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Tortoise, not the hare: Digital transformation of supply chain business processes
Business Horizons (xxxx) xxx, xxx
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Tortoise, not the hare: Digital transformation of supply chain business processes Janet L. Hartley*, William J. Sawaya Bowling Green State University, Bowling Green, OH 43403, U.S.A.
KEYWORDS Supply chain technology; Blockchain; Enterprise resource planning; Robotic process automation; Machine learning; Digital transformation
Abstract With the rapid development of digital technologies, many supply chain professionals are wondering how to move forward. Three technologies are poised to change supply chain business processes: robotic process automation (RPA), artificial intelligence (AI)/machine learning (ML) and blockchain. Based on interviews with supply chain professionals in 14 large, mature manufacturing and service organizations, we outline the promise of each technology and forecast their broad-scale adoption potential. Organizations should take the following measures to ensure their readiness to adopt and effectively use one or more of these technologies: (1) identify a supply chain technology visionary who can lead through the maze of technologies and the changing digital landscape, (2) develop a digital technology roadmap for their supply chain processes, and (3) update foundational information systems. ª 2019 Kelley School of Business, Indiana University. Published by Elsevier Inc. All rights reserved.
1. The uncertain future of supply chain Imagine a future in which accurate information is instantly available up and down the entire supply chain, and data-driven decisions are enabled by artificial intelligence. Digital technologies may quickly make this future a reality. In this article, we describe how three of these technologies, robotic process automation (RPA), artificial * Corresponding author E-mail addresses: [email protected] [email protected] (W.J. Sawaya)
(J.L.
Hartley),
intelligence (AI)dspecifically, machine learning (ML)dand blockchain can improve supply chain business processes. Then, we explore if and how 14 large, mature service and manufacturing companies may adopt and implement these digital technologies in supply chain processes. Based on the experiences of these companies, we provide practical advice on how to prepare for supply chain’s digital transformation. Table 1 provides a brief summary of the digital transformation progress of the companies in our study, whose names are disguised. At the time of the interviews in 2018, all the companies in our
https://doi.org/10.1016/j.bushor.2019.07.006 0007-6813/ª 2019 Kelley School of Business, Indiana University. Published by Elsevier Inc. All rights reserved.
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Medium
Progress in digital transformation Companya
RPA
AI/ML
Packaging
Pilot
Electric CPG1
Digital roadmap
Cloud-based ERP
Cloud-based e-Procurement
Pilot
Yes
Yes
Yes
Yes
Yes
Implementing
Yes
Studying
Yes
Partial
In 5 years
Developing
Evaluating providers
No
Yes
Developing
Yes
Evaluating providers
Yes
No
Evaluating providers
Pilot
Health Equipment1
Yes
Blockchain
Yes
Building
Studying
Energy Low
Degree of Transformation
Table 1.
ProServices CPG2 Auto1
In 5 years
Very low
Transport
Implementing
Yes
No
Implementing
Studying
Yes
In 5 years
In 3 years
Studying
Developing
No
Studying
No
Partial
Evaluating providers
Equipment2
No
No
Yes
CPG3
Provides Input
No
Provides input
No
Auto2
In 5 years
In 5 years
a
The annual sales of all companies exceeded $1 billion. Health, ProServices, and Transport are service companies and the other companies are manufacturers.
J.L. Hartley, W.J. Sawaya
Digital transformation of supply chain business processes study were early in the digital transformation process.
2. Quick wins: Robotic process automation RPA is often a company’s first step in digital transformation. A 2018 study found that over 60% of supply chain professionals surveyed were exploring or using RPA to automate supply chain business processes (APQC, 2018). RPA is software that performs routine process tasks such as an automated email response based on simple rules (Boulton, 2018). RPA tasks include data entry, simple calculations, reading and extracting data from Enterprise Resource Planning (ERP) systems, and form completion (Lowes & Cannata, 2017). With RPA, software mimics what humans would do when entering or manipulating data using a computer. RPA can be used with structured data spreadsheets and databases or unstructured data in emails, webpages, social media, or other types of documents (Ernst & Young, 2017). Supply chains have many repetitive tasks that can be automated with RPA in sourcing, operations, and logistics. Unilever, which received the top spot in Gartner’s 2018 Supply Chain Top 25, is using RPA in its order-to-cash process (Supply Chain Quarterly Staff, 2018). In procure to pay processes, RPA can create and send requests for quotations; compare supplier bid responses to predetermined criteria; create purchase orders; match purchase orders, invoices, and receiving documents; and process payments (Monahan, 2017). Other sourcing tasks ripe for automation include setting up suppliers in ordering systems, maintaining purchasing catalogs, reading supplier emails, and sharing documents with suppliers and contract manufacturers. RPA is also used in logistics; information from documents can be entered into transportation management systems (TMS) and shipments can be scheduled and tracked using RPA, increasing efficiency and customer satisfaction (Gould, 2018). In our study, we found that one companydwhich we call Packagingduses RPA for consolidating and entering orders from many customers and plans to expand it to other areas, including: compliance with spending limits, reviewing and responding to supplier emails, creating and updating purchase orders (POs), and entering data into spreadsheets automatically. Given that some of Packaging’s suppliers and customers do not have EDI capabilities, RPA is especially useful. After a successful RPA pilot, another company in our study, CPG1, created an RPA center of excellence to identify
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opportunities and implement RPA in demand and supply planning, procurement, and contracting manufacturing. Companies start their digital transformation with RPA for several reasons. First, it is relatively easy to deploy RPA using software bots from some of the leading providers such as Automation Anywhere, UiPath, and Blue Prism. With limited training and without the need for coding expertise, tech-savvy supply chain professionals can easily set up their own RPA applications without support from their corporate IT teams (Spend Matters, 2018). However, it is still important to involve IT in the decisions to adopt RPA so that systems are compatible and IT expertise can be leveraged effectively. Second, RPA can be applied to a single, manual pain point in a process so it is faster to implement than redesigning an entire end-to-end process. Firms must make sure that the process is working well before automating it and understand how automating one part of a process might affect its overall performance. Third, once developed, it is easy to add or remove capacity and to scale up or down bots depending upon business needs (van As, 2018). Finally, it is easy to make the case for RPA based on ROI (van As, 2018). Investment in RPA is relatively low. The manager at CPG1 expects RPA to result in double-digit gains in efficiency, and will be redeploying employees displaced by RPA to other activities. A survey by Deloitte showed that payback for RPA is typically less than 12 months (Wright, Witherick, & Gordeeva, 2018). Employees can be redeployed to manage exceptions, solve problems, and take on more strategic activities (Lowes & Cannata, 2017; Monahan, 2017; van As, 2018), as is the case at CPG1. Additional benefits include speed and fewer errors, which improve overall customer service.
