The data-driven organisation
Organisations know that to capitalize on the data economy and grow their business, they need data to make decisions that enable delivering a unified customer experience and employee experience, supply chain integration, innovation and new business models.
In order to become data-driven, organisations are looking to build their data ecosystem. But what is it?
Perceptions vs reality
When people think about data ecosystems, more often than not, they think about those within the organisation. They aspire to organisations such as Google, Apple and Samsung that have strong data ecosystems within their brand that enable the organisation to provide a seamless, personalized customer experience, connecting smart phone and computer, software and apps, home entertainment and appliances, watch and car; all the while collecting more data to increasingly personalize the experience.
But in order to deliver that personalized, seamless customer experience – or employee experience, supply chain integration, innovation or new business model - the data ecosystem needs to operate within and outside the organisation, in the customer’s ecosystem. And the reality is once you go outside the brand, like Apple, Google, Samsung, they don’t play well with others, leading to missing data points in the customer journey, delayed response times, friction in the experience and potential customer pain.
In aspiring to build a data ecosystem, people are frustrated, struggling to integrate data within their own organisation, let alone others. The solution of stitching systems together costs money and time, and risks compliance, PII (personalized identifiable information) safety and brand reputation.
The definition of data ecosystem is limiting its potential
Half the problem is in the definitions of data ecosystem, of which there are many, mostly alluding to the systems and applications used to capture and analyse data within the organisation or brand (as above), and possibly extending to those used to capture and share data sets between organisations.
This is a very narrow definition and capability that won’t deliver the seamless, personalized customer experience that people expect.
The data captured within the organisation alone is not enough because much of the customer ecosystem and journey exists outside the organisation. In order to understand past behaviour, respond to, predict, plan for and ethically influence future behaviour, you need to understand relationships between the data. This requires collecting, analysing and applying:
data and relationships between data
over time and in real-time
at the individual level and the group level
across the customer journey and throughout their current and prospective customer ecosystems
from sources both within and outside the organisation.
A new vision
We need a definition or vision of what a data ecosystem could be.
Michael McDonald, CTO of Fl@World, describes the data ecosystem as follows:
“Similar to a biological ecosystem, a data ecosystem is a living, evolving collection of:
Systems and applications used to capture, integrate, analyse and share data within your organisation and between organisations or individual entities of your “customers” i.e. current, prospective and lapsed customers, employees and stakeholders such as shareholders, suppliers, agencies
Structured and unstructured data contained within these systems and applications, captured, integrated, analysed and shared at an individual level (pending permissions) and in real-time;
Data history, builds and relationships between the data, systems and applications
The controls and conventions on individual data points
And in fact, the people who are using the data ecosystem are part of that ecosystem too”
“With the rapidly evolving needs of customers, new technologies and capabilities such as AI and machine learning, organisations need a living, evolving data ecosystem that connects people and data in real-time.”
As first published by First 5000 on April 10, 2019. Author Rachel Bevans.