One of the industry’s great debates (bigger than regular Cap’n Crunch versus Cap’n Crunch with Crunchberries) is “What is Digital Transformation?” Here’s my take:
Digital Transformation is the fundamental reinvention of an organization’s business model by synergizing advanced analytics (composable, reusable analytic modules) with empowered teams to create a customer journey-centric culture that is continuously-learning and adapting to new sources of customer, product and operational value.
To help organizations navigate their Digital Transformation journey, I introduced the Digital Transformation Value Creation Mapping in the blog “It’s Not Digital Transformation; It’s Digital “Business” Transformation! – Part I.” The Digital Transformation Value Creation Mapping provides a framework to help organizations 1) identify, 2) codify and 3)scale new sources of customer, product and operational value within a 4) customer journey-centric continuously-learningand adapting (via advanced analytics and empowered humans) business and operational environment (see Figure 1).
Figure 1: Digital Transformation Value Creation Mapping
The starting point for the Digital Transformation Value Creation Mapping – identifying sources of value creation – requires a thorough and intimate knowledge of what your customers are trying to accomplish with respect to your products and/or services. As part of that effort, organizations must make the upfront investment to identify, validate, value and prioritize the customers’ sources of value as well as the impediments to their value realization. And that detailed, holistic understanding of your customers’ “journey” should start well before they engage with your products and/or services, and ideally extends beyond that engagement as well.
And that’s where the concept of Service Design comes into play.
Service Design, a methodology out of the Design Thinking toolkit, is instrumental in ensuring that companies thoroughly and intimately understand the entirety of the holistic, end-to-end journeys of their different customer segments.
The Interaction Design Foundation defines Service Design as a “process where designers create sustainable solutions and optimal experiences for both customers in unique contexts and any service providers involved. Designers break services into sections and adapt fine-tuned solutions to suit all users’ needs in context—based on actors, location and other factors.[1]”
The Nielsen Norman Group states that a Service Blueprint (similar to a Service Design) is a “diagram that visualizes the relationships between different service components — people, props (physical or digital evidence), and processes — that are directly tied to touchpoints in a specific customer journey.” See Figure 2.
Figure 2: Source: “Service Blueprints: Definition”[2]
Service Design provides that deep understanding of your customers’ value creation and associated impediments that serves as the foundation for any organization’s Digital Transformation. And since Digital Transformation is about the “fundamental reinvention of an organization’s business model”, a key part of that business model reinvention, for many organizations, includes transitioning your customers to more engaging, value-based “Capabilities-as-a-service” (or Xaas) business model.
Xaas refers to the delivery of specific capabilities as a service. For example, many of you use Gmail or Yahoo! for email. You don’t have to download and maintain an application on your laptop to get access to those email services. Instead, you “consume” email capabilities (composing emails, reading and responding to emails, sending group emails, scheduling meetings, managing contacts) “as a service”. The Xaas consumption model has the end user advantage of hiding the underlying technology complexities; the users only care about having access to their desired capabilities freed from worrying about the underlying technologies.
For example, Uber is leveraging their detailed understanding of consumers, drivers and traffic patterns to provide a new “transit-as-a-service” offering. The Transportation Authority of Marin (California) will pay Uber a subscription fee to facilitate requesting, matching and tracking of its high-occupancy vehicle fleet in support of local residents travel needs.
As more organizations rush to Xaas to find new and more predictable revenue streams, the lack of knowledge about how customers are using your products and services is striking. And that’s when the trouble begins.
To be successful with an Xaas business model requires (see Figure 3):
- Superior consumer product usage insights (product usage tendencies, inclinations, affinities, relationships, associations, behaviors, patterns and trends). Xaas providers must be able to quantify and predict where, how and under what conditions the product will be used and the load on that product across various usage scenarios.
- Superior product operational insights (product performance and product operational tendencies, inclinations, affinities, relationships, associations, behaviors, patterns and trends) to provide an “operational experience excellence” by reducing unplanned operational downtime and optimizing product performance across various usage scenarios (which requires use cases such as predictive maintenance, repair optimization, inventory cost reductions, logistics optimization, elimination of obsolete and excessive inventory, consumables inventory optimization, energy efficiencies, asset utilization, technician retention, remaining useful life, predicted salvage value, etc.).
- Superior data and instrumentation strategy to know (and quantify) what data is most important for what use cases and where to place sensors and other instrumentation and data capturing devices to capture that data so as to balance the operational costs associated with False Negatives and False Positives.
Figure 3: Ingredients for a Successful Xaas Business Model
Xaas business model profitability can only be optimized when you tightly integrate and synergize your design, data and analytics strategies.
As organizations transition to an “as-a-service” business models, it requires an entirely new “product management” and “engineering” mindset:
“When you engineer a capability as a product, then it’s the user’s responsibility to figure out how best to use that product. But when your design a capability as a service, then it’s the designers’ and engineers’ responsibility to ensure that the service is capable of being used effectively by the user. This understanding of how users use your capabilities impacts revenue (usage-based revenue model), pricing (to thoroughly understand the value of that capability so as not to over or under price the capability) and SLA support agreements (so as to properly price service agreements based again upon the value of the capability).”
To help organizations to create the data and analytics strategy necessary to support their Xaas business strategy, I created the Data Science Journey Map canvas that identifies the data science (data and analytic) requirements necessary to 1) identify the customer requirements (as identified from the Solution Design) and 2) codify the customer requirements into analytic models (see Figure 4).
Figure 4: Data Science Journey Map Canvas
Figure 4 shows the Data Science Journey Map for a Discrete Manufacturer who is trying to optimize inventory costs and inventory availability. The Data Science Journey Map decomposes each stage of the customer journey into key actions (or decisions), metrics against which progress and success will be measured, the different analytics that we will need to provide to support the journey, and what data might be useful in supporting the analytics.
As organizations pursue Digital Transformation, a key component to that effort is the transition to a customer-centric, value-focused “Capabilities-as-a-service” (Xaas) business model. Analytics is T-H-E most important competency as companies push into those Xaas business models.
Superior insights into consumer product usage patterns coupled with superior insights into product performance patterns enables Xaas providers to determine the optimal operational, pricing and customer service level agreements to ensure a viable and profitable Xaas business model.
And if you haven’t first mastered customer usage and product performance data management and advanced analytics…SURPRISE (and that’s not the good kind of surprise).
[1] “What is Service Design?” https://www.interaction-design.org/literature/topics/service-design
[2] “Service Blueprints: Definition” http://www.nngroup.com/articles/service-blueprints-definition/
Credit: Data Science Central By: Bill Schmarzo