3. Artificial intelligence/Machine learning AI, a broad field with roots traced back to the 1940s, focuses on designing and building intelligence machines capable of rational action (Russell & Norvig, 2010). AI has been defined in many ways but, for the purpose of this research, we adopt the definition presented by Kaplan and Haenlein (2019, p. 17): “A system’s ability to interpret external data correctly, to learn from such data, and to use those learnings to achieve specific goals and tasks through flexible adaptation.” AI includes the ability to process human language, machine vision, and machine learning (Jarrahi, 2018). There
4 are many existing AI applications in supply chain and a myriad of possibilities. Applications already in use include autonomous delivery vehicles such as those rolled out in Houston by Kroger and Nuro (Wiles, 2019), robots that scan store shelves and place orders to replenish inventory, and augmented reality to improve loading of trucks. As our research is on supply chain business processes, we examined applications of ML, a subset of AI that uses algorithms to analyze patterns in data to develop models without being explicitly programed (Theobald, 2017; Kaplan & Haenlein, 2019). In our study, although some of the participants used the term artificial intelligence, it appeared that most were focused on ML. The availability of input data is critical for ML, as the models are trained and then adapt and improve as they are exposed to new data. As with RPA, data can be structured and unstructured from a variety of different sources. The explosion of data availabilitydincluding those gathered by sensors as part of the Internet of Thingsdcreates opportunities for organizations to improve their supply chain decisions using ML. Supply chain applications of ML include: demand planning and forecasting, scheduling of warehouse pick processes, determining equipment maintenance schedules, analyzing weather data to improve transportation management, rerouting vehicles to avoid congestion, and risk assessment (Gesing, Peterson, & Michelsen, 2018; Banker, 2019). Working with IBM, DHL developed a number of supply chain applications for ML. DHL has long used ML to optimize routing for its delivery vehicles but recently expanded the data used by ML to include social media and satellite images (Gesing et al., 2018). It also developed a model to predict time delays in air freight lanes using 58 different parameters and the expected reasons for the delay (Gesing et al., 2018). This model helps shippers determine when to ship as well as which airline to use. Companies such as Resilinc use ML to monitor data from social media, in addition to news and weather around the world, to identify potential supply chain disruptions for their customers (Behrens, 2019). Stitch Fix, an online fashion personal styling service created a new retail business model using ML. Stitch Fix uses ML to design new products, select styles based on the customer’s style preferencesdincluding what items they keep and returndassign orders to fulfillment centers, and replenish inventory (Marr, 2018). Our study suggests that many companies see value in using ML in their supply chains but only a
J.L. Hartley, W.J. Sawaya few are currently using it. CPG1 expects even greater improvements with ML and other types of AI than it is seeing with RPA, but has not yet adopted ML. The manager at CPG3 envisions a future in which demand planning will be done using ML and planners will deal only with exceptions. Three companies in our study are currently using ML in some applications: Packaging is testing ML for data mining supplier emails to reduce costs and is exploring its use for data analytics in forecasting and demand planning. Health currently uses ML for some automated inventory replenishment. Electric has the most advanced application in which ML is integrated into its newly implemented cognitive sourcing platform. It adopted software that includes supply market intelligence, along with adaptive learning, to provide sourcing recommendations and is exploring additional ML sourcing applications. The supply manager commented: “We started out with a basic need because we could not do spend management and now we can do things like cognitive sourcing.” Electric’s approach of depending upon software providers to integrate ML into their products is likely a common path companies will use when adopting ML. Unless they are in an IT sector, many companies do not have the specialized knowledge and expertise to develop and deploy ML in supply chain processes on their own. Large technology providers such as IBM, SAP, Oracle, and JDAdas well as a number of more specialized software providersdare rushing to add ML to their supply chain software applications (Banker, 2019). As the field continues to evolve, software companies will likely develop products to simplify the deployment of ML, such as Microsoft’s Azure Machine Learning Studio in which coding is not required. Thus, ML is likely to be a standard part of supply chain planning and execution systems in the future.
4. No rush to use blockchain Blockchain, the digital distributed ledger technology that enables cryptocurrencies, received a lot of attention for its potential to transform supply chains by increasing trust and reducing fraud (Cottrill, 2018; Muma, 2018; Partida, 2018). Typically, supply chain blockchain platforms are
Digital transformation of supply chain business processes private and can only be accessed by authorized users who are granted permission to view or add specific data (Gupta, 2017; Cottrill, 2018). Data can be added to the blockchain manually or through RPA by scraping data from an ERP system. After data are recorded to the blockchain and verified, they cannot be changed or removed (Gupta, 2017). Benefits of blockchain include realtime visibility of transactions throughout the supply chain and a reduced chance of data manipulation and fraud (Cottrill, 2018; Muma, 2018; Partida, 2018). In addition, routine transactions can be automated with blockchain using smart contracts (Min, 2019). Large technology companies (e.g., IBM, SAP, Oracle, Microsoft) as well as many technology startups have developed blockchain applications for supply chain management. Early blockchain applications addressed issues with safety, sustainability, and compliance through increased supply chain visibility. One of the most widely publicized supply chain applications, IBM’s Food Trust platform, traces the flow of food from farmers to retailers and has been adopted by Walmart and Carrefour to speed up their response to food recalls (Stanley, 2018). Tracking diamonds from mines to the retail stores is another highprofile blockchain application. Blockchain platforms developed by De Beers and Everledger allow customers to confirm diamonds are ethically sourced (Paton, 2018). Bumble Bee seafood company is working with SAP to use blockchain to trace fair-trade tuna from where it is caught in Indonesia until it is in stores (Hackett, 2019). The aerospace industry is also testing blockchain as a way to prevent counterfeit parts from entering supply chains (Bryan, 2018) and may be adopted to address counterfeiting in other complex supply chains, such as automotive. Blockchain is also applied to areas in which document flows create bottlenecks and inefficiencies. With global shipping, many types of documents must be shared with different parties, including transportation providers, ports, terminals, and government officials. TradeLens is a joint venture between Maersk and IBM that is being used to speed up the document sharing and the approval process with global shipping. None of the companies in our study have specific plans to adopt blockchain in the foreseeable future. Only Health, which likes to be on the leading edge, would like to do a pilot of blockchain but did not envision doing that for at least another year. It is waiting to see how blockchain might fit its needs. Most, like Transport, might consider blockchain down the road but are trying to
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understand how it might be used and are waiting to see how others adopt the technology. Managers at Auto1 met with a blockchain service provider but decided to wait and see what other companies were doing and where their industry goes with respect to blockchain before adopting. CPG1 is trying to learn about blockchain but has not seen any applications that are scalable; although the manager sees potential benefits from using blockchain for traceability, it is not a major concern for the company. The manager at Energy commented: “I can see blockchain being a huge thingdbut it is so far out.” Other managers expressed skepticism about blockchain. The manager at Equipment1 said that “I am not convinced that blockchain is the next big thing” because other technologies can be used. The manager at Equipment2 was also skeptical and stated that encrypted private networks can be used to deliver the same functionality. When referring to blockchain, the manager at Electric commented: “I am not sure how it is going to help us. We have taken a shot at trying to understand it.” It appears that, currently, the perceived value of blockchain for supply chain is limited to specific cases that have a high need for increased supply chain visibility or that have complex document flows among many different types of supply chain members.
