Last week we covered the 7 step play order to get the most out of technology and data initiatives and benefit from the multiplier effect from having the right foundation in place. The starting point, step #1, was the customer announcement, or the customer outcome. In this week’s post we are going to delve a little deeper into this step in a broader sense to help unravel the business strategy, which will inform the data strategy, which will in turn influence the technology choices we will have to make.
Is not being data driven an option? Only if you don’t plan on being a leader at winning market share and retaining your customers. You always need to be data driven if you want to be a market leader, but what data you are going to be driven by is the question and that depends on your strategy.
A clear strategy statement specifies objective, scope and the advantage. This leads to greater clarity about the value discipline that your business is aligned to.
The value disciplines
The excellent HBR article - Customer Intimacy and Other Value Disciplines - on the 3 value disciplines is a bit dated (30 years to be exact), but its wisdom remains timeless despite the internet powered information revolution that has taken place since, with new entrants displacing the market leading positions of some of the companies mentioned in this article, although many still remain as leaders. [As an aside, none of the companies that were in the top 10 list of the most valuable companies in 1993 are now in the 2023 top 10 list. And all except Berkshire Hathaway and Visa are technology companies - not important for this discussion, but interesting nevertheless].
The value discipline you choose as your strategy will determine the category of customer you choose to serve. And research suggests that it is virtually impossible to be masters of more than one discipline, with a few notable exceptions. So if you want to be a market leader, be clear about which category you are aiming for from the start, which will guide everything you will align to - category of customer, hiring policy, corporate culture, and of course, the information systems and the data architecture to support it.
Customer Intimacy
Operational Excellence
Product Leadership
Customer Intimacy
This value discipline espouses flexibility, responsiveness to the customer and a “have it your way” mentality. Driven by a commitment to deep personalisation, there will be a culture of empowerment of people working close to customers, highly trained in analytical capability, powered by data from multiple sources designed to optimise customer lifetime value, supported by systems that integrate seamlessly with a rich ecosystem of data sources. Typical data sources leveraged by these companies include internal transactional and historical data, internal and external industry data on consumer behaviours, and external geo-demographics data.
Distributed data architecture paradigms with federated domain level ownership, strong inter-domain data exchange contracts and flexible on-demand allocation of computing resources are not uncommon for firms that belong to this category.
Two market leaders that epitomise this value discipline: Amazon, Netflix
Operational Excellence
Firms that choose to master this value discipline interact with customers using channels that promote low user friction, often sell direct to customer, operate on low overheads, are the lowest cost producer in their industry and lead on price, followed by convenience. Their systems and processes enable virtual inventory rather than real inventory, made possible through just-in-time manufacturing and delivery, powered by deep real-time data on purchase patterns and inventory movement, with tight integration with information systems used by their suppliers and delivery channel partners.
Centralised data architectures often prevail in this category, with fast real-time data movement (or access) through the value chain, supported by core strengths in Master Data Management (MDM) and Reference Data Management (RDM) disciplines. High data quality enables high levels of automation that further reduce cost and help maintain price leadership.
Classic examples in this category are Walmart and Dell. But we include Berkshire Hathaway in the list, being an investment holding company that thrives on creating value by consistently making contrarian bets, and ‘influencing its acquisitions to maximise operational efficiency’. Also in this category is Amazon, who through high levels of automation enabled by robotics have become masters of two.
Product Leadership
Firms in this category are creative, quick to commercialise products, value entrepreneurial spirit and hire employees empowered and incentivised to scout ideas from outside-in. They have the deep pockets to allocate development and marketing resources to launch new products quickly, are willing to fail by making quick decisions rather than make a late decision or not at all. They are characterised by open exchange of ideas devoid of hierarchical boundaries with less analysis and more action. Business divisions are often run like startups backed by the resources and funding from the mother ship - much like a venture capital firm. Hiring is focused on cultural fit rather than industry specific experience, valuing team players with the ability to receive feedback and pivot quickly as needed. These firms are not wedded to flagship products, often choosing to make their own products obsolete, in order to maintain product leadership.
These businesses are often powered by federated system architectures designed to align with decentralised business units empowered to react to the market, supported by open communication channels agnostic of management hierarchy, and portfolio analytics designed to objectively assess success and failure, to better inform decision makers and protagonists on where the next cycle of bets should be made.
Market leaders: Apple, Google, Nvidia and Tesla.
Mastery of Two
The research shows that mastering one value discipline alone is difficult, making it unlikely that anyone could master 2 or all 3. With only a few notable exceptions, most prominent one being Amazon. Interestingly, becoming adept at using state of the art information systems seems to be the pathway to crossing the boundary from mastering one discipline into mastery of a second discipline, with the typical combinations being [Customer Intimacy + Operational Excellence] and [Production Leadership + Operational Excellence]. Operational Excellence seems to be the common factor here, becoming a strength for those companies that are able to leverage technology, particularly information systems excellence, to their advantage after leading initially with one of the other two disciplines.
