The Evolution of IBM's Transparent Supply Chain
The Need for Transparency
Many organizations face questions relative to the strategies they should put in place to thrive in a customer-centric economy – and an environment where deep infrastructural changes are being driven by disruptive technologies and the rapid emergence of digital commerce channels.
Faced with these forces, supply chain managers are recognizing that while cost optimization is important, equally important is improved agility in responding to shifts in customer demands, requirements and market conditions. In this dynamic environment, successful organizations must be able to respond and react quickly to information and events, as unexpected supply chain disruptions.
Supply chain visibility and transparency are highly necessary, yet insufficient, capabilities for enabling supply chain responsiveness. They must be accompanied by a deep set of capabilities that drive alignment between parties both upstream and downstream and provide access to real-time data to drive improved responsiveness.
But how does a large company begin this journey? Is this a function of technology investment, analytical skillsets, a new orientation, or an organizational redesign? In this paper, we examine how one organization, IBM, launched their journey towards a more transparent, intelligent and agile supply chain.
The IBM Supply Chain: Roots of Change
IBM, like many large enterprises, is under continuous pressure to drive value – and the supply chain is certainly a primary source in driving that value. The IBM Supply Chain organization, frequently an early adopter of new technologies, understood that the [market] was at a new inflection point with several transformative technologies – including Cloud, analytics, the Internet of Things (IoT) and cognitive technologies – reaching a level of maturity, ubiquity and affordability.
The leadership team recognized that these technologies could play a transformative role in the supply chain; helping the company develop a more intelligent and agile supply chain. After a thorough self-evaluation, the leadership team identified four areas in which to drive supply chain improvement.
Explore the four areas for improvement the leadership team identified.
1. Responding to Disruptions
As one IBM executive noted, “we didn’t identify risks and issues early enough.” In retrospect, the signs of a disruption were usually evident, but the company did not have sufficient data and insight to consistently look for them ahead of time. The pace of information and team response went along like a raft in the river.The organization was not consistently looking ahead or steering the raft. It typically was a reaction to events.
2. Right Information at the Right Time
Some of the company’s risk management systems provided alerts. However, like an alert on a car dash panel, they didn’t provide information about the nature of the problem, nor the technical details on how the problem could be solved. IBM thought it was critical to identify the elements associated with events/problems, as well as the touchpoints in the network that needed to come together to address these issues. The leadership team defined an ideal alert and solution as characterized by immediate notification accompanied by the right information to make a decision.
3. Collaboration and Team Decision Making
The third critical insight was the recognition that in a large organization important decisions are made by cross-functional, cross-enterprise, and multiple tiers of people, not by individuals in a void. The speed of decision-making is critical. The challenge became, how IBM could improve team collaboration and quickly bring people together to make business decisions.
4. Learning and Capturing Institutional Knowledge
Finally, the team recognized that while they were creating “gold nuggets” in learnings and insights each time in response to a disruption or issue, there was no standard and effective way to capture and apply the key “lessons learned” to create organizational learning and improvement. In sum, there was a real desire to have information more quickly and in real-time – to be able to access information about what was happening more quickly, to respond to problems more quickly, but also to drive business insights and exploit opportunities to add value.
The Transparent Supply Chain: Underpinned by a Cognitive Platform
These needs led IBM to pursue what they described as the IBM Transparent Supply Chain Initiative: a real-time connected, transparent supply chain system enabled by cognitive technology.
The facets of the IBM Transparent Supply Chain Initiative are illustrated here: the red triangle signifies the synergistic power of combining deep visibility, real-time data and analytics, and cognitive technology.
Together these components create a supply chain with:
- A single version of the truth (enabling deep visibility)
- Data captured and available in real-time(enabling agile response)
- Cognitive systems that connect and collate information from multiple systems/sources (enabling insights and recommendations)
These elements create an unparalleled, intelligent solution that continuously accrues knowledge and delivers value. The core values of the transparent supply chain are enabled by technology, but the cultural and business process shifts that accompany its use also drive success.