5. The path forward Although the timing of adoption is different, digital technologies such as RPA, ML, and blockchain will transform supply chain processes. Supply chain professionals must begin preparing now to ensure that their organizations are ready to effectively adopt and employ digital technologies. There are some critical decisions organizations can make now to position themselves to exploit these and other new technologies successfully. Organizations planning for successful adoption of one or more of these technologies must: (1) identify a supply chain technology visionary who can guide the organization through the maze of digital technologies, (2) develop a digital technology roadmap for supply chain processes, and (3) update foundational information systems.
5.1. Identify a supply chain technology visionary As organizations move forward with the digital transformation of supply chain processes, they
6 face hurdles that occur when adopting new information technologies (e.g., user resistance) as well as new challenges from the rapid pace of digital technology changes. Digital transformations must overcome challenges common to organizational change, including lack of investment, lack of skills to evaluate and implement new technologies, and resistance to change (Polites & Karahanna, 2012). To lead the digital transition process and overcome these challenges, it is important to identify a visionary who understands the technologies, can intermediate between supply chain and IT, and possesses excellent change management skills. Packaging, Electric, and Health each have such a visionary within their supply management organizations who is helping them to be on the forefront among the companies in our study. At CPG1, the Chief Information Officer (CIO) is a strong advocate for supply chain technologies. These supply chain technology visionaries understand supply chain practices, are learning about digital technology capabilities and trajectories, and imagine the possibilities for transforming their supply chain processes. Educating others about the possibilities for digital transformation is a key role of the visionary. Thus, they must be able to help those within the supply chain function understand how and why adopting the technology is important. Equally important is the ability to effectively communicate with the company’s executive team members, who are often unfamiliar with digital technologies and unsure of applications in the supply chain. Another role of this visionary is to garner support for technology investments in order to improve supply chain processes. Typically, CIOs control the budget for information systems for the entire organization and leaders from different functions complete to win approval for information system upgrades and new investments. One of the reasons companies are adopting RPA is its low investment cost. Unfortunately, it is often difficult to make a business case for upgrading supply chain systems based on cost savings alone because supply chain improvements often lead to soft savings such as completing tasks faster and improved quality in the business processes, which allow employees to be redeployed to other tasks. That is why it is important to focus on how investment in digital technologies can create new capabilities. Digital technologies provide automation and data, enabling supply management professionals to transition from doing transactional activities to becoming strategic category managers who increase business value.
J.L. Hartley, W.J. Sawaya
5.2. Develop a digital roadmap for supply chain processes Another important role of the visionary is to guide development of a digital roadmap for supply chain processes. To create a competitive advantage using digital technologies, business strategy and IT strategy must be integrated (Bharadwaj, El Sawy, Pavlou, & Venkatraman, 2013). Most large companies have a supply chain strategic plan and, as we found from our interviews, companies that are leading in digital technology adoption have developed a roadmap for digital technologies in their supply chains. Companies can develop the roadmap internally if they have the expertise. Participating in professional organizations, attending conferences, benchmarking, and talking with service providers are relatively low-cost ways to learn more about digital technologies. Because of the complexity and rapid rate of change, those without internal expertise can turn to consultants to build a digital technology roadmap. In our study, one companydElectricdstood out with its process to develop its supply chain digital roadmap internally. Electric is also integrating ML and natural language processing into its products. It has a centralized group that is responsible for managing the systems, tools, and processes for its global supply management function. Its mission is to deliver adaptable, innovative, and scalable supply chain services that optimize customer value. The team categorizes its technical capabilities as foundational (e.g., its ERP systems) and advanced (e.g., tools to assess supply chain resiliency and gain visibility deeper into its supply network). In order to develop the roadmap, the team worked with internal business partners to assess the current state of its processes, future business needs, and the level of maturity of its supply chain technologies. This team also benchmarked supply chain technologies used by other companies. Using this information, the team developed a technology roadmap and maturity matrix that showed which of its existing technologies it should upgrade, what new technologies were needed, and where it needed to find new technology partners. Electric works with its internal business partners to update its supply chain technology plan annually. Three of the firms we interviewed used consultants to develop their supply chain digital technology roadmaps. CPG1 has had a 3-year rolling supply chain technology plan for 7 years but it did not include
Digital transformation of supply chain business processes emerging digital technologies. Within the last 3 months, CPG1 worked with consultants to integrate digital technologies into its supply chain technology plan. Within the last year, ProServices used a consulting group’s standardized approach to develop a digital technology roadmap for its supply chain that provides input for the company’s overall IT strategic plan, which is the responsibility of the Chief Technology Officer. CPG2 also worked with consultants to develop its supply chain technology plan. The plan focuses on the capabilities needed in transaction processing, supply and demand planning, forecasting, and risk management. Each business process owner at CPG2 is responsible for developing and maintaining 3-year plans that incorporate IT tools. One risk with digital technology roadmaps is focusing too much on the technology rather than how to best achieve supply chain goals. This was a lesson that Health learned the hard way with a past technology adoption. Health was an early adopter of IT; historically, it selected the technology first and then adapted the technology to fit its processes. With digital technologies, Health went from being an early adopter to being a fast follower. It is currently reviewing its supply chain processes to see how they can be improved before developing its digital technology roadmap. Auto1 is taking a similar approach by first identifying what data it needs from suppliers to make better decisions before determining which technology it should use to effectively gather, analyze, and share the data within the company and across the supply chain.
