinational mining giant Rio Tinto has declared that the skills crisis and demand for greater productivity has forced them to take steps towards automated mining in Queensland, with driverless trains and trucks operating at their Western Australian operations that are actually controlled 1200km away in Perth. The fleet control system prevents collisions with other dump trucks, service vehicles, other equipment or people at the mining site, making it extremely safe and reliable.
However, it is in logistics where this technology will make most compelling financial sense. Currently a truck’s active period is dictated by laws preventing drivers from spending excessive periods behind the wheel. Automated trucks remove that restriction.
Scania, in collaboration with KTH Royal Institute of Technology in Stockholm, is developing self-driving trucks with the goal to increase accessibility and reduce energy consumption. Vehicles will communicate with each other real time, determine optimal routes via GPS, and even communicate with traffic lights so it knows whether to brake or continue. One element is ‘platooning’ where 6-8 vehicles follow a leading truck at a safe distance between each truck of about 25 meters. Running the trucks even closer together would reduce drag and lower fuel consumption by about 20%.
From a technology point of view, the self-driving car and truck is ready for wide-scale use. The only barrier is for governments to legalize them and for companies to build them.
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As of June 2014, the only states in the US to have legalized self-driving cars are Nevada, Florida, California, and Michigan. Interestingly, driverless cars are not explicitly illegal – the original laws did not stipulate that there must be a driver operating a car. Google essentially asked for regulation. It was a brilliant move on their part – what business nowadays demands regulation for something that did not yet exist?
Although the Google headquarters is located in California, the cars’ project leaders targeted Nevada first, where apparently the state legislature regulates quite lightly, at least compared to California. Thus Google hired David Goldwater, a Nevada legislator-turned-lobbyist, to help them pass the first bill for driverless cars. Next, Google worked with Bruce Breslow, former leader at the Nevada DMV, to draft the highly technical and complicated regulations. The internet giant de facto led the legal discourse, paving the road for the future onset of driverless cars.
Next stop: California. Although legislators and various groups, such as the Alliance of Automobile Manufacturers and the Assembly Transportation Committee, raised some concerns and hesitated to pass the bill written by Senator Alex Padilla, the bill was eventually signed by Gov. Brown in September 2012.
The concerns raised include:
1. Will automakers be liable for injuries caused by driverless modifications to their cars?
2. Should a human be present in a driverless car? To what extent must the individual have manual control over the car? Is the technology really THAT advanced?
3. What ethics will the new cars abide by? If there is a human in the car during a life-threatening incident where there is another human at stake (I.e. A swerve, car crash, hit-and-run), how does the car decide who to save?
In a poll conducted by Harris Interactive, 79% of 2039 adults said they’d be afraid of riding in a driverless car because of possible hardware malfunction.
- 59% questioned liability issues (in the event of a car crash)
- 52% were worried about hackers taking control of the vehicle
- More than 1/3 raised privacy concerns – To what extent will auto companies, insurers, advertisers, and governments collect personal data.
- 93% of people older than 65 expressed concerns; 84% of those ages 18-34 also expressed concerns.
However, another survey conducted by automotive consulting firm Accenture found that 90% of motorists are still interested in certain features of driverless technology, such as automatic braking systems and auto-parking.
There is no doubt that automated vehicles will become a prominent fixture in tomorrow’s world, especially in the transportation & shipping industries. However, there is still valid fear about driverless technology that must be addressed and assuaged. It will be very interesting to see how Google will spearhead this legal endeavor.
The Automated Value Chain
While individually these may appear to be simply interesting and innovative technological advances, the real opportunity is in aligning these together to radically transform the end-to-end Supply Chain. The following describes the potential:
Automated Value Chain
- Immediate demand signals are received via intelligent machines, including information on the customer’s preferences, location, age and background, and the machine’s current stock levels and consumption data.
- These demand signals are combined and processed by Big Data analytical tools, passed down as replenishment requests to a cloud based ERP system, automatically processed and converted into either manufacturing and/or procurement demands. Purchase requisitions are automatically converted into purchase orders and electronically dispatched to the relevant supplier.
- Suppliers will process these orders automatically on their cloud based systems, which generate replenishment demands that will be picked, packed, and loaded by warehouse robots onto an automated truck. The component supplier’s system will communicate delivery information to the manufacturer’s system, and a delivery time and warehouse slot would be confirmed automatically.
