Analyst(s):Noha Tohamy, Paul Lord, Christian Titze
This research presents supply chain leaders responsible for strategy with three innovative vendors whose offerings support the digitalization of supply chain. Their solutions include artificial intelligence, augmented reality and digital business platforms.
Artificial intelligence is slowly coming to supply chain, with emphasis on decision making in addition to processing of unstructured data and natural language, and uncovering complex patterns in the data.
Augmented reality and mobility are being introduced to support supply chain use cases like maintenance, services and product design.
Through digital platforms, the agriculture industry is leveraging the economics of connections with value creation through data sharing and analytics.
Supply chain leaders responsible for supply chain future trends and innovations:
Define a cohesive digital supply chain strategy prior to experimenting with innovative, nascent technology. Piecemeal investments in these technologies might distract from the ultimate vision for supply chain digitalization that spans organizational changes, new business models and offerings, and process redesign.
Work closely with your IT, business and other functions in the organization to evaluate these new technologies. Many of the vendors profiled here offer solutions that span different functional areas such as customer support, sales and marketing, and services. A multifunctional relationship can leverage your organization's efforts in vendor education or in data management.
Follow Mode 2 guidelines and expectations to pilot these technologies. Return on investment might not align with the organization's expectations from more established technology. Benefits might include lessons learned, elimination of potential solutions or co-development opportunities with the vendor to shape its product strategy and roadmap.
This research does not constitute an exhaustive list of vendors in any given technology area, but rather is designed to highlight interesting, new and innovative vendors, products and services. Gartner disclaims all warranties, express or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.
Like digital business, supply chain digitalization seeks to create supply chains that blur the lines between the digital and the physical worlds. Building a digital supply chain is a priority for supply chain executives looking to support their organization's transformation to a digital business. The scope and nature of digitalization ranges by industry and maturity level.
Digital initiatives will vary based on the organization's digital maturity level (see "Charting the Path to Digital Maturity in the Supply Chain" ). For some companies, embarking on the digitalization journey starts with foundational capabilities such as building a data infrastructure internally or externally with trading partners. For more advanced organizations, this journey revolves around the use of digital technologies and capabilities such as IoT, mobility and analytics to support trading partner ecosystems (see Figure 1).
Source: Gartner (April 2017)
As shown in Figure 1, the path to supply chain digital maturity has five stages. Organizations can undertake a variety of initiatives along the path, for example:
Starting at Stage 2 (digital supply chain functions), the organization might use augmented reality (AR) to improve its functional performance in warehousing or use IoT to improve manufacturing operations.
In Stage 3 (digital supply chain), the use cases become more about end-to-end supply chain performance. The organization might use artificial intelligence (AI) to support end-to-end supply chain optimization, taking into account cross-functional goals and constraints.
In Stage 4 (digital value network) and Stage 5 (digital ecosystem), the organization's goals revolve around improving the performance across the extended supply chain or creating value in their trading partners' ecosystems. For example, the organization might use IoT to create a digital record for its manufactured products from raw materials to finished goods. Alternatively, an organization can use conversation AI to build a direct relationship with its consumers through chatbots and cognitive analytics.
In this research, we showcase three vendors whose technology solutions can support a supply chain's maturity journey to digitalization:
Enterra Solutions offers AI capabilities to solve supply chain problems. Through deep learning, rule-based inferences, natural-language processes and prescriptive analytics, it supports the digitalization of supply chain planning processes, automating decision making or replicating human decision-making processes to augment talent.
Farmers Business Network built a digital platform that allows farmers to increase their purchasing leverage for agricultural supplies. It combines advanced data management, advanced analytics and machine learning capabilities to build an agronomic database composed of 90 million acres of precision data files on several dozen crops collected from 115,000 fields totaling nearly 13 million acres, and provides analytical insights to its members.
ViewAR offers a platform with front-end features of 3D design and AR experience, and back-end infrastructure addressing use cases in industries such as interior design, furniture retail, or architecture and construction. In addition to the platform (framework of functional components), ViewAR serves as an agency, a system integrator (e.g., front- and back-end integration) and a software development kit (SDK).
Newtown, Pennsylvania ( www.enterrasolutions.com )
Analysis by Noha Tohamy
Why Cool: The Enterra Enterprise Cognitive System (described below) comprises two main components for manufacturing companies and retailers: its Supply Chain Intelligence System and its Category Management Intelligence System. Both systems self-learn how the organization's best experts in supply chain planning and category management go about making their decisions to later generate recommendations or take automated actions to mimic and refine that logic. Additionally, the Enterra Enterprise Cognitive System can provide the planners and category management staff with actual recommendations in areas like inventory management and promotional management to propagate supply chain strategy into tactical plans.