5.3. Update foundational information systems Two information systems, ERP and e-procurement, are key sources of supply chain data essential to effective supply chain decision making. Many companies are still struggling with outdated or disparate ERP and/or e-procurement systems. Difficulties in retrieving and sharing information from these systems lead to inefficiencies, errors, and suboptimal decisions. Thus, it is important to make sure these systems are updated and used effectively. In addition, software providers are integrating RPA and ML into their ERP and e-procurement systems for tasks such as demand and supply planning, risk management, and cognitive
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sourcing (Korolov, 2017; Brooks, 2018). The companies in our study are expanding the use of, adding new capabilities to, or updating their existing information systems. About 7 years ago, Equipment2 implemented a single, company-wide ERP system that drove common processes and dramatically improved efficiency. Now, it is continuing to drive manual processes into its ERP system, replacing spreadsheets. At Packaging, even years after its ERP implementation, some supply chain planners still used Excel spreadsheets for planning; the company is now retraining employees to do planning in its ERP system to standardize its planning processes. For these companies, increasing use of their ERP system was more strategic than automating outdated inefficient processes with RPA. For years, large organizations have used onpremise ERP systems to share data and standardize business processes across internal business functions. In the last few years, companies have been moving from on-premise systems to cloud-based systems in which ERP is software as a service (SaaS). Cloud-based ERP systems offer several benefits over on-premise systems. These include lower implementation costs, ease of upgrades, easier remote access for employees working outside of the office, centralized security and controls, and better business intelligence and analytics (Warnock, 2018). However, in our study, some managers raised concerns about data security with cloud-based systems. Cloud-based ERP systems can help address a common problem of disparate ERP systems within organizations. This problem can happen in decentralized organizations or those that have grown through mergers and acquisitions. Transport, which completed a merger over 5 years ago, still has several different ERP systems in different parts of its organization. It has some cloud-based applications but, ideally, would like a totally cloudbased ERP system for its entire organization. CPG2 has different ERP systems in different countries and some regions are using very old systems. Its goal is to move to common cloud-based ERP and planning processes. By updating systems, CPG2 is “building a strong foundation for the futuredfor the future of AI, digital, and blockchain.” Health was in contract negotiations for a new updated cloud-based ERP system that could “leverage us better for the future.” Procurement has lagged behind other business functions, especially customer facing ones, in the adoption of digital technology (Burnson, 2018). In our study, eight of the companies had either recently implemented or were in the process of
8 implementing e-procurements systems. System features vary but typically e-procurement systems automate end-to-end procurement workflow processes, including payment (Partida, 2015). The systems are sources of spend data that can be analyzed to identify more effective sourcing strategies. Often e-procurement systems include catalogs that allow internal customers to make routine online purchases from approved suppliers using negotiated pricing creating an Amazon-like purchasing experience. In our study, three organizations implemented full procure (source) to pay platforms: ProServices executed a new cloud-based procure to pay system to automate the entire process and eliminate mundane jobs in procurement. Transport issued requests for proposals (RFP) for a new source to pay platform to replace its old cumbersome system that was not intuitive. The new system provides increased spend visibility and reports, the tools needed to be more efficient, and simplify the process by having a single procurement system. Selecting and implementing this system is Transport’s focus for the next two years. Health is currently implementing two new cloud-based e-procurement systems, one for products and the other for services.
6. A slow and steady transformation For the participants of our study, a complete digital transformation of supply chain business processes is likely years away. The organizational change needed to understand the opportunities created through digital technologies and overcome resistance resembles a marathon more than a sprint. However, even in a marathon, it is critical to start down the correct path. Guidancedeven in early stages when assessing digital technologiesdis critical. Every organization needs a supply chain technology visionary to help plot its course and remove barriers to digital transformation. Furthermore, it is crucial that all supply chain executives educate themselves and ensure their organizations have a digital roadmap for the supply chain. When developing the roadmap, rather than starting with the technologies, identify the critical supply chain business processes that are bottlenecks or places where information visibility is lacking that makes it difficult to make good
J.L. Hartley, W.J. Sawaya decisions. Then, consider which digital technologies will best address those problems or create new opportunities. The organizations in our study are focused on updating and fully deploying mature information technologies, including ERP and e-procurement using cloud-based solutions. Updated foundational technologies are a prerequisite to adopting digital technologies such as RPA, ML, and blockchain. Employees must use existing information systems effectively before automating manual processes with RPA. Data integrity and quality are required to get the most out of advanced tools such as ML or before putting data into a blockchain. Thus, it is important to invest in and quickly implement foundational ERP changes, if required, prior to implementing technologies that will use ERP data. Additional research may help organizations move beyond piloting into adoption. Some questions that deserve exploration include: What are key success factors, and do these differ by technology? Which supply business processes stand to benefit the most from which digital technologies and why? How can digital technologies enable new capabilities and lead to a truly integrated supply chain? Finally, ethical issues with the adoption of digital technologies in the supply chain such as potential job loss need to be examined (Wright & Schultz, 2018).
