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Big Data Analytics and the Connected Supply Chain

March 11, 2015


“Our world continues to change at an increasing rate,” writes Ron Guido (@safeathome12), President of LifeCare Services, LLC. The biggest change he sees for businesses is the requirement to adapt to the era of big data. “Just when we were getting comfortable using fax machines as a replacement for postal services,” he writes, “e-mailed scans, and cloud-based repositories are replacing fax documents and hard drive storage systems. In fact, emails are giving way to short message service (texts), posts and tweets because who has time to compose and read electronic mail anymore? There is a massive proliferation of online and digital content competing for our attention every day.”[1] Guido recommends that companies think about jumping feet first into digital enterprise pool. Paul Willmott (@WillmottPaul), leader of McKinsey Digital, agrees. He writes, “It’s safe to assume virtually all companies use digital technology in some form or another. Yet getting beyond obvious and small applications of technology to drive the creation of truly ‘digital enterprises’ is vital — and presents a challenge for executives.”[2] The best place to start the digital enterprise transformation is with the supply chain. As Lora Cecere (@lcecere), founder and CEO of Supply Chain Insights, is fond of saying, “The supply chain IS Business, not a department within a business.”[3]


In a follow-on article, Guido insists that companies are going to be compelled to become digital enterprises (or as he calls them “connected enterprises”) whether they like it nor not. “Companies are being forced to change their approach to organizational design,” he writes, “evolving to a true end-to-end supply chain enterprise due to the dynamics of global commerce. This evolution of the enterprise must consider many diverse factors and newly developed business drivers in re-casting itself into the information age.”[4] He continues:

“Design criteria must take into account both developed and emerging global markets, e-commerce and mobile retailing, escalated demand for customer responsiveness and business continuity, increased and changing (non-traditional) competition, the growth of consumerism and mobility of its customers. … In order for all companies to leverage the changing marketplace, the information-rich customers and the broadening universe of its operations, they must capture, process and curate information in a way that empowers all resources of the enterprise to out-perform competition. This is what is referred to as the Connected Enterprise.”

Ray Major (), Chief Strategist of Halo Business Intelligence, believes that the transformation to a digital enterprise generally follows a path that corresponds to the kind of data it is capable of analyzing. In his taxonomy, there are five different categories of data: single source, multi-source, data cleansing, real-time, and big data.[5] Major admits “there are lots of different ways to categorize data” and “that there is not necessarily one right way to do it.” He selected his framework because, as you proceed along the continuum from single source to big data, the level of analytic maturity required to achieve optimum results increases. He elaborates on each of his categories of data:

Single Source — When companies first set out to leverage their supply chain data to improve or optimize some aspect of their business, they typically start by trying to ‘ask’ questions related to single sources of data, questions like ‘how much did we sell last quarter?’ are common, and require access to data such as the corporate ERP, CRM, HR, POS or disparate Excel files.

Multi-Source — As companies mature in their analytics, questions become more complex like ‘Do we have enough inventory to cover our orders?’ The answers to these questions usually require data to be pulled from more than one data source. Disparate data sources can be accessed through BI systems and combined, which allows for more complex and sophisticated assessments of the business.

Data Cleansing — Once companies can access their data easily through an analytic system, data quality becomes critical. Bad data = Bad decisions, so Data quality tools and processes are integral to maturing the Supply Chain BI platform. Data quality tools help companies avoid the problems associated with making decisions based on incorrect or incomplete information.

Real-Time — Becoming ever more critical in supply chain information management is the need to incorporate real-time data. Real-time data is more complicated to manage and analyze, but the benefits of doing it right are great. Intelligence in real time systems is updated on a frequent basis, either every few minutes or even continuously as new data becomes available. This allows supply chain managers to respond better to situations as they arise. Customer satisfaction, production efficiency and sales can all be improved.

Big Data — The holy grail of data the data continuum and the most complex to manage and utilize is ‘Big Data’. Big Data refers to unstructured data from external sources such as machine sensors, weather, and social media feeds that are incorporated into the Supply Chain BI system. Used properly, Big Data improves insight into the larger business eco-system.”

Boston Consulting Group analysts, Libor Kotlik, Christian Greiser, and Michele Brocca, assert, “The combination of large, fast-moving, and varied streams of big data and advanced tools and techniques such as geoanalytics represents the next frontier of supply chain innovation.”[6] Guido proposes the following objectives as essential in order to transform into a connected (or digital) enterprise:

  • Seamless access to end-to-end information linking customer preferences/needs to supply management.
  • Unencumbered network [that is] accessible across the enterprise and global marketplace.
  • Harnessing the Internet of Everything into business applications: people, processes, data and things.
  • Adoption of serialization technology: Each resource, internal or external, that links demand to supply; every unit of supply, and every product and package level is assigned a unique identifier for marshaling those resources and goods expeditiously through to fulfillment. A link is made possible from raw materials to packaging, to supply chain to consumer using serial numbers. Interoperable systems are implemented throughout the supply chain to replace the trading, shipping and invoicing of ‘products’ with ‘serial numbers’ as surrogates for the products. Returned or recalled goods can be tracked and processed properly (e.g., proper credits, restocking location). Administrative functions such as human resource management, scheduling, budgeting, project management and cost accounting become streamlined through connecting asset numbers to a time, place and function. Serial numbers can also be used to establish a direct link to the customer for brand loyalty purposes.
  • The ability to explore other disruptive technologies unique to your business and designed to collaborate seamlessly inside the enterprise and externally.
  • A smart and highly secure infrastructure, which freely enables legitimate business activities yet protects against hacking and other breaches of security.
  • Real-time analysis and curation (distribution) of transactional information to inform all business systems for purpose of continuous improvement.
  • Provision of new decision-support tools and virtualization co-capabilities to streamline scenario planning and guide investments.
  • Linking human resources and authorized stakeholders (using apps, wearable technology, mobility devices, etc.) to various parts of the enterprise to enrich the customer experience.

Kotlik, Greiser, and Brocca conclude, “Companies that excel at big data and advanced analytics can unravel forecasting, logistics, distribution, and other problems that have long plagued operations. Those that do not will miss out on huge efficiency gains. They will forfeit the chance to seize a major source of competitive advantage.” There can be no doubt that the business landscape has been forever altered by mountains of data with which businesses must contend if they are to succeed in the decades ahead. The only way to accomplish that is to transform into a digital enterprise, I agree with analysts from Deloitte, who write, “Maintaining a competitive edge means building a Digital Enterprise that’s capable of taking full advantage of social, mobile, web, cloud and analytic technologies. … It requires integration of people, processes, and capabilities to deliver an omni-channel experience.”


[1] Ron Guido, “The Information Age & the Shift in Consumerism,” EBN, 11 February 2015.
[2] Paul Willmott, “The Digital Enterprise,” Insights & Publications, November 2013.
[3] Lora Cecere, “Sage advice? Only for turkeys.eft, 1 February 2013.
[4] Ron Guido, “Creating a Supply Chain in the New Age of Commerce,” EBN, 12 February 2015.
[5] Ray Major, “Understanding the Supply Chain Data Continuum,” Halo Business Intelligence, 1 September 2014.
[6] Libor Kotlik, Christian Greiser, and Michele Brocca, “Making Big Data Work: Supply Chain Management,” bcg.perspectives, 27 January 2015.

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