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The Age of Digital Disruption: The Smarter Supply Chain

AI allows a proactive approach to rising above ever-changing challenges
 By Ron Castro

We are at a significant inflection point for the manufacturing industry. Opportunities for disruption are unprecedented, from redefining business models, to how we best deliver value, to how we develop the right culture and skills. Supply chain professionals appreciate the challenges of managing global networks in an increasingly complex and volatile world. Opportunities for disruptions are plenty: complexity of globalization, protectionism, effects of extreme weather, natural disasters, global political tensions and trade implications, and new disruptors from unexpected players in the market to name a few. When circumstances change as frequently as they do in today’s environment, decision making must be fast, unbiased, fact-based and, most importantly, with “noise” segmented from real risks.

In addition to the operational challenges that can rattle your supply chain at a moment’s notice, clients’ expectations continue to increase. Customers have grown to expect real-time transparency, ‘one day’ delivery, an improved consumer experience, customization, and more, all adding more responsibility with the expectation of flawless execution of the supply chain.

There has never been a time which was more challenging and exciting for our supply chain professionals than today, but there has also never been a time with more opportunities to get help through exponential technologies.

Disrupt, Adapt, or Perish 

The biggest challenge in this new digital era becomes how best to leverage the stacking of new innovative technologies to become a disruptor vs. being disrupted. Those who react the smartest and fastest will differentiate in the market, reaping significant benefits. To manage the workload and understand the impact of disruptions, supply chain leaders are making investments on emerging technology solutions to analyze massive amounts of data from existing silos and touchpoints of their supply chains. The use of advanced analytics, artificial intelligence, IoT and exploration of technology platforms such as blockchain are designed to enable visibility into operations, with the anticipated results of better and faster decision making, operational improvements, yielding higher value to clients and greater financial returns.

While new technologies work to provide improvements within their respective silos, I believe that in order to bring the value to a broader level, there is a critical need and incredible opportunity to tie this data together through a single, connected digital stream. AI-enabled supply chains leverage these technologies and data, helping enterprises to proactively handle an ever-changing environment, with the potential to deliver exceptional customer experience and empowering supply chain professionals.

IBM Institute for Business Value identified seven key success factors for successful digital and cognitive transformation of organizations1:

  1. Create a new business platform built for competitive advantage
  2. Leverage the incumbent advantage in data
  3. Architect your business for change enabling agility and flexibility
  4. Redesign your workflows around AI
  5. Get agile, change fast and deploy faster
  6. Reinvent your workforce to ignite talent
  7. Ensure trust and security of your business platform

These success factors form the outline of the playbook for successful design and deployment of a cognitive supply chain. In IBM’s supply chain, we are following this playbook for our own digital transformation journey.

Data: The Next Natural Resource 

“Data will be the greatest natural resource,” says Ginni Rometty, Chairman, President and CEO, IBM Corporation.

The ubiquitous nature of data throughout the world over the past decade is a well-known fact. Digitization has resulted in an unprecedented amount of information collected, where organizations that can harness the incredible power of this information can reap the rewards, while those that fail to derive insights may see themselves drown in a sea of misinformation. Just as crude oil has few uses until it is refined into various petrochemicals, raw data will provide little insights until it can be constructed into meaningful insights for our organizations.

 

 

The advancement of technology has matured enough to match the proliferation of data, our world’s next natural resource

The pace that data is being gathered and created is growing exponentially, with 90% of the world’s data created in the past two years2. About 80% of the world’s data is proprietary, being secured within an organization’s firewall3. Having AI integrated into your business to understand this data is increasingly becoming essential. But how do you secure and protect your data, ensure you don’t get biased information, provide transparency and derive the right insights? Reliable AI cannot exist without the proper IA (Information Architecture). To address this, in IBM’s supply chain we have implemented a cognitive enterprise data platform where our critical data is connected and stored to establish ‘one version of truth’. When establishing this IA, it is crucial to consider the relevancy, timeliness, trustworthiness, bias and diversity that factor into data. Once you have the correct architecture, you can apply your AI to best leverage the incumbent power of structured and unstructured data, whether on-premise, in the cloud, or from a multiple of cloud providers.

In a complex supply chain, we are bound to face areas where there will be inconsistencies in the data that we receive, especially when dealing with external entities beyond our control. While AI can provide great insights into our data, it can only provide advice as accurate as the data that feeds it. This is where blockchain and IoT technologies can help us get closer to the truth compared to traditional methods of data collection. In our supply chain we have seen blockchain provide benefit in providing immutable and secured data around customs declaration and supplier parts provenance, and IoT is helping us get near-real time status on the location of our shipped goods.