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future where you can “get anything you want”. Supply Chain Management Review, 21(5), 66e67. Muma, S. (2018, December 18). Are you fit for Blockchain. Supply Chain Management Review. Available at: https:// www.scmr.com/article/are_you_fit_for_blockchain Partida, B. (2015). The benefits of modernizing procure-to-pay. Supply Chain Management Review, 19(5), 79e81. Partida, B. (2018). Blockchain’s great potential: Blockchain’s potential is immense, but most organizations have not yet made the investment. Supply Chain Management Review, 22(1), 51e53. Paton, E. (2018, November 30). Will blockchain be a boon to the jewelry industry? The New York Times. Available at: https:// www.nytimes.com/2018/11/30/fashion/jewelry-blockchainde-beers.html Polites, G. L., & Karahanna, E. (2012). Shackled to the status quo: The inhibiting effects of incumbent system habit, switching costs, and inertia on new system acceptance. MIS Quarterly, 36(1), 21eA13 Russell, S., & Norvig, P. (2010). Artificial intelligence: A modern approach (3rd ed.). Upper Saddle River, NJ: Prentice Hall. Stanley, A. (2018, October 8). Ready to rumble: IBM launches food trust blockchain for commercial use. Forbes. Available at: https://www.forbes.com/sites/astanley/2018/10/08/ ready-to-rumble-ibm-launches-food-trust-blockchain-forcommercial-use/#173fb79f7439 Supply Chain Quarterly Staff. (2018, Quarter 2). Unilever captures top spot in Gartner “Top 25” ranking for the third straight year. CSCMP’s Supply Chain Quarterly. Available at: https://www.supplychainquarterly.com/news/20180522unilever-captures-top-spot-in-gartner-top-25-ranking-forthird-straight-year/ Theobald, O. (2017). Machine learning for absolute beginners (2nd ed.). Palo Alto, CA: Scatterplot Press. van As, E. (2018, Quarter 2). Robotic process automationeDemystifying its potential in the supply chain. CSCMP’s Supply Chain Quarterly. Available at: https://www. supplychainquarterly.com/news/20180117-robotic-procesautomation-demystifying-its-potential-in-the-supply-chain-/ Warnock, R. (2018, June 14). 4 reasons you should move to a cloud-hosted ERP. CIO. Available at: https://www.cio.com/ article/3281866/4-reasons-you-should-move-to-a-cloud-hosted-erp.html Wiles, R. (2019, March 17). Kroger ends its unmanned-vehicle grocery delivery pilot program in Arizona. USA Today. Available at: https://www.usatoday.com/story/money/ 2019/03/17/kroger-ends-unmanned-vehicle-grocery-deliverypilot-program-arizona/3194604002/ Wright, S. A., & Schultz, A. E. (2018). The rising tide of artificial intelligence and business automation: Developing an ethical framework. Business Horizons, 61(6), 823e832. Wright, D., Witherick, D., & Gordeeva, M. (2018). The robots are ready. Are you? Untapped advantage in your digital workforce. Deloitte. Available at: https://www2.deloitte. com/content/dam/Deloitte/tr/Documents/technology/ deloitte-robots-are-ready.pdf
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Tortoise, not the hare: Digital transformation of supply chain business processes Janet L. Hartley*, William J. Sawaya Bowling Green State University, Bowling Green, OH 43403, U.S.A.
KEYWORDS Supply chain technology; Blockchain; Enterprise resource planning; Robotic process automation; Machine learning; Digital transformation
Abstract With the rapid development of digital technologies, many supply chain professionals are wondering how to move forward. Three technologies are poised to change supply chain business processes: robotic process automation (RPA), artificial intelligence (AI)/machine learning (ML) and blockchain. Based on interviews with supply chain professionals in 14 large, mature manufacturing and service organizations, we outline the promise of each technology and forecast their broad-scale adoption potential. Organizations should take the following measures to ensure their readiness to adopt and effectively use one or more of these technologies: (1) identify a supply chain technology visionary who can lead through the maze of technologies and the changing digital landscape, (2) develop a digital technology roadmap for their supply chain processes, and (3) update foundational information systems. ª 2019 Kelley School of Business, Indiana University. Published by Elsevier Inc. All rights reserved.
1. The uncertain future of supply chain Imagine a future in which accurate information is instantly available up and down the entire supply chain, and data-driven decisions are enabled by artificial intelligence. Digital technologies may quickly make this future a reality. In this article, we describe how three of these technologies, robotic process automation (RPA), artificial * Corresponding author E-mail addresses: [email protected] [email protected] (W.J. Sawaya)
(J.L.
Hartley),
intelligence (AI)dspecifically, machine learning (ML)dand blockchain can improve supply chain business processes. Then, we explore if and how 14 large, mature service and manufacturing companies may adopt and implement these digital technologies in supply chain processes. Based on the experiences of these companies, we provide practical advice on how to prepare for supply chain’s digital transformation. Table 1 provides a brief summary of the digital transformation progress of the companies in our study, whose names are disguised. At the time of the interviews in 2018, all the companies in our
https://doi.org/10.1016/j.bushor.2019.07.006 0007-6813/ª 2019 Kelley School of Business, Indiana University. Published by Elsevier Inc. All rights reserved.
2
Medium
Progress in digital transformation Companya
RPA
AI/ML
Packaging
Pilot
Electric CPG1
Digital roadmap
Cloud-based ERP
Cloud-based e-Procurement
Pilot
Yes
Yes
Yes
Yes
Yes
Implementing
Yes
Studying
Yes
Partial
In 5 years
Developing
Evaluating providers
No
Yes
Developing
Yes
Evaluating providers
Yes
No
Evaluating providers
Pilot
Health Equipment1
Yes
Blockchain
Yes
Building
Studying
Energy Low
Degree of Transformation
Table 1.
ProServices CPG2 Auto1
In 5 years
Very low
Transport
Implementing
Yes
No
Implementing
Studying
Yes
In 5 years
In 3 years
Studying
Developing
No
Studying
No
Partial
Evaluating providers
Equipment2
No
No
Yes
CPG3
Provides Input
No
Provides input
No
Auto2
In 5 years
In 5 years
a
The annual sales of all companies exceeded $1 billion. Health, ProServices, and Transport are service companies and the other companies are manufacturers.
J.L. Hartley, W.J. Sawaya
Digital transformation of supply chain business processes study were early in the digital transformation process.