- The automated truck will deliver the component parts to the supplier, where robots will put them away until the automated planning system, responding to all of the demand and supply signals, instructs the warehouse robots to move them to the assembly line.
- Manufacturing robots like Baxter will assemble the finished product – which will then be transferred by bots to the finished goods warehouse, then picked and packed onto another automated truck that will deliver the finished products based on a pre-calculated optimal route defined by the cloud based distribution planning system that is in constant GPS contact with the trucks.
- ‘Big Data’ analytical tools will be used to provide accurate replenishment forecasts, production and distribution plans, helping to continually establish the optimal cost-to-serve models, stocking profiles and manufacturing schedules.
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Although a completely automated supply chain like the potential one described above is quite disruptive to job markets, it will also provide extensive benefits to consumers. Manufacturing and market risk management would get a huge boost – computers will be able to track all the data and information provided by each link in the chain.
For example, Georgia Nut Co. Implemented a successful and relatively smooth recall of its pistachio products after inspectors found the presence of salmonella. One of its customers was a firm owned by Kraft Foods. Fortunately, Kraft had the infrastructure to track all of its activities and goods that flow toward either side of the supply chain (from the supplier to the retailer). It identified and quickly recalled suspect shipments. It was also able to trace the contamination to a supplier in California.
This is just one example of how an automated system can boost efficiency, response-time, and control over a company’s supply chain. However, companies also know that there are many variables outside of their control. Natural disasters, individual health concerns, theft, fluctuation of transportation prices, and the overall economy – all play a distinct role along supply-side of the chain. Companies must learn how to most effectively deal with such factors or risk being crippled by them.
Interestingly, one of the greatest risks since the recession in 2008 is not supply-side but demand-side: reduced consumer spending. Manufacturing risks aside, this fact greatly shapes how companies increase their profits. It’s not just about cutting costs anymore – they must also obtain more revenue from consumers in a time when individuals are cutting down on their own costs too. In many ways, the consumers are more empowered and can leverage their demand with more influence.
There are already certain projects, such as the robot Pepper, that attempt to create a sentimental robot. Pepper can talk well and display emoticons on its screen that reflect some semblance of human emotion. Granted, these emotions are pre-programmed by its parent engineers, but it’s still a sizable step towards a deceptively human robot. What happens next is completely unfathomable.
What is automation’s role in customer service? Are robots and software programs sufficient for customer service? Will they supplant customer service agents?
There will be positives and negatives from the automation revolution. Robots like Baxter and Kiva’s bots could, for the first time, bring the benefits of robotics and automation to areas of work where it never made sense before. This could help Western countries compete in the global manufacturing market against low-wage labor countries, making it more efficient for companies to re-shore and make products nearer their customers.
How important is low-cost labor when you don’t actually need labor?
Another silver lining is the possibility of improved working conditions for those remaining in robot enabled warehouses, as they are typically quieter and cooler providing more reasonable working conditions, in contrast to the conditions reported at some non-robotic Amazon warehouses.
Automating with robots also creates jobs, in refitting the facilities as well as designing and building the robots, pods, and control systems. These are certainly better quality, and require more skill, than the jobs that are eliminated, although they are not nearly as numerous.
New types of jobs will be created. Take ‘Big Data’. According to McKinsey by 2018, the United States alone could face a shortage of 140,000 to 190,000 people with deep analytical skills as well as 1.5 million managers and analysts with the know-how to use the analysis of big data to make effective decisions. Big data and cloud computing has also created a new industry sector, with numerous innovative new companies rising up, and creating employment opportunities.
There will be dramatic changes to the dynamics of the workforce, with an emphasis on acquiring talent that has a high level of design and creativity skills. There will be a massive reduction in functional, ‘I’ shaped skills, but a massive increase in demand for “T” shaped skill-sets with people who understand the customer and can shape the integrated end-to-end Value Chain to meet their needs.
This in turn will have a significant impact on old-school management styles; the command and control of teams of single function employees will disappear; replaced by empowerment, multi-functional skillets and the freedom to try things, innovate, and to make mistakes without blame.
Blue collar blues?
A critical issue is whether the gains of these efficiencies will simply benefit the bottom line of multinational corporations. Income inequality is a growing problem in the developed world, and one of the main factors is the lack of good paying jobs for lower-skilled workers. Manufacturing and logistics used to be a place where lower-skilled workers could got to make a decent living, and robotic automation will almost certainly mean lost jobs for an already struggling low-skill workforce.