Leaders are Acting Now 

Supply chain leaders across the industry are beyond realizing the importance of pulling improved insights from their data – they’re on their way. In 2018, the average supply chain accessed 50 times more data than just five years earlier 4. But leaders know that just accessing this data is not enough. They are working on plans to get smarter by weaving AI into their operations in order to better address their customers’ habits and business challenges.

Looking at organizations across the globe, we can see the segmentation of the types of digital transformation leaders. Reinventors, about 27% of companies, are those that are leading the way when it comes to innovation, helping them outperform peers in both revenue growth and profitability over the past three years6. The rest of the pack is filled out with Practitioners (36%) who are starting to dabble in applying these transformational technologies, and Aspirationals (37%) who lack the proper vision and strategy 6. For leaders in the Aspirational category, it is imperative you start to apply these transformational technologies as the journey to become an innovator in your space could be long. With rapid changes in industry and increasing customer demands, making the step to the digital age is becoming ever more important.

The time to act is now and following the seven success factors laid out in the beginning of the article is an excellent place to start. By establishing a strategic business platform that will serve as the integration point of the data in your supply chain, building in redesigned business processes to work hand-in-hand with AI and empowering a workforce to be the best they can be, you can start to pave the future for your supply chain. It is a prime opportunity to disrupt and drive innovation, and best way to do it is to move boldly and fast.

The Future Supply Chain is SMART 

A new era of business reinvention is dawning. For many years we saw enterprises experimenting with multiple technology proofs of concept, embarking on ‘random acts of digital’ to evaluate process impacts. We refer to this initial phase of transformation as Chapter 1.

Now as companies turn the page to Chapter 2, we see the scaling of digital and AI throughout their business. Today these technologies are becoming embedded in core processes, underpinned by responsible stewardship.

We see a fundamental shift when comparing Chapter 1 and Chapter 2: While in the past organizations engineered processes for efficiency and imposed them on workers to direct their actions, they are now designed for responsiveness. AI and exponential technologies are liberating humans to make more informed decisions on their own based on situational awareness. While former ERP transformation optimized operations, it also locked them into given processes.

Domain and industry-specific workflows must be re-imagined, not just layeingr AI on top of old ways of working. The best is to have a “green field” strategy for your business and ingrain AI and exponential technologies there. Chapter 2 brings forward new business platforms where workflows aren’t just automated, optimized and efficient, they are also agile and intelligent. Having AI infused, the adaptive operational processes will continuously learn and will be self-aware. (Figure 4)

Previously, business processes were driving technology and innovation; now technology and innovation create an unparalleled opportunity to redefine business processes. The “outside-in” digital transformation of the past decade is giving way to the “inside-out” potential of data exploited in your processes with these exponential technologies. At IBM, we call this next-generation business model theCognitive Enterprise.

IBM in Action: Selected use cases 

In IBM’s supply chain we are reimagining our workflows based on the vision of creating a universal business platform to provide real-time status and decision-making assistance backed by data, analytics and AI. Our cognitive supply chain advisor creates situational awareness for each supply chain professional and guides them within their new, flexible workflows. The ‘machine’ assist and augment our employees by sensing risks and identifying disruptive events in the end-to-end supply chain. The machine also provides recommendations on how best to manage the situation and learns with the human through feedback loops on decision making as well as on the outcome of process adjustments.

Instead of providing traditional reports and raw data to analyze, we’ve embedded analytics, automation and AI into our new business processes, enabling quicker and more accurate decision-making. AI-recommended mitigation plans for supply constraints, build decisions and earlier shipments have become a reality in our IBM supply chain to fundamentally change the way that our supply chain professionals work (see Figure 5). With each incident and each interaction, the workflow learns and improves.

In IBM Manufacturing, we have been able to completely reinvent the way we visually inspect for quality and conduct our assembly processes by implementing an innovative visual recognition solution based on IBM’s IoT and PowerAI Vision solution. With it we were able to decrease the time to manufacturing completion and strain caused from manual inspections while increasing the accuracy and confidence in these parts and products. In our outbound logistics process, we are deploying smart sensors which signal not only real-time physical location of our finished goods deliveries on their way to our customers, but also highlight out-of-spec situations in temperature, humidity and tilt during transportation. Those visual AI and IoT solutions provide us critical, real-world information while we use blockchain technology to protect our digital information against data inconsistencies and change.

We don’t drive our supply chain transformation with a ‘big bang’ approach. We started small and are now growing fast using agile and design thinking methodologies. We base that transformation on a single, re-invented business platform and a centrally managed robust blueprint of our data and application strategy.

The Evolving and Elusive New Talent 

We believe that a proper strategy for developing new digital skills for the next generation of talent and leveraging the skills of our current talent is a key success factor. The roles for any and all jobs may evolve. As a supply chain leader, I’m thrilled at the opportunity to help define the new roles of the future and the required skills.