2. Quick wins: Robotic process automation RPA is often a company’s first step in digital transformation. A 2018 study found that over 60% of supply chain professionals surveyed were exploring or using RPA to automate supply chain business processes (APQC, 2018). RPA is software that performs routine process tasks such as an automated email response based on simple rules (Boulton, 2018). RPA tasks include data entry, simple calculations, reading and extracting data from Enterprise Resource Planning (ERP) systems, and form completion (Lowes & Cannata, 2017). With RPA, software mimics what humans would do when entering or manipulating data using a computer. RPA can be used with structured data spreadsheets and databases or unstructured data in emails, webpages, social media, or other types of documents (Ernst & Young, 2017). Supply chains have many repetitive tasks that can be automated with RPA in sourcing, operations, and logistics. Unilever, which received the top spot in Gartner’s 2018 Supply Chain Top 25, is using RPA in its order-to-cash process (Supply Chain Quarterly Staff, 2018). In procure to pay processes, RPA can create and send requests for quotations; compare supplier bid responses to predetermined criteria; create purchase orders; match purchase orders, invoices, and receiving documents; and process payments (Monahan, 2017). Other sourcing tasks ripe for automation include setting up suppliers in ordering systems, maintaining purchasing catalogs, reading supplier emails, and sharing documents with suppliers and contract manufacturers. RPA is also used in logistics; information from documents can be entered into transportation management systems (TMS) and shipments can be scheduled and tracked using RPA, increasing efficiency and customer satisfaction (Gould, 2018). In our study, we found that one companydwhich we call Packagingduses RPA for consolidating and entering orders from many customers and plans to expand it to other areas, including: compliance with spending limits, reviewing and responding to supplier emails, creating and updating purchase orders (POs), and entering data into spreadsheets automatically. Given that some of Packaging’s suppliers and customers do not have EDI capabilities, RPA is especially useful. After a successful RPA pilot, another company in our study, CPG1, created an RPA center of excellence to identify
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opportunities and implement RPA in demand and supply planning, procurement, and contracting manufacturing. Companies start their digital transformation with RPA for several reasons. First, it is relatively easy to deploy RPA using software bots from some of the leading providers such as Automation Anywhere, UiPath, and Blue Prism. With limited training and without the need for coding expertise, tech-savvy supply chain professionals can easily set up their own RPA applications without support from their corporate IT teams (Spend Matters, 2018). However, it is still important to involve IT in the decisions to adopt RPA so that systems are compatible and IT expertise can be leveraged effectively. Second, RPA can be applied to a single, manual pain point in a process so it is faster to implement than redesigning an entire end-to-end process. Firms must make sure that the process is working well before automating it and understand how automating one part of a process might affect its overall performance. Third, once developed, it is easy to add or remove capacity and to scale up or down bots depending upon business needs (van As, 2018). Finally, it is easy to make the case for RPA based on ROI (van As, 2018). Investment in RPA is relatively low. The manager at CPG1 expects RPA to result in double-digit gains in efficiency, and will be redeploying employees displaced by RPA to other activities. A survey by Deloitte showed that payback for RPA is typically less than 12 months (Wright, Witherick, & Gordeeva, 2018). Employees can be redeployed to manage exceptions, solve problems, and take on more strategic activities (Lowes & Cannata, 2017; Monahan, 2017; van As, 2018), as is the case at CPG1. Additional benefits include speed and fewer errors, which improve overall customer service.
3. Artificial intelligence/Machine learning AI, a broad field with roots traced back to the 1940s, focuses on designing and building intelligence machines capable of rational action (Russell & Norvig, 2010). AI has been defined in many ways but, for the purpose of this research, we adopt the definition presented by Kaplan and Haenlein (2019, p. 17): “A system’s ability to interpret external data correctly, to learn from such data, and to use those learnings to achieve specific goals and tasks through flexible adaptation.” AI includes the ability to process human language, machine vision, and machine learning (Jarrahi, 2018). There
4 are many existing AI applications in supply chain and a myriad of possibilities. Applications already in use include autonomous delivery vehicles such as those rolled out in Houston by Kroger and Nuro (Wiles, 2019), robots that scan store shelves and place orders to replenish inventory, and augmented reality to improve loading of trucks. As our research is on supply chain business processes, we examined applications of ML, a subset of AI that uses algorithms to analyze patterns in data to develop models without being explicitly programed (Theobald, 2017; Kaplan & Haenlein, 2019). In our study, although some of the participants used the term artificial intelligence, it appeared that most were focused on ML. The availability of input data is critical for ML, as the models are trained and then adapt and improve as they are exposed to new data. As with RPA, data can be structured and unstructured from a variety of different sources. The explosion of data availabilitydincluding those gathered by sensors as part of the Internet of Thingsdcreates opportunities for organizations to improve their supply chain decisions using ML. Supply chain applications of ML include: demand planning and forecasting, scheduling of warehouse pick processes, determining equipment maintenance schedules, analyzing weather data to improve transportation management, rerouting vehicles to avoid congestion, and risk assessment (Gesing, Peterson, & Michelsen, 2018; Banker, 2019). Working with IBM, DHL developed a number of supply chain applications for ML. DHL has long used ML to optimize routing for its delivery vehicles but recently expanded the data used by ML to include social media and satellite images (Gesing et al., 2018). It also developed a model to predict time delays in air freight lanes using 58 different parameters and the expected reasons for the delay (Gesing et al., 2018). This model helps shippers determine when to ship as well as which airline to use. Companies such as Resilinc use ML to monitor data from social media, in addition to news and weather around the world, to identify potential supply chain disruptions for their customers (Behrens, 2019). Stitch Fix, an online fashion personal styling service created a new retail business model using ML. Stitch Fix uses ML to design new products, select styles based on the customer’s style preferencesdincluding what items they keep and returndassign orders to fulfillment centers, and replenish inventory (Marr, 2018). Our study suggests that many companies see value in using ML in their supply chains but only a
J.L. Hartley, W.J. Sawaya few are currently using it. CPG1 expects even greater improvements with ML and other types of AI than it is seeing with RPA, but has not yet adopted ML. The manager at CPG3 envisions a future in which demand planning will be done using ML and planners will deal only with exceptions. Three companies in our study are currently using ML in some applications: Packaging is testing ML for data mining supplier emails to reduce costs and is exploring its use for data analytics in forecasting and demand planning. Health currently uses ML for some automated inventory replenishment. Electric has the most advanced application in which ML is integrated into its newly implemented cognitive sourcing platform. It adopted software that includes supply market intelligence, along with adaptive learning, to provide sourcing recommendations and is exploring additional ML sourcing applications. The supply manager commented: “We started out with a basic need because we could not do spend management and now we can do things like cognitive sourcing.” Electric’s approach of depending upon software providers to integrate ML into their products is likely a common path companies will use when adopting ML. Unless they are in an IT sector, many companies do not have the specialized knowledge and expertise to develop and deploy ML in supply chain processes on their own. Large technology providers such as IBM, SAP, Oracle, and JDAdas well as a number of more specialized software providersdare rushing to add ML to their supply chain software applications (Banker, 2019). As the field continues to evolve, software companies will likely develop products to simplify the deployment of ML, such as Microsoft’s Azure Machine Learning Studio in which coding is not required. Thus, ML is likely to be a standard part of supply chain planning and execution systems in the future.