In the Robotic Age, how will the men who don’t own the machines provide for themselves?
The Far East will not be immune either. Terry Gou, the Chairman of Foxxconn has addressed the controversial issue of poor working conditions, which led to a spate of workers committing suicide, by announcing that they will build an industrial park in Taiwan to produce 1 million robots in three years in order to replace 500,000 jobs.
The march of technology, and Moore’s law, also raises the question of when robots will simply be able to build themselves.
The battle lines between man and machine are already being drawn. Australian mining unions, outmaneuvered by the introduction of autonomous trucks and diggers, are switching from strike threats and wage demands which provide increased motivation to automate, to humanistic appeals about retaining a sense of community.
Businesses in control of their Supply Chains will be able to align and exploit these new opportunities, whereas companies lacking control will not.
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The question of where blue collar workers might find a living in an automated world is a dire one and must be taken deeply into consideration. The way in which such workers view this impending technology is rather delicate; it can spiral down into a fire of resentment, mistrust, and anger. Safety nets must be erected to help cushion the changes caused by rapid technology progress, or else those who fall will surely rise up in indignant, and justifiable, resistance. Whether these safety precautions are undertaken by governments, philanthropic organizations, or by citizens themselves remains to be seen. What is sure is that action-oriented dialogues between many different perspectives and understandings must take place. Public discourse can drive policies, influence decisions, shape ideas, spread knowledge, and bring about constructive changes.
We need to talk about this. Not just about the pros and cons, benefits and costs, ills and misfortunes, or the morals. We need to talk about the potential problems and brainstorm viable solutions. As technology progresses through innovation, so must our individual lifestyles, values, and actions within society.
In the same way Japanese car manufacturers controlled the market through their ability to perform at previously unseen levels of operational efficiency, these new developments could once again threaten to create a performance divide. Businesses in control of their Supply Chains will be able to align and exploit these new opportunities, whereas companies lacking control will not. If one company is restricted by working and driving regulations, unions, minimum wages, off-shored manufacturing and long lead times, while their competitors have invested in systems that involve none of this, then two games are being played with two sets of rules and two fundamentally different costs of playing.
The real casualties will be in complacent companies that still lack clear, cohesive strategies and integrated planning and execution capabilities. Businesses still operating in functional silos will struggle to compete with their levels of inefficiencies against proactive competitors who will develop fully integrated and systemized control towers and an automated Supply Chain and may, like the Western car manufacturers in the 70s and 80s, be left trying simply to survive.
The issue will not be simply about blue collar job losses from robotic innovations – it will be from the subsequent collapse of companies that have been complacent for decades and failed to make the opportunity to understand and control their end-to-end Supply Chains. Robots need to know what to make, pick, pack and ship – and if the company hasn’t got control of its plans, schedules and data then robots will not help.
In the same way that companies with the same ERP system get widely different results, robotics will also delight some, and disappoint others. Companies cannot exploit these innovations unless they have the basics in place; and they need to wake up quickly to this fact, realize that they simply cannot to live off past performance and prepare themselves for Supply Chain 3.0 – the automated Supply Chain.
This article was originally published The European Business Review. We were given the permission to transcribe the article from the PDF for your intellectual pleasure.
About Sean Culey
Sean Culey is a member of the European Leadership Team of the Supply Chain Council, the global, not-for-profit center for Supply Chain Excellence, and founder of Aligned Integration Ltd. Previous to this he was CEO for SEVEN Collaborative Solutions, and Principal at Solving Efeso.
Sean has worked around the globe helping companies create dramatic increases in profitability and growth, breaking down their barriers to success through the alignment and integration of their people, processes, systems and data. He helps companies to navigate the journey from functional silos, creating foundations of control that enable continual improvement and innovation via his ‘Aligned & Integrated Organizations’ (AIO) approach designed to create end-to-end, integrated customer and profit focused Value Chain teams. This approach also helps companies align their Integrated Business Planning, Management, and Execution processes. He also has 20 years’ experience of creating value from ERP investments such as SAP, and is an expert in helping companies to understand how to realize the value of these investments.
Sean is a frequent conference chair, speaker and author with many published articles on Organizational Greatness, Cultural Change, ERP and Value Chain excellence. His book ‘Becoming Great (by taking everyone with you) – Developing the Aligned and Integrated Organization’ is due to be published in late 2013.
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