Implementing Digital Transformation: A Collection Of Three Caselets

The last decade has witnessed the integration of AI into regular industry practices across various domains, with organisations leveraging state-of-the-art AI technologies to enhance their businesses. According to Harvard Business Review, “By 2024, 90% of marketers believe that their organisations need to utilise AI to remain competitive, particularly in terms of cost, in the contemporary marketplace.” The three case studies illustrate the adoption of Generative AI at HubSpot, digital transformation at Starbucks, and preparation for digital transformation in a large company in India.

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HubSpot : Exploring Generative AI Opportunities

AI is still 10% and human intelligence is 90%. Much work is required to be done by humans to power the AI system.

Organisations like HubSpot have explored how Generative AI initiatives could impact their sales and marketing. The research highlighted the personalisation of contextual content at the highest level to serve the top of their sales funnel, as well as the development of smart chatbots to drive business growth and customer service. Generative AI has the potential to replace nearly all employees responsible for creating unique and informative content, as it can produce more relevant and personalised content for each prospective customer, requiring only an efficient prompt engineer. However, the situation remains challenging, as the expected level of creativity is still not achievable by AI engines. While AI systems excel in trend prediction, pattern recognition, object detection, and image synthesis, they continue to fall short of human capability when the desired output involves delivering truly innovative content.

Existing marketing analytics and marketing attribution reporting are enhanced through GenAI-powered features, easing tasks for marketing and sales teams.

Generative AI could replace some employees involved in sales processes, such as chat representatives and salespersons. Human-like conversational bots can enhance customer experience, trust, and satisfaction, inviting higher levels of engagement and surpassing the capabilities of pre-programmed, rule-based bots. In the third quarter of 2024, HubSpot integrated Breeze generative AI agents into their marketing and sales platform. Breeze agents can generate marketing content, initiate communication with customers for service, provide sales-related assistance, and continuously monitor connected social media platforms. The GenAI module collects data across the enterprise to offer the sales and marketing team clear insights into customers at an individual level, enabling them to personalise their pitches accordingly.

A GenAI-enabled platform can be a legitimate choice for the entire sales, marketing, and service operation for midsize businesses.

HubSpot’s executive vice president of product, Andy Pitre, said, “While the company is large language model agnostic, for its own features, it ‘leans’ toward OpenAI's ChatGPT. Among the generative AI features that are live now, HubSpot has seen around 25% adoption of one or more of those features. The company views this as strong adoption, given the recency of release... AI enhancements are just going to continue to permeate the product and become a natural way of using it.”

In addition to large enterprises, small- and medium-sized businesses can leverage HubSpot's services integrated with GenAI, offering an array of sales, service, marketing, and content tools to support daily operations.

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Starbucks’ “Digital Flywheel”: Digital Transformation Focused on Improving Customer Experience and Operations

Personalisation through AI can drive strategy, leading to enhanced services and operational efficiency.

In 2017, Starbucks launched its digital transformation initiative, the “Digital Flywheel” strategy. The company continued reinvesting in a tech innovation strategy that fostered growth across its verticals. According to Starbucks’ Chief Strategy Officer, Matt Ryan, “This fundamental modernisation of our technology stack will replace legacy rewards and ordering functionality with a new scalable cloud-based platform for rewards and ordering, improved customer data organisation, and tighter integration with store-based operating systems, including inventory and production management.” The strategy made mobile orders and payment systems more user-friendly, and the organisation enhanced the customer app using AI to personalise offerings and discounts based on customers’ preferences and buying behaviour.

The wealth of collected data can drive high-level strategy on major aspects such as location selection, in-store staffing allocation, and logistics, to name a few. According to Nasdaq, in July 2017, “the company reported that in U.S. company-operated stores, Mobile Payment increased to 30% of transactions, while Mobile Order and Pay increased to 9% of transactions.”

A combination of human excellence and machine intelligence can help develop a robust AI system that enhances customer experience and operations.