The Enterra platform combines traditional cognitive capabilities — including data ingestion and ability to interact with natural language, discover patterns and generate inferences with varying probabilistic confidence levels — with prescriptive capabilities including optimization techniques to generate actionable recommendations given objective and highly complex sets of trade-offs and constraints.
The Enterra Enterprise Cognitive System is an AI platform that allows organizations to capitalize on big data through advanced analytics. This platform is composed of a number of technologies that allow for inferences and deductions, and discovery of nonobvious relationships in datasets, and that explain the reasons behind the inferences deduced. It also provides natural-language processing capabilities used to process unstructured data to extract information from communications such as social media posts, or business or regulatory documents, and it presents insights in natural language.
Enterra's platform also provides computational intelligence to uncover the functional drivers that explain the higher order relationships within datasets. It generates actionable recommendations that match specific product or business goals.
Enterra can be deployed as its own supply chain planning and optimization system or as an additional layer to the pre-existing planning landscape, generating insights to resolve exceptions from the primary planning solution or refining recommendations already made by other systems.
Challenges: While the advantages for early adoption can be significant, only a few companies are ready to embark on AI pilots right now. Many companies lack the data and cultural readiness for AI. Those companies ready for experimenting with AI in supply chain might prefer a platform solution from Google, Microsoft or Amazon, for example, as the overall enterprise AI platform to serve various functional areas including the supply chain. Enterra's best-of-breed platform solution can be integrated with these general-purpose platforms for additional cognitive capabilities and focus on supply chain use cases, but some companies might still be hesitant to make further investments in these burgeoning technologies.
For Enterra to continue to gain market traction in the supply chain, it must further articulate its supply chain domain expertise and its solution's differentiation beyond cognitive reasoning to decision-making augmentation or automation. Enterra must also articulate how its solution coexists with organizations' already deployed supply chain technologies.
Finally, AI deployments are typically lengthy, requiring significant change management within the organization for successful adoption. Enterra can mitigate this challenge by building relationships with consulting organizations having the experience and wherewithal for large implementations.
Who Should Care: The Enterra platform will appeal to supply chain leaders in these kinds of organizations:
Organizations looking to leverage AI for competitive advantage and to extend and improve supply chain planning capabilities.
Organizations struggling to generate actionable insights from massive amounts of data.
Organizations looking for technology that can self-learn, use big data and interact in natural language.
Organizations that would like to move beyond basic AI technologies into richer cognitive computing capabilities that can find inferences and deep relationships to decision-making capabilities that can prescribe actions to optimize supply chain performance in complex environments.
Organizations evaluating their supply chain talent strategy and investigating the role of AI in talent augmentation and virtual assistance for their planners and business users.
San Carlos, California ( www.farmersbusinessnetwork.com )
Analysis by Paul Lord
Why Cool: Farmers Business Network (FBN) is cool because it offers a cost-effective, independent, unbiased platform that brings together the collective purchasing power of individual farmers. Since 2015, FBN has combined a trusted environment with data science, advanced analytics and machine learning capabilities to build an agronomic database composed of 90 million acres of precision data files on several dozen crops collected from 115,000 fields totaling nearly 13 million acres. Insights from this platform support farmers in fact-based agronomic decision making and in purchase negotiation of agricultural supplies.
FBN Analytics employs advanced data science techniques in the collection and structuring of data related to agronomic conditions such as tillage, soil regimes, climate, irrigation, seeds and agrichemical use. It provides analytics that support a range of farming decisions involving risk and complexity (such as seed selection, treatment and irrigation). At an aggregate level, the FBN seed-soil matching analytics indicate the potential for crop yield improvements of between 2% to 10%, equivalent to an average of six bushels per acre. In regions with very high data density, the incremental value enabled by analytics is much higher (as high as 25 bushels per acre).
The FBN subscription-based business model — built on a "Farmers First" philosophy to create trust and foster collaboration — is disrupting the North American market structure, which is currently controlled by a small number of manufacturers and retailers. With a low-risk annual price of $600, FBN provides services and insights rather than selling software and technology, reducing the need for farmers to consider implementation costs and risks. FBN Direct has built a marketplace around the farmer to increase supply options and pricing transparency, neutralizing the limitations of local supplier relationships and pricing confusion caused by bundles, rebates and complex discount structures. Farmers experience immediate benefits with cost reductions as high as 50% but typically averaging 10% to 30% on agricultural inputs. In addition, FBN Direct provides access to input purchase financing and farm financing, and will eventually enable alternative market outlets for farmers' harvested products.
