Aug 02, 2022 | Strategy | Digital Transformation | By Kapil Nagpal, Priyanka Nagpal, and Shubham Dudeja
Introduction
When a company embarks on a digital transformation program, it chooses to focus on one of the three facets at a time.
1. Consumer-oriented
2. Enterprise-focused
3. Shifts in business models
Each type of transformation presents unique opportunities and challenges. In this post, we will see a few examples.
1. Consumer-oriented digital transformation.
Companies can enhance the way consumers interact with their brands using digital enablers such as conversational AI. A great example of leveraging conversational AI for a differentiated user experience is the Mercedes MBUX. With voice commands, the car’s occupants can control the climate, change seat positions, adjust the ambient lighting, and switch driving modes.
To add a personalized touch, MBUX even detects which passenger gave the voice command “Hey Mercedes, I am cold” and adjusts the preferred temperature only to their side of the cabin.
Another example in the retail space is Target offering omnichannel commerce capabilities. Target provides shoppers with the ability to search, browse, and order items through various channels like the mobile app, web, and in-store while offering a consistent brand experience. Shoppers can use the mobile app to browse the available items in the virtual aisles and add the items to the cart to pick up in-store.
Why do companies invest in consumer-oriented digital transformation?
To enable delightful and personalized experiences for their customers, thereby differentiating from the competition.
To encourage repeat purchases by providing a hassle-free search, browse, buy, and product-use experience.
To improve the products, services, and brand experience across all stages of the customer journey by building a data-driven understanding of customer behaviors and leveraging those insights.
What are some typical challenges?
Poorly designed digital transformations can lead to an overly complex and clunky end-user experience. Most customers desire a simple and seamless experience. Who wants to interact with unhelpful self-serve chatbots and automated voice robots?
Digital transformations can be expensive, especially if not planned in incremental phases. Balancing iterative delivery of value to consumers with achieving the end-state vision of the user feature or transformation program is fundamental to successful digital transformation, especially if the program runs over a few years.
Informing the development process with continuous consumer feedback helps increase the probability of consumer uptake post-launch.
It also aids in identifying critical issues early and either finding a resolution or sometimes even credibly pivoting from the original plan while ensuring alignment across stakeholders.
As a starting point, every digital transformation program needs a project plan. But, due to the complex nature of digital transformation, the plan needs to be revised and iterated.
Iterative delivery through data-driven planning generates time and cost savings.
2. Enterprise-focused transformation through digital enablers.
Enterprises can drive cost optimization and efficiency by leveraging digital technologies like Machine Learning and RPA to automate various business functions.
A great example is Zara, where robots in automated factories can perform labor-intensive tasks like cutting patterns, dying fabric, and stitching.
At Zara, a product can go from design to sales-ready in days instead of months.
Why do companies invest in enterprise-focused digital transformation?
1. To drive cost optimization and efficiency.
2. To enable new capabilities and gain a competitive advantage.
3. To unlock business opportunities.
1. To drive cost optimization and efficiency by automating back-office operations and resource-intensive tasks.
2. To enhance customer experience and gain a competitive advantage by providing automation-enabled services and eliminating customer dissatisfaction from manual and slow back-office execution issues.
3. To unlock business opportunities by leveraging data insights and customer patterns.
Unilever achieved 90% time efficiency and saved £1 million by using AI to automate its recruitment processes, leveraging natural language processing to analyze body language, vocabulary, speech patterns, and facial expressions.
The largest e-commerce platform, Alibaba, is known for leveraging natural language processing across the business - in product development, sales, marketing, and support.
Leveraging data, Alibaba can predict customer sales based on past data patterns before the customer has even placed the order, generate product descriptions on the website, and analyze marketing campaigns.
What are some typical challenges?
1. Ineffective organizational structure can be a stumbling block in implementing transformation initiatives. There can often be a lack of buy-in from senior executives and pushback from employees due to changes in reporting lines and roles, absence of training and organizational change management, and sometimes a complete overhaul of the organizational structure.
2. Unstructured data and/or processes are often among the first barriers in the digital enablement journey of large enterprises.
Companies need to bring offline data to an online platform, connect disconnected systems and streamline existing processes, and create a structure to best leverage the power of big data at scale and digital transformation.
In the short term, skipping the digitalization of offline data and streamlining unstructured data can lead to faster implementation. However, in the mid to long term, this artificial growth can not only lead to bugs but also the need to re-build from scratch, thereby leading to wastage of time, budget, and resources.
3. The lack of a well-defined transformation strategy can be a critical stumbling block to achieving success. A thorough transformation strategy ensures strategic alignment of all parties to the long-term and short-term business goals and also boosts employee morale. The lack of a transformation strategy can lead to the following:
Inefficient utilization of resources
Scope creeps
Inability to monitor progress
Misalignment of long-term and short-term goals
Poor budget management
Low adoption post delivery
In the worst-case scenario, without a clearly defined overall transformation strategy, the entire transformation program may come to a standstill.