Web/mobile interactions are necessary but not sufficient by themselves to deliver the gold standard in customer experience. The digital journey must progress beyond the first touchpoint of the consumer to the entire life cycle of experiences. Digital natives have done this successfully in various industries; legacy enterprises are expected to achieve the same.
Customer experience is the new face/promise of brands that sets the winners apart from the losers. Driving higher customer loyalty is the key to generating shareholder value in the digital age.
Successful transformation programmes take a holistic approach – defining the experience, one that puts the consumer at the centre, rejigging the organizational processes to deliver the experience seamlessly, and enabling end-to-end integration for consistently delivering high-quality experiences.
Key Takeaways What must Experience Design incorporate to fuel successful digital transformation initiatives Trends in Customer Experience
Used properly, Analytics is a Source of Competitive Advantage
Digital experience and its promise of personalization can be delivered effectively only when analytics informs the ‘man + machine’ agents to engage with consumers proactively in the digital age.
So far, analytics has been deployed by traditional enterprises to add incremental value, as opposed to the way digital natives have deployed it, which is to truly make it a source of competitive advantage.
There is a wide gap between the promise and reality of analytics. This occurs due to six key reasons, which I outline in the relevant chapter. These must be carefully addressed by enterprises to make analytics a source of competitive advantage for themselves in the digital age.
Key Takeaways Trends in Analytics Analytics: Gap between promise and reality Future of analytics
Delivering the promised customer experience typically requires an end-to-end overhaul of the business processes.
Even today, many traditional enterprises are stuck with a control mindset and have cumbersome processes. This often leads to bureaucracy, slow speed, and thus friction for the customer.
Enterprises need to go beyond incremental approaches to operations and build confidence by embarking on more transformational and end-to-end change programmes. The changes should include data-driven measurement of operations, intelligent automation that goes beyond RPA, and leveraging of AI for self-learning of processes.
Key Takeaways The next wave of Operations Transformation: Data, AI, and Automation
AI powers the forward march of Digital Transformation
AI is becoming mainstream, especially among digital natives. However, it has not yet reached scale in many traditional enterprises as it is embraced mostly as a ‘feature’ and not as an ‘architecture’.
AI has the potential to drive the next frontier of digital transformation, both on customer experience and operations transformation. To make this happen, there are four key considerations, which I have outlined in the chapter on AI.
Key Takeaways How can AI power digital transformation to the next level? AI-enabled Digital Transformation: Execution imperatives
Data is the centrepiece of digital transformation, enabling design, analytics, operations transformation and AI. Without data, digital strategy cannot be executed.
The exponential growth of data in volume and variety, and at unprecedented velocity, is the engine of success for the digital natives. At the same time, it is paralysing many traditional enterprises that have invested millions of dollars in it but have not realized the desired impact from it.
It is imperative that enterprises develop a digital data architecture that is fit-for-purpose and also change their operating processes to harness the power of data in the digital age.
Key Takeaways Changing profile of data in the digital age Pressure points of the data ecosystem Agility: The new mantra for enterprise data management
Blockchain - going beyong the hype to Sustainable Value Creation
As the hype around bitcoin faded away, many read into it the failure of blockchain technology itself. That is untrue. Blockchain is a powerful technology that is just getting off the ground.
Blockchain offers a new infrastructure-related capability that provides transparency, thereby increasing trust in the system. It has the potential to transform the value chain in many industries. A good example of its usefulness is in payments in banks.
Blockchain is currently at a nascent stage, with many POCs being tested across industries. It will require a set of challenges to be resolved (outlined in the chapter on the subject) before it becomes a mainstream technology.
Key Takeaways Blockchain opportunities The blocks to blockchain implementation The two-speed strategy for blockchain implementation
Cloud is increasingly becoming the backbone of the technology stack, knitting the whole digital transformation programme together. Earlier, enterprises looked at cloud as a low-hanging fruit for realizing cost take-out in infrastructure, but now the possibilities with cloud have grown significantly.
Both business units and CIO teams are now looking at cloud for broader purposes than for just making costs variable and infrastructure scalable.
Business leaders are realizing the value of cloud in reimagining CX and achieving reduced time-to-market as they take on new-age competitors. Whereas CIOs are leveraging cloud for managing enterprise data better and scaling up AI across the enterprise.
Key Takeaways Cloud as an accelerator for business transformation Cloud as an enabler for organizational investments Cloud and Data Scaling Enterprise AI
