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Data Literacy, Homo Analyticus, VIA and more: top takeaways from Gartner 2020

The Gartner Data and Analytics Summit 2020 happened in Sydney last week, hosted at the beautiful International Convention Centre and attended by 1,300 people from various industries. With speakers from all over the world, it was easy to get lots of different point-of-views and insights – here are my top takeaways from the event.

The role of the Chief Data Officer

The keynote challenged us to rethink the definition of the Chief Data Officer (CDO). For me, the insight from that session was that we should be considering our Chief Data Officers as the Chief Disruption Officer, Chief Diversity Officer, Chief Design Officer and the Chief Decision Officer.

The example of how Netflix welcomes disruption and breakage caught my attention. Netflix uses a piece of software called Chaos Monkey to test the resiliency and recoverability of its cloud platform. The software simulates failures of services running within the cloud by shutting down one or more instances in production, ensuring engineers implement resilient services. By monitoring these failures and how systems recover, Netflix can prevent these events from happening in real life, delivering better customer experience (CX).

Data Literacy is a big challenge for organisations

Gartner defines Data Literacy as the ability to read, write, and communicate data in context, including an understanding of data sources and constructs, analytical methods and techniques applied, and the ability to describe the use-case application and resulting value.

Informally, it means, “do you ‘speak’ data”?

Some examples of what poor data literacy in organisations might look like:

  • Talking about information as ‘our greatest corporate asset’ or as ‘the new oil’ without treating it as an enterprise asset
  • Cherry-picking data to justify an already made decision, rather than examining the data to support the decision process
  • Asking for a report because ‘that’s the way we’ve always done it’
  • Data hoarding by individuals and departments, who don’t recognise the value of data and limiting how others could use the data
  • A fixation on hindsight-oriented analytics and “pretty pie charts” instead of high-value diagnostic, predictive and prescriptive analytics

Some examples of what good data literacy in organisations might look like:

  • Organisation policy is based on data, not on dogma or belief. Politicians and executive teams ‘speak data’ with ease and model the behaviour. The phrase ‘what does the data tell’ is commonly heard
  • Data is not the by-product of a process. Reporting and analytics are not an afterthought
  • Data visualisation and storytelling are commonly used techniques
  • Those who enter data understand why data quality matters
  • The organisation understands the nature of data privacy, security and ethics, bias and risk 

The Value, Information and Analytics (VIA) model

Often (not always) organisations start with an analytics program, look for data to feed the program and then wonder what the value of all that effort was. Gartner challenged us to use the VIA model when thinking about any problem or use case.

The Value, Information and Analytics (VIA) model

Start with the Value: What is the question, business problem or target outcome? How is the value realised? Have you spent enough time asking ‘why’ (five whys)?

Find the information: What data or data sources are needed to answer the questions. Where do they exist? Are they easily accessible? What needs to be done to get the information? Who is the gatekeeper to this data (should we even have a gatekeeper at all)?

Bring in the Analytics: What platform do we use to ingest all the data? What analytical or data science methods can we apply to the data?

The Homo Analyticus

Homo Analyticus: the data-driven decision-maker

The age of the Homo Analyticus is upon us! The data-driven decision-maker – but what characterises the Homo Analyticus?

Knowledge:  I know how to do it.

  • Analytical Ability: Can work with data to identify patterns; uses judgment to form conclusions that may challenge conventional wisdom
  • Learning Agility: Rapidly acquires new knowledge and learns new skills; deals effectively with ambiguity by using experience
  • Business Results Orientation: Understands business needs; delivers efficient and high-quality results
  • Teamwork: Promotes and facilitates coordination and cooperation among peers

Skills: I can do it

  • Communication: Conveys information to diverse audiences in a way that is easily understood and actionable
  • Influence: Asserts ideas and persuades others to gain support across a matrixed organisation
  • Relationship Management: Creates relationships and builds trust with internal and external stakeholders quickly
  • Decision Making: Considers the relative costs and benefits of potential actions to choose the most appropriate one
  • Prioritisation: Self-directs work through goal setting, time management, and planning

Mindset: I want to do it

  • Creativity: Applies original thinking to produce new ideas or products; questions assumptions and imagines future possibilities
  • Process Orientation: Follows directions; designs practices, policies, procedures, and systems to simplify work and use resources efficiently
  • Ethical Behavior: Considers and publicly discusses the ethical implications of organisational work, products, and decisions to dissuade unethical practices
  • Organisational Awareness: Understands and execute actions in line with the organisation’s mission, values, operations, structure and goals 

Some quotes that got me thinking

  • “Everyone has data, everyone has analytical tools. You win by asking the right questions. You win by acting fastest on answers.”
  • “Very soon, your personal device will know about you than your family.”
  • “More data is not necessarily better. Right data is better.”
  • “Trust is your new product. How do you build trust into your product design”?
  • “Don’t be afraid to fail, because FAIL is First Attempt In Learning.”
  • “Seven most expensive words in a business: ‘We have always done it this way’”

This blog is part of the #datareimagine series. For more experts' insights, clients' experiences and to download our datasheets, click the banner.

For more experts' insights, clients' experience and to download our datasheets, click the banner #datareimagine

Posted by: Priyanka Roy, Head of Data & AI, Intergen | 25 February 2020

Tags: Data Insights, #datareimagine

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