Businesses who embed data into their strategy will win in the future. In this presentation, we discuss some of the top things to consider when building your organisational data & insights capabilities in 2019. They include: 1. Define your project well 2. Embed active data management into your processes 3. Get your ‘drill downs’ right and enrich 4. Visualise & put it into context 5. Story tell 6. Evolve from access to engagement 7. Backwards is good but forward is better 8. Take the long road For more information, visit https://twoshape.marketing/services/data-and-insights/

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

2. Introduction
Where is the future of business heading?...
Smart people. Insights. Data-driven decision making.
Storytelling. Automation.
Following are some of the top things to consider when building your data &
insights capabilities.

3. 1. 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 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.

4. 2. 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.

5. 3. 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.

6. 4. Visualise & put it into context
1. Modern-day visualisations are changing the way we can view and interact with data.
2. Ensure you select 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.
4. Put it into context by asking the right questions and developing actions.

7. 5. 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.

8. 6. Evolve from access to engagement
1. Data 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.

9. 7. 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.

10. 8. Take the long road
1. Starting can be overwhelming – ensuring you prioritize 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.

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

12. https://twoshape.marketing
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