The rapid change of technology creates the incremental challenge of having people constantly involved, engaged and informed. This challenge can be best addressed by driving transformation and innovation from the bottom up, with needs and value to business coming directly from business focals in cross-functional agile teams. Domain captains review and prioritize the funnel of projects with the product owners. Prioritization is finalized with domain executive sponsors and delivered by agile development teams. All users are kept up-to-date by operating scrum of scrums meetings, driving adoption through cognitive advocacy teams, maintaining an online community and organizing frequent cognitive expos accessible to every member of the team (Figure 6).

In an AI-enabled company, even newcomers can have access to AI trained by internal and external subject matter experts, giving them insights into relevant data and assist them in making fact-based decisions based on end-to-end analysis. The organizational culture may have to adapt and transform with these new realities.

In our experience, it is imperative to create a systematic and structured approach to identify, collaborate, coach and grow the required skills and talent. A strong focus on skills development for existing employees combined with recruiting new talent has proven to be a winning formula. Food for thought: As a potential new hire, which company would you like to join? Which company would you recommend to your friends or your kids? We believe those companies that start their AI integration earlier will get an advantage attracting and developing the best talent.

The Evolving and Elusive New Talent 

We believe that a proper strategy for developing new digital skills for the next generation of talent and leveraging the skills of our current talent is a key success factor. The roles for any and all jobs may evolve. As a supply chain leader, I’m thrilled at the opportunity to help define the new roles of the future and the required skills.

The rapid change of technology creates the incremental challenge of having people constantly involved, engaged and informed. This challenge can be best addressed by driving transformation and innovation from the bottom up, with needs and value to business coming directly from business focals in cross-functional agile teams. Domain captains review and prioritize the funnel of projects with the product owners. Prioritization is finalized with domain executive sponsors and delivered by agile development teams. All users are kept up-to-date by operating scrum of scrums meetings, driving adoption through cognitive advocacy teams, maintaining an online community and organizing frequent cognitive expos accessible to every member of the team (Figure 6).

In an AI-enabled company, even newcomers can have access to AI trained by internal and external subject matter experts, giving them insights into relevant data and assist them in making fact-based decisions based on end-to-end analysis. The organizational culture may have to adapt and transform with these new realities.

In our experience, it is imperative to create a systematic and structured approach to identify, collaborate, coach and grow the required skills and talent. A strong focus on skills development for existing employees combined with recruiting new talent has proven to be a winning formula. Food for thought: As a potential new hire, which company would you like to join? Which company would you recommend to your friends or your kids? We believe those companies that start their AI integration earlier will get an advantage attracting and developing the best talent.

 

 

AI-fueled workflows and capabilities will continue to move supply chains from pure cost centers to value drivers

Bringing it Together 

The exponential growth of available data and deeper insights combined with innovative new technologies and new ways of collaboration are redefining how supply chains are managed. There is an unprecedented opportunity to implement workflows that are intelligent, flexible and that continuously learn, building a smart supply chain.

We are in a unique moment where AI-fueled workflows and capabilities will continue to move supply chains from pure cost centers to value drivers. The advancement of technology has matured enough to match the proliferation of data, our world’s next natural resource. Transformative technologies like blockchain, 5G and IoT are being leveraged to access data to provide fast and actionable insights with automation and AI, and being integrated into a cohesive business platform with intelligent workflows. These forward-thinking companies, always ready to adapt, can differentiate themselves from their competitors.

We are fortunate to be supply chain professionals at such a critical inflection point, an opportunity to disrupt and win. We have the opportunity to gather insights from all available data, especially incumbent and proprietary, and leverage these exponential technologies for fast and optimal reaction. This is an exciting time, one that will fuel the next round of innovation using AI to build the smarter supply chain, a fundamental pillar driving higher value for the cognitive enterprise.

Are you ready? M

 

  1. “The Cognitive Enterprise: Reinventing your Company with AI” IBM Institute for Business Value.
  2. “2.5 quintillion bytes of data created every day. How does CPG & Retail manage it?” IBM Industry Insights.
  3. Rometty, Ginni. “We need a new era of data responsibility.” World Economic Forum. January 21, 2018. https://www.weforum.org/agenda/2018/01/new-era-data-responsibility/
  4. Ellis, Simon. “The Path to a Thinking Supply Chain.” IDC. August 2018. https://www-01.ibm.com/common/ssi/cgi-bin/ssialias?htmlfid= WHW12345USEN&
  5. “Welcome to the cognitive supply chain” IBM Institute for Business Value.
  6. “Incumbents Strike Back: Insights from the Global C-suite Study.” IBM Institute for Business Value. February 2018. ibm.biz/csuitestudy

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