4. No rush to use blockchain Blockchain, the digital distributed ledger technology that enables cryptocurrencies, received a lot of attention for its potential to transform supply chains by increasing trust and reducing fraud (Cottrill, 2018; Muma, 2018; Partida, 2018). Typically, supply chain blockchain platforms are
Digital transformation of supply chain business processes private and can only be accessed by authorized users who are granted permission to view or add specific data (Gupta, 2017; Cottrill, 2018). Data can be added to the blockchain manually or through RPA by scraping data from an ERP system. After data are recorded to the blockchain and verified, they cannot be changed or removed (Gupta, 2017). Benefits of blockchain include realtime visibility of transactions throughout the supply chain and a reduced chance of data manipulation and fraud (Cottrill, 2018; Muma, 2018; Partida, 2018). In addition, routine transactions can be automated with blockchain using smart contracts (Min, 2019). Large technology companies (e.g., IBM, SAP, Oracle, Microsoft) as well as many technology startups have developed blockchain applications for supply chain management. Early blockchain applications addressed issues with safety, sustainability, and compliance through increased supply chain visibility. One of the most widely publicized supply chain applications, IBM’s Food Trust platform, traces the flow of food from farmers to retailers and has been adopted by Walmart and Carrefour to speed up their response to food recalls (Stanley, 2018). Tracking diamonds from mines to the retail stores is another highprofile blockchain application. Blockchain platforms developed by De Beers and Everledger allow customers to confirm diamonds are ethically sourced (Paton, 2018). Bumble Bee seafood company is working with SAP to use blockchain to trace fair-trade tuna from where it is caught in Indonesia until it is in stores (Hackett, 2019). The aerospace industry is also testing blockchain as a way to prevent counterfeit parts from entering supply chains (Bryan, 2018) and may be adopted to address counterfeiting in other complex supply chains, such as automotive. Blockchain is also applied to areas in which document flows create bottlenecks and inefficiencies. With global shipping, many types of documents must be shared with different parties, including transportation providers, ports, terminals, and government officials. TradeLens is a joint venture between Maersk and IBM that is being used to speed up the document sharing and the approval process with global shipping. None of the companies in our study have specific plans to adopt blockchain in the foreseeable future. Only Health, which likes to be on the leading edge, would like to do a pilot of blockchain but did not envision doing that for at least another year. It is waiting to see how blockchain might fit its needs. Most, like Transport, might consider blockchain down the road but are trying to
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understand how it might be used and are waiting to see how others adopt the technology. Managers at Auto1 met with a blockchain service provider but decided to wait and see what other companies were doing and where their industry goes with respect to blockchain before adopting. CPG1 is trying to learn about blockchain but has not seen any applications that are scalable; although the manager sees potential benefits from using blockchain for traceability, it is not a major concern for the company. The manager at Energy commented: “I can see blockchain being a huge thingdbut it is so far out.” Other managers expressed skepticism about blockchain. The manager at Equipment1 said that “I am not convinced that blockchain is the next big thing” because other technologies can be used. The manager at Equipment2 was also skeptical and stated that encrypted private networks can be used to deliver the same functionality. When referring to blockchain, the manager at Electric commented: “I am not sure how it is going to help us. We have taken a shot at trying to understand it.” It appears that, currently, the perceived value of blockchain for supply chain is limited to specific cases that have a high need for increased supply chain visibility or that have complex document flows among many different types of supply chain members.
5. The path forward Although the timing of adoption is different, digital technologies such as RPA, ML, and blockchain will transform supply chain processes. Supply chain professionals must begin preparing now to ensure that their organizations are ready to effectively adopt and employ digital technologies. There are some critical decisions organizations can make now to position themselves to exploit these and other new technologies successfully. Organizations planning for successful adoption of one or more of these technologies must: (1) identify a supply chain technology visionary who can guide the organization through the maze of digital technologies, (2) develop a digital technology roadmap for supply chain processes, and (3) update foundational information systems.
5.1. Identify a supply chain technology visionary As organizations move forward with the digital transformation of supply chain processes, they
6 face hurdles that occur when adopting new information technologies (e.g., user resistance) as well as new challenges from the rapid pace of digital technology changes. Digital transformations must overcome challenges common to organizational change, including lack of investment, lack of skills to evaluate and implement new technologies, and resistance to change (Polites & Karahanna, 2012). To lead the digital transition process and overcome these challenges, it is important to identify a visionary who understands the technologies, can intermediate between supply chain and IT, and possesses excellent change management skills. Packaging, Electric, and Health each have such a visionary within their supply management organizations who is helping them to be on the forefront among the companies in our study. At CPG1, the Chief Information Officer (CIO) is a strong advocate for supply chain technologies. These supply chain technology visionaries understand supply chain practices, are learning about digital technology capabilities and trajectories, and imagine the possibilities for transforming their supply chain processes. Educating others about the possibilities for digital transformation is a key role of the visionary. Thus, they must be able to help those within the supply chain function understand how and why adopting the technology is important. Equally important is the ability to effectively communicate with the company’s executive team members, who are often unfamiliar with digital technologies and unsure of applications in the supply chain. Another role of this visionary is to garner support for technology investments in order to improve supply chain processes. Typically, CIOs control the budget for information systems for the entire organization and leaders from different functions complete to win approval for information system upgrades and new investments. One of the reasons companies are adopting RPA is its low investment cost. Unfortunately, it is often difficult to make a business case for upgrading supply chain systems based on cost savings alone because supply chain improvements often lead to soft savings such as completing tasks faster and improved quality in the business processes, which allow employees to be redeployed to other tasks. That is why it is important to focus on how investment in digital technologies can create new capabilities. Digital technologies provide automation and data, enabling supply management professionals to transition from doing transactional activities to becoming strategic category managers who increase business value.
