Advanced Practices Council members gained insight into two strategic questions and two technical ones:
How can companies best leverage their distinctive knowhow and software to succeed in the future?
How can companies leverage platforms to succeed in the future?
How can companies benefits from robotic process and cognitive automation to gain the triple win of greater shareholder, customer and employee value?
What approach should companies take to augmented reality?
They also received a technology update from a prominent venture capital executive.
The examples of successful digital start-ups are plentiful. But how can businesses that were not born digital defend against companies like Amazon in the grocery business and Tesla in the auto business? Plastics was the secret to success in the 1960s as heard in the movie "The Graduate." Software is the secret to success in 2018 according to Vijay Gurbaxani, director of the Center for Digital Transformation at the University of California Urvine. Regardless of industry, we are competing on a software playing field where a company's future value is built on software, which can be easily scaled, and distinctive knowhow, which is codified into the software. Take Peloton, a company that builds stationary exercise bikes. It entered a decades-old business. But it transformed that business through software and knowhow by offering cycling classes with live rides streamed directly to your house from its New York City studio. You can choose from thousands of on-demand classes for any level.
In his research sponsored by the Advanced Practices Council, Vijay identified six key dimensions needed for companies to transform themselves for the digital world in order to achieve greater profitability and revenue, new income streams, and operating efficiencies:
Both new and old auto companies are rethinking future transportation. Lyft envisions a world without car ownership. Daimler's Car2Go envisions rentals by the minute with cars picked up where needed and dropped off where they no longer are. Cadillac envisions a subscription service to request a vehicle, schedule delivery, and drive and exchange at any time. Other companies envision autonomous vehicles.
Key elements of strategic vision include:
Senior executives understand digital and how it supports business objectives.
Senior executives have a clearly defined strategic vision mapped to digital needs.
The company is exploring new business models, markets, customers, products, and services.
Codifying distinctive knowhow
Monsanto's codified knowhow enables its self-driving tractors to plant seeds based on algorithms that significantly increase yields.
Key knowhow elements to be codified include:
After years of using a standard digital platform, Delta decided that it could achieve strategic advantage by creating its own unique platform.
Key elements of strategic alignment include:
By thinking innovatively, Edmunds staff has created a text-based platform that enables customers to buy cars by text.
Key elements of a culture of innovation include:
The CEO is an active champion.
Innovators are rewarded.
New ways of thinking are encouraged.
Work is more collaborative.
There is a shift from fixed product cycles to more continuous innovation.
There are more external strategic partnerships.
The company is willing to fund strategic digital initiatives with uncertain returns.
JPMorgan employs 20,000 coders, in many cases replacing lawyers. JPMorgan software achieves in seconds what lawyers previously achieved in 360,000 hours.
Key elements of digital capability include:
Software is seen as a necessary core competence.
Technical talent for innovation is available.
Analytics capability and needed data are available.
Key technology assets needed for the future include:
Emerging technologies such as big data analytics, artificial intelligence and machine learning, internet of things, mobile, augmented and virtual reality, cybersecurity
Technology infrastructure conducive to digital transformation.
PRODUCTS TO PLATFORMS
iPhone's ability to take over the Blackberry market had little to do with the technology of the two devices. In fact, Blackberry offered innovative products that were well engineered. According to Amrit Tiwana at the University of Georgia, iPhone won the competition because of its iOS ecosystem comprised of Apple's 200,000 developers (vs. Blackberry's 8,000). The iOS platform approach succeeded because of three key elements.
1. Trifecta of ubiquity, software, and digitization
Software is becoming ubiquitous in such non-IT products as airlines, mobile phones, and autos. When the three factors converge, business model possibilities emerge that could not have been previously realized.
2. Platform thinking
Ecosystems can form among owners, customers, and app developers in which each party can benefit. Platform owners can scale without ownership; customers can gain due to lower search and transaction costs; and app developers have access to prescreened customers. Most platforms emerge as standalone products (e.g., iOS, Netfliz, Salesforce, Dropbox) and then gradually welcome other parties, thereby gaining network effects.
Unlike products, the revenue model with platforms includes revenue streams vs. lump sum payments and lock-in potential is much greater. Management mindsets must shift to more emergent vs. planned and to orchestration among ecosystem partners vs. command and control.
3. Architecture as DNA
Appropriate architectural choices can determine success or failure. Modular (lego-like) approaches and APIs facilitate mass coordination. Appropriate platform governance is also essential. Decision rights among platform partners is critical, as are control and measurement elements. Pricing should also be carefully worked out. Rather than offer a prescription for architectural and governance elements, Amrit emphasized that the two must be well integrated like gears of an evolutionary motor.
Amrit suggested that we address several questions as we create platforms:
Are there sides you can add to your already-existing business model to gain competitive advantage?
Are there unexploited long-tails in your market (e.g. State Farm signs up high risk drivers on a weekly pricing structure)?