The supply side view
Having looked at the demand side view of strategy, what about the supply side? A look at core competencies popularised by Prahalad and Hamel suggests that staying true to inherent capabilities allows deep roots to set, enabling core competencies to mushroom into core products which combine to produce market offerings (the leaves are abundant in number and wide in variety, despite the roots being smaller in number and narrower in variety, to use a tree metaphor). Staying focused on core competencies allows the freedom to innovate and guide end products to evolve and change to fit market needs. Core competencies strengthen with reinforcement over time, reasserting the deep moats of competitive advantage, and guiding the patterns of diversification and market entry into new products that attractiveness of markets alone cannot provide.
Technological know-how, discipline and culture works together to create core competency. Within this paradigm is the increasing relevance of a powerful set of ingredients specific to information technology - "the combination of information systems, data fabric, and analytical nous among the workforce to leverage knowledge about processes, products and customers to harmonise streams of technology and organise work to deliver value". The company’s information systems and analytical capacity can be thought of as not only a core competency, but also an intermediate ‘core product’, which is part of the magic ingredient that helps it either directly deliver the end product or helps create its competitive advantage, across any of the value disciplines discussed above.
Data, Automation and AI as core competencies
Data, Automation and AI related skills, technical know-how and domain knowledge are core competencies, and Data, Automation and AI product functionality and modules are core products, which can be either ingredients to make end customer products (take Google's and Amazon's cloud computing offerings as an example) or ingredients that support the firm to excel at any one of the 3 value disciplines mentioned above.
Prahalad also recommends firms to create a Strategic Architecture that maps underlying core competencies (the roots) to ‘core products’ which in turn map to business units and end products (the leaves). Products will come and go, but the core competencies run deep, and the core products present pathways for the firm to spin up new products or supply the core products upstream in the value chain of equivalent end product markets.
Google’s commitment to engineering and AI excellence, Apple’s unwavering discipline in product design and user experience; Netflix’s deep rooted culture of relentlessly leveraging user data to decide what content to create and what to eliminate; Nvidia’s meteoric rise leveraging its graphics accelerator chip know-how to cash in on the AI revolution with its GPU offerings; Tesla applying its battery technology know-how to cars, power walls and solar panels; Berkshire Hathaway deploying its 58 year experience in the discipline of investment management to acquire and enhance the operational efficiency of businesses as far ranging as Kraft Heinz, Coca Cola and Apple; and Amazon’s pioneering standard setting in not only establishing the culture of seeking customer feedback and using data to drive recommendations, but also double up on a second value discipline of operational excellence through its other core competency in robotics within its warehouse facilities, enabling the 'magic of next-day-delivery':- are all world class examples of focus and commitment to a value discipline and nurturing core competencies by in-housing strategic technologies and talent even in the face of cut-throat competition and pressure to outsource.
The Upshot of all this
Leverage your greatest asset - people - and the inventory of skills they bring to the table, and apply them in a non-traditional way to mould your core competencies and core products. This discussion has incidentally made reference exclusively to companies in the list of the top 10 most valuable companies in the world (only exception being Netflix who are nevertheless the market leaders in their content streaming niche). i.e. This actually works!
List of the world's most valuable companies, in order of market capitalisation, as at 30/6/2023 (USD Trillions):
Apple (3T)
Microsoft (2.5T)
Alphabet (1.5T)
Amazon (1.3T)
Nvidia (1T)
Tesla (0.8T)
Berkshire Hathaway (0.8T)
Meta (0.7T)
TSMC (0.5T)
Visa (0.5T)
What is our product?
Tribana is a Data, Automation and AI product focused company that aims to make core products that can be used by customers to build their own core products and/or end consumer products.
What value discipline do we follow?
Tribana is committed to the Customer Intimacy value discipline as its primary inspiration to help shape the way we develop Data, Automation and AI products and provide services to customers looking for ways to identify gaps in their capabilities, set up the right data foundations, and exploit Automation and AI to optimise their value creation. We use the tagline - Orchestrate, Automate, Optimise, which refers to the sequential activities of:
Orchestrate - Setting up the right data foundation
Automate - Implementing low complexity automation to increase productivity and process efficiency
Optimise - Building AI models and buying AI products that can take you to the next level in business performance.
We thrive on knowing who you are and what makes you successful.
What is an Automation product?
An Automation based software product is only able to respond to outcomes it has been programmed for.
What is an AI product?
An AI based software product is a special type of automation product that is able to ‘learn’ from past outcomes, and ‘adjust’ its outputs to continuously track a desired outcome, within a specific domain or predetermined set of boundaries or parameters. While a general purpose AI product would be great to have, such capability is not yet available (not to us anyway) and remains the holy grail of computer science, and artificial intelligence research.
The irony - greater automation leads to needing more skilled people
A defining trait of an AI product is the ability to perform work that would otherwise need to be done by a human, yet this ability depends on continuous human oversight for optimal performance.
And that’s it for this week. Next week we will delve a little deeper into the Orchestrate theme (Part 2), and look at specific data architectures that align with the value disciplines discussed in this article, and consider specific technologies that can help bring this to life.
See you then!
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