The company’s AI platform, Deep Brew, has driven a transformative shift towards achieving operational efficiency and delivering more customer-centric solutions. The ability to offer personalised and efficient services, such as customised product recommendations and optimising the customer journey in both physical and digital outlets, has undoubtedly impacted revenue. A proper blend of technology and human expertise has ensured operational excellence at the highest level. However, the initial integration of AI was not a smooth journey for Starbucks. Developing a machine learning system like Deep Brew is challenging, as it is a cross-functional and complex solution. The entire data pipeline—from data collection to verification, feature extraction, analysis, and process management tools—must be aligned in the proper direction. Cross-team parity is necessary to train the system effectively, and Starbucks has largely achieved this over time.

CTO Deb Hall Lefevre observed, “In many ways, Starbucks is a tech company. We are a company that uses the power of digital to nurture the limitless possibility of human connection anywhere in the world.” In 2020, the CEO articulated the company’s vision: “Over the next 10 years, we want to be as good at AI as the tech giants….” This ambition has been further accelerated by the advent of Generative AI, which has recently dominated the tech hype cycle.

Taking into consideration advancements in the field of AI, Starbucks is re-platforming. In a recent interview, CEO Laxman Narasimhan discussed how they are accelerating digital innovation to enhance their digital capabilities. Organisational agility in embracing innovation is key to success. He stated, “Starbucks has had a long track record of industry-leading digital innovation. As we approach the fundamental platform transformation underway with AI, we intend to invest to lead in this area, using a foundational Deep Brew capability as the launching pad. Our focus in these investments will remain on improving the partner experience while elevating the customer experience and delivering productivity gains.”

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A Large Steel Company in India: Preparing for the Digital Journey

While digital transformation has been making inroads into Indian businesses, a large steel company in India focused on Industry 4.0 adoption as a business goal in 2016. In 2017, the company set its sights on becoming a leader in digital steel manufacturing by 2025. This goal was championed by the senior leadership to remain competitive in global steel markets, where competitors had similar ambitions.

The path forward was challenging, as the ecosystem consisted of employees with limited digital awareness. To spearhead this initiative, a new Chief Information Officer (CIO) was brought on board.

Reverse mentoring: Young digital natives mentor senior leadership to build digital awareness.

The company began its digital journey by creating a reverse mentoring programme, in which young, promising individuals were selected to mentor the senior leadership. These mentors covered fundamental digital concepts such as search engine optimisation, the potential of analytics, and augmented reality/virtual reality (AR/VR) applications. As the senior leadership experienced many "wow" learning moments, appreciation for the programme grew, leading to more young mentors being inducted the following year and paired with the next level of leadership.

The development of digital capabilities at all levels helps gain momentum across the enterprise.

With awareness building underway, the company implemented two programmes to develop digital competencies. The first included explainer videos that conveyed digital concepts in an easy and conversational style. All employees were required to complete this programme, which not only introduced them to the potential of digital technologies but also generated many ideas. The second programme focused on building advanced analytics capabilities.

Select tech interventions to drive business value, identify small opportunities, and scale up quickly.

Next, the company augmented legacy systems, and technology teams were consolidated. The goal was to focus on areas where technology adoption would create real business value. The emphasis was on reimagining significant changes, identifying and initiating small opportunities, and scaling up quickly. Both bottom-up ideas driven by business requirements and top-down ideas aligned with strategic goals or competitor best practices were explored. Even practices from other industries unrelated to steel manufacturing were considered.

The benefits were numerous. One immediate advantage of digitalisation was the creation of algorithms for predicting failure rates, which enabled predictive maintenance and reduced failure rates across asset classes. Other initiatives, such as breaking down data silos and consolidating data across value chains, led to considerable gains across divisions.

ARTICLE AT A GLANCE

• GenAI needs to be complemented by human intelligence for effectiveness.
• AI can lead to enhanced services and increased operational efficiency.
• Developing a digital mindset and spreading digital awareness are essential for enterprise-wide digital transformation.
• Digital interventions are often selected with the sole purpose of driving business value.

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