J.L. Hartley, W.J. Sawaya
5.2. Develop a digital roadmap for supply chain processes Another important role of the visionary is to guide development of a digital roadmap for supply chain processes. To create a competitive advantage using digital technologies, business strategy and IT strategy must be integrated (Bharadwaj, El Sawy, Pavlou, & Venkatraman, 2013). Most large companies have a supply chain strategic plan and, as we found from our interviews, companies that are leading in digital technology adoption have developed a roadmap for digital technologies in their supply chains. Companies can develop the roadmap internally if they have the expertise. Participating in professional organizations, attending conferences, benchmarking, and talking with service providers are relatively low-cost ways to learn more about digital technologies. Because of the complexity and rapid rate of change, those without internal expertise can turn to consultants to build a digital technology roadmap. In our study, one companydElectricdstood out with its process to develop its supply chain digital roadmap internally. Electric is also integrating ML and natural language processing into its products. It has a centralized group that is responsible for managing the systems, tools, and processes for its global supply management function. Its mission is to deliver adaptable, innovative, and scalable supply chain services that optimize customer value. The team categorizes its technical capabilities as foundational (e.g., its ERP systems) and advanced (e.g., tools to assess supply chain resiliency and gain visibility deeper into its supply network). In order to develop the roadmap, the team worked with internal business partners to assess the current state of its processes, future business needs, and the level of maturity of its supply chain technologies. This team also benchmarked supply chain technologies used by other companies. Using this information, the team developed a technology roadmap and maturity matrix that showed which of its existing technologies it should upgrade, what new technologies were needed, and where it needed to find new technology partners. Electric works with its internal business partners to update its supply chain technology plan annually. Three of the firms we interviewed used consultants to develop their supply chain digital technology roadmaps. CPG1 has had a 3-year rolling supply chain technology plan for 7 years but it did not include
Digital transformation of supply chain business processes emerging digital technologies. Within the last 3 months, CPG1 worked with consultants to integrate digital technologies into its supply chain technology plan. Within the last year, ProServices used a consulting group’s standardized approach to develop a digital technology roadmap for its supply chain that provides input for the company’s overall IT strategic plan, which is the responsibility of the Chief Technology Officer. CPG2 also worked with consultants to develop its supply chain technology plan. The plan focuses on the capabilities needed in transaction processing, supply and demand planning, forecasting, and risk management. Each business process owner at CPG2 is responsible for developing and maintaining 3-year plans that incorporate IT tools. One risk with digital technology roadmaps is focusing too much on the technology rather than how to best achieve supply chain goals. This was a lesson that Health learned the hard way with a past technology adoption. Health was an early adopter of IT; historically, it selected the technology first and then adapted the technology to fit its processes. With digital technologies, Health went from being an early adopter to being a fast follower. It is currently reviewing its supply chain processes to see how they can be improved before developing its digital technology roadmap. Auto1 is taking a similar approach by first identifying what data it needs from suppliers to make better decisions before determining which technology it should use to effectively gather, analyze, and share the data within the company and across the supply chain.
5.3. Update foundational information systems Two information systems, ERP and e-procurement, are key sources of supply chain data essential to effective supply chain decision making. Many companies are still struggling with outdated or disparate ERP and/or e-procurement systems. Difficulties in retrieving and sharing information from these systems lead to inefficiencies, errors, and suboptimal decisions. Thus, it is important to make sure these systems are updated and used effectively. In addition, software providers are integrating RPA and ML into their ERP and e-procurement systems for tasks such as demand and supply planning, risk management, and cognitive
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sourcing (Korolov, 2017; Brooks, 2018). The companies in our study are expanding the use of, adding new capabilities to, or updating their existing information systems. About 7 years ago, Equipment2 implemented a single, company-wide ERP system that drove common processes and dramatically improved efficiency. Now, it is continuing to drive manual processes into its ERP system, replacing spreadsheets. At Packaging, even years after its ERP implementation, some supply chain planners still used Excel spreadsheets for planning; the company is now retraining employees to do planning in its ERP system to standardize its planning processes. For these companies, increasing use of their ERP system was more strategic than automating outdated inefficient processes with RPA. For years, large organizations have used onpremise ERP systems to share data and standardize business processes across internal business functions. In the last few years, companies have been moving from on-premise systems to cloud-based systems in which ERP is software as a service (SaaS). Cloud-based ERP systems offer several benefits over on-premise systems. These include lower implementation costs, ease of upgrades, easier remote access for employees working outside of the office, centralized security and controls, and better business intelligence and analytics (Warnock, 2018). However, in our study, some managers raised concerns about data security with cloud-based systems. Cloud-based ERP systems can help address a common problem of disparate ERP systems within organizations. This problem can happen in decentralized organizations or those that have grown through mergers and acquisitions. Transport, which completed a merger over 5 years ago, still has several different ERP systems in different parts of its organization. It has some cloud-based applications but, ideally, would like a totally cloudbased ERP system for its entire organization. CPG2 has different ERP systems in different countries and some regions are using very old systems. Its goal is to move to common cloud-based ERP and planning processes. By updating systems, CPG2 is “building a strong foundation for the futuredfor the future of AI, digital, and blockchain.” Health was in contract negotiations for a new updated cloud-based ERP system that could “leverage us better for the future.” Procurement has lagged behind other business functions, especially customer facing ones, in the adoption of digital technology (Burnson, 2018). In our study, eight of the companies had either recently implemented or were in the process of
8 implementing e-procurements systems. System features vary but typically e-procurement systems automate end-to-end procurement workflow processes, including payment (Partida, 2015). The systems are sources of spend data that can be analyzed to identify more effective sourcing strategies. Often e-procurement systems include catalogs that allow internal customers to make routine online purchases from approved suppliers using negotiated pricing creating an Amazon-like purchasing experience. In our study, three organizations implemented full procure (source) to pay platforms: ProServices executed a new cloud-based procure to pay system to automate the entire process and eliminate mundane jobs in procurement. Transport issued requests for proposals (RFP) for a new source to pay platform to replace its old cumbersome system that was not intuitive. The new system provides increased spend visibility and reports, the tools needed to be more efficient, and simplify the process by having a single procurement system. Selecting and implementing this system is Transport’s focus for the next two years. Health is currently implementing two new cloud-based e-procurement systems, one for products and the other for services.
6. A slow and steady transformation For the participants of our study, a complete digital transformation of supply chain business processes is likely years away. The organizational change needed to understand the opportunities created through digital technologies and overcome resistance resembles a marathon more than a sprint. However, even in a marathon, it is critical to start down the correct path. Guidancedeven in early stages when assessing digital technologiesdis critical. Every organization needs a supply chain technology visionary to help plot its course and remove barriers to digital transformation. Furthermore, it is crucial that all supply chain executives educate themselves and ensure their organizations have a digital roadmap for the supply chain. When developing the roadmap, rather than starting with the technologies, identify the critical supply chain business processes that are bottlenecks or places where information visibility is lacking that makes it difficult to make good
J.L. Hartley, W.J. Sawaya decisions. Then, consider which digital technologies will best address those problems or create new opportunities. The organizations in our study are focused on updating and fully deploying mature information technologies, including ERP and e-procurement using cloud-based solutions. Updated foundational technologies are a prerequisite to adopting digital technologies such as RPA, ML, and blockchain. Employees must use existing information systems effectively before automating manual processes with RPA. Data integrity and quality are required to get the most out of advanced tools such as ML or before putting data into a blockchain. Thus, it is important to invest in and quickly implement foundational ERP changes, if required, prior to implementing technologies that will use ERP data. Additional research may help organizations move beyond piloting into adoption. Some questions that deserve exploration include: What are key success factors, and do these differ by technology? Which supply business processes stand to benefit the most from which digital technologies and why? How can digital technologies enable new capabilities and lead to a truly integrated supply chain? Finally, ethical issues with the adoption of digital technologies in the supply chain such as potential job loss need to be examined (Wright & Schultz, 2018).
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