Challenges: FBN was founded in response to the needs of farmers, and is facing substantial resistance from incumbent channel masters, particularly retailers. 1 While FBN has grown dramatically in just two years, participation still represents a small portion of the more than 2 million American farms. Adoption will proceed as with any other innovative disruption, led by early adopters and avoided by laggards until the benefits and ease of adoption are obvious. FBN has a geographically distributed Farmer Experience team to provide adoption support and foster local relationships with members in 38 states.
FBN's most significant risk may be similar to those faced by other disruptive business models (e.g., Uber and Airbnb) if incumbents are able to hinder adoption rates by creating fear, impugning FBN's image or promoting legislation that slows adoption through regulations. Another risk factor is whether the agrichemical database will develop in a way that can continue to deliver additional value once initial insights have been monetized by farmers to sustain their participation.
Who Should Care: The rise of FBN represents a disruption in the agrichemical value chain, which is a risk for comfortable incumbents (suppliers and retailers), as well as an opportunity for suppliers that are currently experiencing growth limitations caused by the current market structure. As adoption of FBN increases, agrichemical producers will require the e-business and logistics capability to make direct shipments to FBN Direct members, as well as more competitive supply networks that can be profitable at lower prices for products that have become commoditized due to patent expiration and competition.
Vienna, Austria ( www.viewar.com )
Analysis by Christian Titze
Why Cool: ViewAR's coolness revolves around its ability to apply an array of digital technologies — 3D design, AR, virtual reality and mobile technologies — to help companies showcase their products and designs in an environment that increases engagement and decision making among their customers. Besides accelerating customer buying decisions and driving sales, such technology opens a path for additional benefits such as the reduction of product returns or an enhanced brand awareness. For a company in the consumer electronics industry, this enhanced customer engagement created an efficiency increase in double-digit numbers.
ViewAR applies advanced 3D design for creating mobile, custom business solutions that are cost- and time-efficient. The system distributes 3D content visualization as a core capability for designing specific apps for specific business objectives, thus driving deeper customer engagement, delivering faster purchase decisions and increasing productivity. ViewAR consists of several components. It serves as a platform (e.g., framework of functional components), an agency, a system integrator (e.g., front- and back-end integration) and an SDK. With this emerging technology and applied use cases, ViewAR won the "best AR app" award last year at the Augmented World Expo 2016 in Silicon Valley.
ViewAR has its roots in database systems and real-time visualization. Its founders first came across AR in 2010, realizing its enormous potential in various practical use cases. The ViewAR platform was born, combining front-end features of 3D design and AR experience with back-end infrastructure addressing use cases in industries such as interior design, furniture retail, or architecture and construction.
Having leveraged its core technology platform in initial use cases, ViewAR is now expanding into other use cases and industries including IoT service maintenance in industrial plants, AR-assisted remote services in the building industry and logistics/cargo management for airfreight optimization.
Challenges: Established in 2010, ViewAR is a very small startup of 15 people who have developed 30 customized apps (as of December 2016), predominantly targeting the European market. The company's conversion to a more global player will take time, and it will face hurdles. One challenge will be to find the right talent to support its growth strategy of doubling the staff this year; another will be finding the right partners for scalability. To serve growing client interest, preferred partners will have to act as development and system integrators while also ensuring the quality of services. Finally, the branding of distinctive features will become essential to surviving the ever-expanding market of AR, virtual reality and wearable technology.
Who Should Care: Supply chain leaders of companies looking for a new way to engage and communicate internally or with customers in the real world should be interested in ViewAR. Its system can help companies seeking to drive faster business decisions, create additional mobile sales channels, reduce marketing costs or simply enhance brand awareness. For some, just having their company associated with cool new technology — be it in marketing or industrial and service use cases — will be a big draw.
|Digitalization||The use of digital technologies to change a business model and provide new revenue and value-producing opportunities; it is the process of moving to a digital business.|
|Digitization||The process of changing from analog to digital form.|
|Digital Business||The creation of new business designs by blurring the digital and physical worlds.|
|Supply Chain Digitalization||The use of digital technologies to build supply chain models and processes to support the digital business.|
1 M. Grassi. "Controversial Farmer's Business Network Procurement Program Rebranding as 'FBN Direct.'" CropLife. 14 December 2016.