Are there other possibilities in your industry enabled by ubiquity, software, and digitalization?
ROBOTIC PROCESS AND COGNITIVE AUTOMATION
Service automation consists of robotic process automation (RPA), which uses structured data and rules-based processes, and cognitive automation (CA), which uses unstructured data and inference-based processes. It promises to achieve the triple win of shareholder, customer, and employee value. Mary Lacity of the University of Missouri in St. Louis emphasized that rather than resisting service automation, employees in her case studies actually embraced the robots, in many cases giving them names and cartoon bodies. She shared action principles that led to triple wins with RPA:
Projects should be business led and configured, but IT should be an active partner. Business roles include: strategy; tool-selection; feasibility reviews; rethinking needed skill sets, roles and job descriptions; automation configuration and development; and quality assurance. IT roles include: vetting IT tools to comply with IT security, auditability, and change management; access and security rules for robots; infrastructure configuration and scalability; and manage technology changes.
Projects should focus on pain points, "swivel chair" interfaces, short-term processes, and Band-Aids (e.g., connecting legacy ERP systems during transitions).
Redesign work allocation and flows so that remaining tasks not conducted by robots require the judgments that only humans can bring at this point.
Redesign employee evaluation criteria to recognize that employees will probably process fewer tasks per hour due to the greater difficulty of those they process. Consider the output of humans and robots as a team.
Mary shared a different set of action principles that led to triple wins with CA:
Manage as a live learning project that is co-owned by business and innovation group staff.
Start with low ambition because you are dealing with dark data (untapped, unstructured, untagged), insufficient good examples, dirty data (missing, duplicate, incorrect, inconsistent, outdated), and difficult data (natural language text, fuzzy images, unexpected types).
Many companies are successfully using RPA tools, but few are doing more than dabbling with CA. Therefore, Mary's final advice was to begin with RPA before tackling CA applications. And for any service automation program, prioritize the triple win to drive good practices that will "take the robot out of the human."
AUGMENTED REALITY IN THE ENTERPRISE
In 2017 Apple, Microsoft, and Google issued augmented reality (AR) devices. In some cases, the devices were second-generation attempts to overlay virtual objects on real images to provide a mixed reality as an immersive experience. AR combines multiple technologies, including live video, scene recognition, information retrieval, graphics overlay, and image rendering. Unlike virtual reality (VR), which is often used for training, AR is used principally to inject knowledge during a task in the real world, creating instant expertise and super-performance, allowing non-experts to perform difficult tasks. AR is considered by technology forecasters as one of three megatrends that will drive digital business into the next decade (along with artificial intelligence and digital platforms).
Current applications include consumer retail (casual and serious gaming, fun retail, serious purchasing) and business (value chain business uses, mission critical business uses, and transformational business uses).
Christian Wagner of the University of Hong Kong shared current examples of business applications.
Coca Cola uses AR to simulate the customer experience of refrigerators in retail outlets. Caterpillar Equipment guides novices to make quality inspections.
DHL assists pickers in factories find the appropriate parts.
Boeing uses AR for wiring harness assembly, replacing PDFs on laptops with Google Glass, enabling hands-free operation.
Cargo handlers at Singapore's airport identify cargo contents by first reading tags with their Google Glass. They receive loading instructions for cargo and passenger baggage after scan of visual markers (QR codes). AR enables faster cargo handling (reduced from 60 to 45 minutes) and increases handler accuracy, thereby lowering costs.
As a way to predict future uses, Christian explored the job market for AR developers. He concluded that platform/technology developers are hiring significantly (Oculus, Facebook, Microsoft) as are media/game development companies. Few mainstream employers are hiring in this category. He believes that the hiring of deep technical expertise suggests the absence of readily available platforms or end-to-end solutions. In conclusion, Christian thinks that the highly optimistic market projections have not yet materialized. There are fragmented ecosystems with no clear winners. But there are some promising applications along the business value chain and opportunities for transformation.
He suggests that for most CIOs, a 2-3 year wait and see is appropriate. Alternatively, this could the time to invest in proof-of-concept applications along promising value chain opportunities.
Jeff Williams of Interlock Partners summed up his technology forecast:
The enterprise market is being empowered by the convergence of cloud based computing, data mining coupled with artificial intelligence, natural language processing, and machine learning.
Increased data modeling tools and intuitive processes like prescriptive analytics and predictive analytics are key business enablers.
The enterprise is in the early stages of understanding how artificial intelligence, natural language processing, and machine learning will impact business.
Businesses will change because of blockchain (the leading platform for digital assets), consumption based service models, ever-changing security requirements, server less environments, intelligence assistance platforms, integration of micro services into bigger business processes, machine learning, and the Internet of Things.
He suggests keeping an eye on these technologies in 2018 and beyond: augmented reality, virtual reality, 3D printing, drones, and cypto-currencies.