Success in the fourth industrial revolution requires a process framework to understand and enable human centricity in operations. By Anirban Bhattacharyya, Sonya Banerjee
Manufacturing leaders are embracing Manufacturing 4.0 in order to become more competitive by identifying new business models, improving efficiency, and meeting changing customer requirements. Their focus is faster responsiveness to market dynamics through real-time precision and predictive analytics, higher productivity, and flexibility in production for product customization.
This requires a deeper understanding of customer preferences through increased collaboration across the value chain of suppliers, employees, and customers. Attention is shifting to creating customer experiences that are personalized and customized and that will provide long-term value for an organization. But in order to create this value, manufacturers must become more adaptive and flexible in how they produce what customers want.
According to a survey conducted by Salesforce.com, Inc., 76% of customers think that companies should understand their expectations and needs. To respond more effectively to demand and deliver customized capabilities, more than 40% of manufacturers say that they must reduce product development cycle times, upgrade aging production equipment and technology, reduce cost structures, improve order-to-delivery lead times, and speed up management decision making.
One of the critical underlying factors in adopting M 4.0 is the availability and synthesis of real time data to propel on-time decision making. What happens when an organization has an existing legacy system with complex flows and disparate proprietary tools and applications? It often doesn’t communicate very well. Large cartels of duplicated, unused, non-real time data end up being an inhibitor to operational efficiencies rather than an aid. Data often resides in silos, making it difficult to assess and leverage collective organizational insights that could drive increased operating margins by executing a variety of strategic initiatives.
This is where the adoption of M4.0 helps monetize existing untapped data through shared services models across various units of the organization, and between the organization and its partners. Imagine a self-learning, self-healing automated system that provides on-time visibility to processes with traceability for richer insights. Additionally, this equips the user with tools for on-time decision making to keep operational efficiencies flowing and sustainable. These shared models take away the siloed view to run daily business, with each business unit providing an end-to-end view to the organization.
Design thinking ensures outcomes that envision business value creation and helps develop a strategic roadmap for the future.
Creating a Process Framework
Automation alone, however, won’t ensure maximum efficiencies and create value. What’s needed is a process framework to understand and enable human centricity in operations. Manufacturing organizations must start with a baseline capability model built from process decomposition to assess the current situation, and quickly follow with a design thinking approach to spur innovation.
This cognitive, strategic, and empirically-based way of thinking enables organizations to envision and execute human-centered innovations that help them differentiate and sustain themselves in the marketplace. After all, it’s the human-centric experience that drives customer affinity, positive word of mouth, and sustains business – unlocking tremendous value for any organization.
As shown in the diagram above, this boils down to transforming products, operations, and services with experience.
So, what is design thinking? Simply put, it is the science of defining the art of experience to drive top-line growth. Every problem statement has a persona intent on solving a problem, willing to adapt to needed changes, and impacting the existing business for increased profitability. To bring human centricity to a cyber-physical environment, it’s critical to understand the ergonomics attributed to experiences that add to efficiencies, thus augmenting process innovation with a user-based, experience-led transformation.
Design thinking consists of five distinct steps: empathy mapping, problem definition, ideation and prioritization of scenarios, prototyping, and, lastly, testing. During the execution of one step it is at times common to iteratively return to previous steps for validations. As depicted in the diagram above, design thinking is non-linear in nature.
Every organization has an encompassing portfolio that delivers design-led programs. Two key concepts, Network of Influences (NOI) and Network of Experiences (NOE), are instrumental in operationalizing the framework of design thinking. NOI rallies the right stakeholders to deliver a network of cross-functional experiences. This can only be achieved with current and future state journey maps. On the next page is an example of a Customer Journey Map (CJM), which illustrates the journey of a business process from a less mature state to a more improved version. CJM is a process to design desirable end customer service experiences as well as employee- based interactive process-led experiences that drive efficiencies and enhance safety on the factory floor.
Connected Experience
Industry’s demand to embrace fourth industrial revolution transformation compels organizations to lead programs with precise, predictive, and traceable data mechanics that drive interconnectivity of cyber physical systems in the era of Industrial Internet of Things (IIoT). This connected data experience brings value that delights the organization in the eco-system. Deploying a range of industry-forward technologies like persona-driven overall equipment efficiency models (optimizing availability, performance, and quality) and cognitive robotics must go hand in hand with the business experience vision.
Undoubtedly, key personas and their experiences need attention for this vision to come to fruition. Personas in the production value chain encompassing asset management, operational performance, quality management, data analytics and management, product development, and logistics are critical for creating an impact that is sustainable. Bringing in virtualization (digital twins) along with augmented reality to co-work with robots and machines enables better decision making. This creates an immersive product experience for prospective customer demands. An enabler like design thinking is a perfect fit in this user scenario.
The M4.0 revolution offers new ways to conduct business through consistent value creation. The latest use case for the shift from 4G to 5G network performance in factories has been driving the need for experience as a factor in return on investment, known as Return on Experience (ROE). All in all, as shown in the diagram on page 9, design thinking is enabling certain key processes like interoperability and service orientation, which are main areas of M4.0 transformation.
Epics and Metrics
In the future, experiences that encompass a promise of quality, delivery, and service will be the currency and metric that drive business decisions. The best way to innovate consistently is to place humans at the center, re-imagining experiences that are financially viable and technologically feasible.
Design thinking is becoming the way to deliver innovation. With its intrinsic human-centric framework, it ensures outcomes that envision business value creation and ideates innovation which results in a strategic roadmap. It also introduces co-existing development and operations to prototype and test simultaneously with integrated feedback mechanisms, which allows for continuous improvement.
Design thinking can be an enabler for various situations in an organization. It can be leveraged to reduce ambiguity when leaders are trying to decide on a program. As high-level business process epics (strategic business cases are known as epics) are being defined, one can run design thinking for one or several decomposed process areas under one epic. Design thinking enables business and technical feasibility, interoperability, and overall desirability for any type of business problem. As leaders are initiating design-led transformation, along with data, engineering and strategy, they are managing innovation as a key outcome of organization strategy and roadmap planning. What is most important to kickstart design thinking is cognizance of an existing underlying problem no matter how wide or narrow the focus.
A few scenarios where Design Thinking can be introduced to enable an organization’s 4.0 mission are:
A. Know the epic, no matter how inarticulate:
● Led by process decomposition, this scenario drives data to benchmark, assess maturity, and capably model. It is a precursor to the onset of the design thinking process that innovates contextually with measurable outcomes.
B. Do not know the epic:
● Usually initiated by leadership as a cultural shift in an organization looking to re-imagine and innovate strategic businesses.
● This is where design thinking helps to envision, ideate, and reimagine with viable outcomes.
● When combined with data-centric strategic decomposition, design thinking yields solutions that help businesses leapfrog to sustainable innovations.
C. Single use, one off challenge:
● In cases where there is a definitive challenge with no existing solutions in an ambiguous environment.
● Design thinking helps demystify the layers of ambiguity and suggests precise solutions.
D. Retrofitting an idea:
● An idea or a concept when tabled, no matter how attractive it may sound, needs to be evaluated for plausibility in the context of an organization’s vision and evolving ecosystem.
● Design thinking, being non-linear, can retrofit its tenets of human centeredness to evaluate its existing or future fit in a persona’s journey map
● Taken forward, the progressive process of design thinking can modify or retain an idea and convert it to a low fidelity prototype with agile value execution.
A Cultural Shift Required
Industry leadership realizes that to stay relevant in an eco-system, it is imperative to foresee trends and proactively act upon them. In a dynamic and volatile market, driving innovation cannot be a one-off process. Innovation needs to seep into an organization’s inherent behavior through a cultural shift in the mindset of its employees. This is a key difference between how transformation programs have been run in the past vs. how they are currently run in the fourth revolution era.
Value, when translated in a manufacturing set up, is derived from analytics-enabled insights that deliver an organization’s vision through a set of progressive and cognitive actions. Most organizations are moving from product organizations to solutions portfolios. To embrace servitization, defined as a fully productized and data-driven service offering model, manufacturers need the insights from the field back to the manufacturing floor that precise analysis of data can provide due to smart connectivity.
It is imperative for leadership to create an ongoing pool of consistent metric-based innovation as a way of achieving a competitive edge and devising new revenue streams. Layering servitization on top of productization develops a sustained pool of value creation for a business.
By 2020, according to Gartner, 25% of customer service operations will use virtual customer assistants like chatbots. This is an increase from 2 percent in 2017. More than 40% of all data analytics projects will relate to customer experience by 2020. Two-thirds of all customer experience initiatives will use design thinking by 2022, a jump from 50% in 2017. Interactions will be handled solely by AI in 2021, a 400% increase from 2017.
While most of these statistics pertain to post-sales service engagement, experience is all pervasive. The paradigms of B2B2C experience-centric value measurement exist around customer satisfaction (CSAT) scores; affinity, loyalty and recommendation scores (e.g. net promoter score); customer engagement metrics (strength of positive interactions); customer retention scores; time taken to resolve a post purchase issue (effort score, average time to resolution, first contact resolution); Life Time Value as ROI (LTV); and Measurable Organizational Value (MOV). ROE-driven revenue analysis creates an impactful communication strategy for CxO reporting, as depicted in Figure 5 above.
It’s a foregone conclusion that the ability to create innovative customer experiences is the currency that unlocks sustainable business value. Therefore, it is as critical to measure experience outcomes through a set of value metrics that are contextual to the value unlocked. To measure experience outcomes, design thinking is at the core of the innovation. M