Detailed Visibility across the Supply Chain
IBM leveraged its Watson cognitive technology, advanced analytics and visualization of data to provide deep and detailed visibility across its supply chain. The team established end-to-end links to help understand risks on component supply and transparency into:
- where parts are produced
- who they are purchased from
- when there is a disruption or event
- what parts numbers are impacted
- which products are impacted
- which deals will be impacted
The system is also tied into quality analytics, creating a warning system that managers look at to understand the impact of changes in material, and every aspect of quality including Key Performance Indicators (KPI’s), including manufacturing floor defects, field warranty rates, and repairs with suppliers. These KPI’s are tied in to impacts on end to end system efficiencies, throughput rates, and clarity on sources of potential waste throughout the system.
Finally, IBM captures insights on weather, IoT data (like shipment tracking), social data, fulfillment systems, and customer data to create a real-time feed of data on delays in product flows, which is translated into external shipping delay alerts to clients, communicated in real time.
IBM also recognized that organizations are rapidly moving into the era of real-time supply chains, which enable managers to understand and predict what internal users and customers will need as soon as new demand data becomes available – or even before customers themselves recognize their needs.
IBM understood that response velocity is becoming a capability that will define competitive survival. To quickly respond to changes, IBM established real-time transparency into events and material flows, which in turn “at the edge” and the growth of digital ecosystems.
IBM, and other large/complex manufacturers, rely on not only internal data in real-time, but external demand signals from ‘big data” collected through multiple channels. Cognitive technologies and connected systems and sources of data will allow supply chains to sense and respond to more diverse forms of information then in the past, being generated through digital sensors (Internet of Things), analysis of social media and e-commerce. Organizations are only now beginning to understand how to leverage that data to make informed decisions around order fulfillment, forecasting, logistics and supplier management that enables them to support customers’ changing needs. This is a major shift, as organizations have very rigid planning systems and can no longer afford to drop forecasts into spreadsheets and run manual planning methods.
IBM has seen its data retrieval times reduced by more than 75 percent and supply chain disruption management shortened from 18-21 days down to just hours since using Watson cognitive technology and starting its Transparent Supply Chain Initiative.
Cognitive Insights and Continuous Learning
When process data is rapidly digitized and communicated, it becomes easier for individuals to spot disruptions and risks, providing that the data is structured and highlighted in a manner that draws people’s attentions to the right things.
IBM recognized that a lot of money was being spent on expedited shipments and quality misses, because supply chain processes were not operating in the proper fashion. As real-time visibility systems mature, it becomes clear that users may become overwhelmed with streams of data, and can no longer sort the wheat from the chaff.
Cognitive Play Books
Cognitive technology is elevating the IBM supply chain workforce to a higher level by allowing individuals to have a broader view of the supply chain and enabling higher value tasks. As Watson begins to capture information and historical activities, it builds a learning capability around situational intelligence that can be used to derive multiple benefits, including:
- Rapidly enabling new employees to be integrated into the system. A new employee could access years of supply chain experience in minutes with help from Watson.
- Watson will enable supply chain workers to be better equipped with market and customer intelligence, which supports the supply chain's alignment with business and become more of a "trusted advisor."
- Watson developed playbooks create competitive advantages in the form of captured knowledge and institutional intelligence.
This evolution of cognitive technology has the potential to be very powerful – and will eventually become a key advisor to individuals in the supply chain. The key benefits of the cognitive technology are:
- First, Watson will link multiple data sources in a systematic manner to provide rapid insights into supply chain events in real time.
- Second, Watson enables cross-functional decision-making using a common source of truth.
- Third, Watson will grow institutional knowledge by capturing expert decisions, thereby spreading well-informed decision-making across the organization, and delivering a competitive advantage.
- Finally, Watson can foster the best of human capability through man/machine collaboration.