Harvard Business Review, Article #2, The New Patterns of Innovation

The New Patterns of Innovation
How to use data to drive growth 
by Rashik Parmar, Ian Mackenzie, David Cohn, and David Gann Jan 2014


http://hbr.org/2014/01/the-new-patterns-of-innovation/ar/1

Idea in Brief

• THE CHALLENGE
• Established companies are notoriously bad at finding new ways to make money, despite the pressure on them to grow.
• THE ANALYSIS
• Most companies own or have access to information that could be used to expand old businesses or build new ones. These opportunities exist because of the explosion in digital data, analytic tools, and cloud computing.
• THE SOLUTION
• Answering a series of questions—from “What data can we access that we’re not capturing now?” to “Can we deliver one of our capabilities as a digital service?”—will help companies find ways to unlock new business value.

Traditional, tested ways of framing the search for ideas

• Competency based: 
• It asks, How can we build on the capabilities and assets that already make us distinctive to enter new businesses and markets?
• Customer focused: 
• What does a close study of customers’ behavior tell us about their tacit, unmet needs?
• Changes in the business environment: 
• If we follow “megatrends” or other shifts to their logical conclusion, what future business opportunities will become clear?
• Fourth approach: 
• It complements the existing frameworks but focuses on opportunities generated by the explosion in digital information and tools
• How can we create value for customers using data and analytic tools we own or could have access to?

Patterns

1. Using data that physical objects now generate (or could generate) to improve a product or service or create new business value.
2. Digitizing physical assets.
3. Combining data within and across industries.
4. Trading data
5. Codifying a capability

Pattern 1

Augmenting Products to Generate Data

• Because of advances in sensors, wireless communications, and big data, it’s now feasible to gather and crunch enormous amounts of data in a variety of contexts.
• Such capabilities, in turn, can become the basis of new services or new business models.

PATTERN 2

Digitizing Assets

• Over the past two decades, the digitization of music, books, and video has famously upended entertainment industries, spawning new models such as iTunes, streaming video services, e-readers, ...
• Digitization of health records, of course, is expected to revolutionize the health care industry, by making the treatment of patients more efficient and appropriate

PATTERN 3

Combining Data Within and Across Industries

• The science of big data, along with new IT standards that allow enhanced data integration, makes it possible to coordinate information across industries or sectors in new ways.
• The goal is to encourage the private sector to develop new business models, such as shared-delivery services in specific areas

PATTERN 4

Trading Data

• The ability to combine disparate data sets allows companies to develop a variety of new offerings for adjacent businesses.

PATTERN 5

Codifying a Distinctive Service Capability

• Now companies have a practical way to take the processes they’ve perfected, standardize them, and sell them to other parties
• Cloud computing has put such opportunities within even closer reach, because it allows companies to:
• easily distribute software
• simplify version control 
• offer customers “pay as you go” pricing

COMBINING THE PATTERNS

• The five patterns are a helpful way to structure a conversation about new business ideas, but actual initiatives often encompass two or three of the patterns

Key Questions

• questions designed to inventory the raw material out of which new business value can be carved
• What data do we have?
• What data can we access that we are not capturing?
• What data could we create from our products or operations?
• What helpful data could we get from others?
• What data do others have that we could use in a joint initiative?
• Armed with the answers, the team cycles back through each pattern to explore whether it, or perhaps a modification or combination of patterns, could be applicable in the company’s business context

AUGMENTING PRODUCTS

• Which of the data relate to our products and their use?
• Which do we now keep and which could we start keeping?
• What insights could be developed from the data?
• How could those insights provide new value to us, our customers, our suppliers, our competitors, or players in another industry?

DIGITIZING ASSETS

• Which of our assets are either wholly or essentially digital?
• How can we use their digital nature to improve or augment their value?
• Do we have physical assets that could be turned into digital assets?

COMBINING DATA

• How might our data be combined with data held by others to create new value?
• Could we act as the catalyst for value creation by integrating data held by other players?
• Who would benefit from this integration and what business model would make it attractive to us and our collaborators?

TRADING DATA

• How could our data be structured and analyzed to yield higher-value information?
• Is there value in this data to us internally, to our current customers, to potential new customers,or to another industry?

CODIFYING A CAPABILITY

• Do we possess a distinctive capability that others would value?
• Is there a way to standardize this capability so that it could be broadly useful?
• Can we deliver this capability as a digital service?
• Who in our industry or other industries would find this attractive?
• How could the gathering, management, and analysis of our data help us develop a capability that we could codify?

Success Factors