Data Literacy Workshop

71point4 > Data Literacy


Building a data-driven organisation has been a catch phrase for the last decade. But in our experience many organisations still face challenges with the practical implementation of this. Often teams tasked with driving the data agenda and the teams responsible for the day-to-day data tasks do not understand each other’s respective needs and challenges. This typically culminates in misunderstanding, frustration and inaction. The good news is that it is relatively easy to get teams to “speak the same language” – all is takes is some a shared understanding of  terminology, an understanding of the limitations and strengths of the organization’s data environment, as well as an understanding of opportunities to better leverage existing data and bring in new data. This is what we call the foundations of Data Literacy.  


The objective of the workshop is to:  

  • Create an awareness of the potential of data to shape decision-making across operational functions as well as at a strategic level  
  • Create a shared understanding across the organisation of key technical terms and concepts 
  • Create an awareness of the importance of data governance, with an emphasis on protection of privacy 
  • Create an awareness of the data pipeline and the strengths and limitations of internal and external data within key departments / units that engage with data  
  • Create an awareness of the importance of accurately capturing and updating data within key departments / units that generate data through their interaction with customers 
  • Enable business teams within the organisation to engage with technical teams / analytical teams more productively 

Who are the workshops designed for?

These workshops are relevant for managers in public, private and non-governmental organisations including government departments, regulators, financial institutions, development finance institutions (DFIs), donor organisations and think-tanks.  

Given the practical nature of the workshops, the content is tailored to the specific context and nature of the participants internal data and particular challenges

What is covered in the workshop?

Sessions will include: 

  • An overview of types of data, generic limitations and pitfalls to be aware of in data and analysis 
  • An overview of internal data, how it is generated and maintained, and specific limitations that impact on data quality and coverage 
  • An overview of the data pipeline (where internal data comes from, how it is captured, stored, analysed and disseminated), and the impact of operational processes on internal data 
  • Hints and tips on framing questions and data requests,  and working productively with data and analytics teams 
  • Core principles of sound data governance, including protection of privacy and data security 

Workshop schedule

The workshop itself will be delivered of 2 days with an additional day of pre-planning held in the week prior to the start date.   

Pre-workshop planning 

Prior to the workshop, the facilitators will meet with internal data / analytics teams to understand:  

  • The internal data landscape at a high level (what data exists, how good it is, what key data gaps exists) 
  • The internal processes with regard to requests for data / analysis from business users  
  • Key challenges experienced by the data / analytics teams with regard to interaction with the business
  • Suggestions for improvement


Session 1: Data overview

  • What is data and what is customer data?
  • How is it generated and curated?
  • How do you use it?
  • What insights can it enable?

This session provides an opportunity to highlight the importance of sex-disaggregated data and analysis, using data to understand underserved customers, and to monitor financial inclusion.

Session 2: Deep dive into internal data

  • What data exists in the organisation?
  • How good is it?
  • Which teams generate data, curate data, ask questions of the data, analyse data, use the outputs of the analysis? 

Session 3: Opportunities to leverage data inside the organisation

Internal teams to prepare an analysis wish list.

  • What questions do they want answers to?
  • Which of these questions are once-off, which should be reported on regularly?   

Session 4: Privacy and data governance (wrap up)

With a focus on next steps including:

  • The development or review of a data strategy
  • Specific priority questions to be explored that will inform business decisions
  • Changes in operational processes that impact on data quality and coverage (e.g. how client data is captured / validated) and / or changes in internal processes regarding interaction with data / analytics teams 

Meet your presenters

Illana Melzer

Illana is a lifetime consultant with over 20 years experience. She works with corporate, public sector and not for profit clients across a range of sectors including banking, consumer credit, other financial services, and housing. Illana holds a Bachelor of Business Science degree in Mathematical Economics.

Illana started 71point4 in 2018. She co-founded research and analytics consultancy, Eighty20 in 2001 and successfully led their strategic research team for over a decade. Prior to that Illana worked at Accenture and the Monitor Group.

Claire Hayworth

Claire is a consultant at 71point4 with a decade of research experience. She has a Business Science degree, specialising in Marketing from the University of Cape Town and has completed two online courses through the Digital Frontiers Institute.

Claire's work focuses on issues related to credit markets, specifically looking at levels of indebtedness, affordable housing and financial inclusion. Claire is experienced in the analysis and usage of transactional data to understand consumers financial behaviours and patterns.

Hanjo Odendaal
Hanjo Odendaal

Hanjo Odendaal holds a PhD in Economics from the University of Stellenbosch where his doctoral thesis focussed on exploring the media-economic nexus.

Hanjo's PhD research consisted of constructing a novel economic index which characterized the sentiment towards the current economic climate in news articles using machine learning and sentometric techniques. Hanjo leads the advanced data analytics and statistical modelling aspects of the work at 71point4. He is passionate about exploring different methodologies to collect, analyse and productionize new and alternative data sets. Recent projects include analysing large transactional datasets from an inter-bank switch in Nigeria, analysing mobile money transactional data in Rwanda and working closely with the Bureau for Economic Research (BER) to productize the work from his thesis

Interested in the workshop?

Get in touch if you are interested in hosting a workshop for your team or have any questions: