Data & insights in 2019. The top things to consider when building your data analytics capabilities

Preamble: This is an extract from the presentation: “The top things to consider when building your data & insights capabilities in 2019”. You can find the presentation version on slideshare.

Introduction

Where is the future of business heading? Experts believe it will evolve around smart people, data analytics, insights, data-driven decision making, storytelling, and automation. While all of these in isolation may not make sense, the sum is greater than the parts. What ties it together? A data & insights strategy. Following are some of the top things to consider when building your data & insights capabilities in 2019.

Define your project well

  1. Be specific with what you are looking to achieve. An ill-defined scope (or aiming too big too early) will misguide efforts and slow down your data analytics project.
  2. Lead with business priorities and questions that you want answered, not just using data for data’s sake.
  3. Understand who from inside and outside the organisation you need to get involved. This can be done by creating a data workflow for your organisation. Clear ownership and handoffs are important.

Embed active data management into your processes

  1. As data sources become more complex, diverse, and numerous, data management is now even more critical in modern BI deployments.
  2. Once you have identified your data, many times, getting access to clean versions of it is the biggest challenge.
  3. Organisations must ensure accuracy within their data and its use in analysis as well as ‘one source of truth’.
  4. The key is to identify the most foundational data sources and actively manage it over time through a series of processes and rules.

Get your ‘drill downs’ right and enrich

  1. Ensuing you have the right data sources is foundational, however ensuring you can drill down to the required level is just as important.
  2. Through defining the right questions at the start of the project, you will be able to understand the cuts of data required and how far you need to drill down to get your answers.
  3. You are better to drill down further and create deeper rules as it will allow for a more robust line of questioning as you explore the outputs.
  4. Over time you can enrich your data by adding new datasets, such as external overlays.

Visualise & put it into context

  1. Modern-day data visualisations and business intelligence platforms are changing the way we can view and interact with data.
  2. Ensure you select data visualisation tools that can best represent your data for easy consumption but also aligns to the skills set of your organisation in the building phase.
  3. Understand what the data means in the real world is arguably the most important part. Business intelligence needs to be real – not just numbers and visuals.
  4. Put it into context by asking the right questions and developing actions.

Story tell

  1. Now that you can see your data, storytelling focuses creating a bridge between our data and its real-world applications by building a narrative.
  2. Storytelling humanises the data-efforts so we can understand it and move it into action.
  3. It allows leaders to rally organisational efforts behind the findings and articulate why they matter and what needs to be done, as much as what they are.

Evolve from access to engagement

  1. Data analytics and insights is not just for the few. It must be shared and become a part of everyday business.
  2. Democratise your data to empower individuals and functions within organisations to understand and take ownership of what they need and be as effective as they can be. People must engage with it – not just have it presented to them
  3. Empower people to dive deep and lead the next iterations and roadmap for your data initiatives.

Backwards is good but forward is better

  1. As a beginning, always start with backward looking or current state data. This will give you a snapshot of current or past performance and allow the team to immerse themselves in the data practice.
  2. As your efforts evolve, bring in predictive views through data science practices such as cluster modelling, which will allow you to forecast trends and predict future occurrences to support decision making within the organisation.
  3. Machine learning will enable systems to gain deeper domain knowledge over time based on your company’s data and the types of questions the users ask.

Take the long road

  1. Starting can be overwhelming – ensuring you prioritise is key and build complexity over time.
  2. Work with each department or function to identify ‘one burning desire’ that will make their job easier/the function more effective by using analytics.
  3. Once you have a firm grip on the basics and it is being used effectively, build a roadmap that will see your efforts evolve over time.

Conclusion

  • Businesses who embed data into their strategy will win in the future.
  • Start by asking questions you need answers to and ensure the outputs are actionable.
  • Democratise access and empower your people to engage with it.
  • Build capabilities over time.
  • There is no better time to start than now.

We focus on demystifying data & insights for marketing, sales and the entire business. What is the result? Easy to use data visualisations that impact day to day decisions and help business owners and function leaders evolve to a data driven business. Two Shape is based in Perth and work with customers all of the world.

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