Exponential Growth in Supply Chain Data
In the middle 1990s, the supply chain was fairly linear with most planning data originating from a legacy or ERP system. The Internet of Things (IoT), unstructured data streams and the like were not part of our vernacular. Today, supply chains are complex and anything but linear with significantly more data streams to consider. ERP and home-grown systems can no longer provide the capabilities needed to manage today’s complex and fast-paced supply chain operations. The total amount of business data is estimated to double every 18 months and by 2025 the World will create 463 Exabyte’s of data daily. For the more mature readers, that is roughly 213 million DVDs of data each and every day.
Demystifying Data Units
Figure 1: Demystifying Data Units
Embracing big data brings the promise of reduced costs, improved customer service, reduced risk and the ability to capture new opportunities. However, capturing the data you need is just the start of the journey. A bigger challenge is the need to transform traditional supply chain operations to a digital landscape where big data is embraced and used by a new breed of supply chain talent.
According to industry research, more than half of supply chain executives consider big data analytics a disruptive and important technology, setting the foundation for long-term change management in their organizations.
Digital Supply Chain Transformation
Digital transformation affects all areas of a company including supply chain planning. To gain executive support and funding, a supply chain practitioner needs to understand what digital transformation of the supply chain involves.
Digital transformation of the supply chain is the change of supply chain activities, processes, competencies and models to leverage the massive amounts of data generated by the Internet of Things (IoT) and related technologies to fundamentally shift, i.e., transform, supply chain capabilities.
Digital transformation of a supply chain involves creating a detailed data model, or ‘Digital Twin,’ that mirrors the intricacies of an actual end-to-end supply chain. Building a digital twin involves capturing, standardizing, blending and modeling both structural supply chain data (capacities, lead-times, network relationships, etc.) and up to date transaction data (order status, inventory positions, shipment tracking, etc.) to enable rich and continuous analysis and response to unplanned events. (Read: Making the Case for AI and Machine Learning.)
The benefits from the use of Big Data are numerous and well documented. Figure 2 shows the results of a survey conducted by Accenture2 showing a long list of reported benefits from Big Data Analytics.
Figure 2: Results Achieved Using Big Data Analytics
Listed below are few benefits from digitally transforming your supply chain:
- Foundation for Artificial Intelligence (AI) and machine learning capabilities depend on high quality, consistent and complete data.
- Winning the War for Talent: The best supply chain planning talent wants to work in data-rich environments that enable them to spend more time analyzing problems and developing value-added recommendations.
- Process Automation: A digital twin lays the foundation to automate routine process steps.
- Continuous Planning: A digital twin enables quick response to unplanned events.
- Optimal Response: Digital transformation unleashes the full capabilities of today’s powerful solutions including algorithmic optimization, which drives game changing competitive breakthroughs.
- Advanced Analytics: Often the largest benefits from digital transformation come from new insights gained from new analysis capabilities.
System Foundation Building Blocks
A successful digital supply chain transformation requires strong foundational capabilities. Listed below are a few of the capabilities that facilitate a successful digital transformation:
- Master Data Management: To develop insights and make timely decisions, Big Data needs to be clean, complete, consistent, current, controlled, and convenient.
- Key Performance Metrics: The ability to identify and measure KPIs will help prioritize and measure transformation efforts.
- Common Data Platform: Enables visibility, analysis and performance measurement of cross-functional processes.
- Advanced Visualization: The ability to view data and analysis output numerically and graphically in multiple units of measure, over multiple time-frames and at different aggregations is essential to support all functional requirements. (Read this white paper to learn more.)
- In-Memory Processing: Enables robust analysis and fast response times.
- Mobile Device Support: Provides 24×7 visibility to supply chain operations and powerful collaborative capabilities.
Building the Digital Supply Chain Team
Hiring managers continually say there is a “War for Talent” driving increased salaries, benefits and turnover rates for supply chain professionals. This is the reality. A University of Maryland/DHL study found the demand-to-supply ratio of available supply chain jobs to qualified individuals is 6 to 1.3 This ratio is only going to increase in 2020 and beyond as baby-boomers retire. Ann Grackin, CEO of ChainLink Research, in a recent blog post refers to the supply chain talent gap as, “…an urgent issue for corporations to address, since the gap stymies growth, dampens innovative ideas and programs, and limits problem solving on a day-to-day level.”4 This is especially true when it comes to available talent for digital transformation initiatives. Early adopters of digital capabilities can gain an advantage, but without talented analysts and data scientists, the additional data just takes up storage space. Listed below are a few of the needed to successfully implement and embrace digital supply chain planning.
- C-Level Sponsor: A digital transformation can involve a multi-year, multi-functional, disruptive effort that can only be accomplished when embraced by top company executives. A good place to look for support outside of the supply chain is the CFO who will often understand the value of information to drive financial improvements.
- Digital Transformation Process Champion / Leader: The digital transformation champion needs a diverse set of skills including communication and influence skills to build support for digital transformation, team-building skills to convince existing employees of the benefits of digital operations and the ability to recruit new talent. The digital transformation champion needs to be a thought leader who fully understands what is required for success.
- Supply Chain / Business Analyst: Analysts improve process performance by understanding business needs, assessing the impact of changes, determining the appropriate response and communicating recommendations to relevant stakeholders. They may be the go-to person for deeper analysis.
- Database Engineer / Data Scientists: Data specialists are responsible for gathering, analyzing and interpreting complex data used in business decision-making. Often they are also responsible for building and maintaining the software infrastructure and complex models that enables computation over large data sets.
- Machine Learning / Artificial Intelligence Specialist: Specialist that uses AI solutions to analyze data, formulate recommendations and automatically take action.
According to Transparency Market Research the number of wireless connected devices is expected to grow at a Compounded Annual Growth Rate (CAGR) of 8% (see Figure 3).6 To achieve the proven benefits of effectively using big data requires a digital transformation of supply chain planning operations. Big data can be blended with existing supply chain network and transaction data to augment and enrich a company’s supply chain digital twin enabling detailed analysis and continuous response to unplanned events. To ensure success with a digital transformation, critical foundation capabilities and the right skills sets need to be in place. Although transforming today’s traditional supply chain operations to digital operations is a daunting task, it is important to start the journey. There is one thing we can all count on, supply chain operational challenges will continue to increase.
Figure 3: Growth in Connected Devices5
1 Louis Columbus. Ten Ways Big Data Is Revolutionizing Supply Chain Management. www.forbes.com, 2015
2 Big Data Analytics in Supply Chain: Hype or Here to Stay? Accenture, 2014
3 Lisa Harrington. The Supply Chain Talent Shortage: From Gap to Crisis. DHL Research Brief, 2015
4 Anne Grackin. The Talent Gap. logilityinc.staging.wpengine.com/blog, 2017
Product Marketing Director Hank brings more than 25 years of experience building high performance supply chains. This experience includes evaluating, selecting, implementing, using and marketing supply chain technology. Hank’s graduate degree in SCM from Michigan State, numerous SCM certifications, diverse experience as a supply chain practitioner and experience in senior marketing roles with leading supply chain solution providers helps him to bring a unique perspective on supply chain best practices and supporting technology to the Voyager Blog.