Series Title: How to Foster a Data-Driven Business Culture

Welcome to the third blog in our series on fostering a data-driven business culture.  To help you, the person who has to actually build the culture, we’ve brought together our hard-won lessons from decades of experience in growing analytics functions.

What does is it really mean to have a data-driven business culture?  For us, it means that:

  • Data driven insights are knitted into the business culture
  • Everyone is on-board and data literate
  • There is a business strategy that incorporates analytics
  • There is an innovative culture within the organisation

There are four key steps that businesses need to take in order to become data-driven.  We’ve already examined the first of these.  Now we’ll move onto the second:

Blog Title: Making It Happen – Moving From Strategy to Implementation 1

Last week, we examined the importance of weaving a data and analytics strategy into a clear, well-defined, well-understood, actionable, single strategy.  However, without a concrete roadmap as to how to action that objective, businesses run the risk of remaining in the theory phase of their journey to becoming data-driven.  This week, we’ll look at how to implement that objective.  It’s not a quick job – so we will need two blog posts to cover it!  This week, we will examine:

  • The pillars of a data-driven organisation
  • Assessing data-driven maturity
  • Building your team
  • Data-Literacy in your organisation


Pillars of a Data Driven Organisation

To pursue a data and analytics strategy, the main pillars of a data-driven organisation are:

  1. People: Creating a data literate workforce.
  2. Data: Architecting and building a data driven environment takes more than building just a technical infrastructure. The Data must exist, and it must be in the appropriate structures to support the business needs. The Governance around it has to exist.
  3. Systems: Creating a technical infrastructure to support a data driven environment.
  4. Decision Making Processes (Decision Space): The mix of data, processes and systems, as implemented by your team, are used to make a decision.

We will look at pillars 1 and 2 in this blog and pillars  2, 3 and 4 in the next installment of the series.

Figure 1. Key Elements of an Analytically-Driven Organisation


Where Are We Now? Where Do We Want To Be?

Not every organisation is starting from the same place, and neither are you.  So, to begin, you’ll need to assess where your organisation lies on a data maturity model. There are lots of data maturity models out there, but we especially like this one from Albert Garcia (see  Not every aspect of the description of each stage in the model will apply to you (for instance Big Data solutions like Hadoop may not be technically required in your organisation, however, the model should give you a good feeling for where you are in terms of your data environment.  More importantly, it allows you to assess where you want to be. Start improving your data environment in an incremental fashion to increase your level of maturity. Remember the level of sophistication you can achieve in terms of analytical models will be determined in some part by how far along the data maturity model you can move.

Figure 2. The Data Maturity Model


People – Building the Dream Team

This is a subject close to our hearts at The Analytics Store. It is key to remember that without a skilled team it is not possible to grow good analytics capacity within an organisation. The skills required to deliver a data-driven agenda are varied and need to be developed and nurtured. The image below illustrates the roles needed in an analytics team. For a detailed description of each role please refer to our previous blog – Analytics is a Team Sport.

Figure 3. The roles in a data analytics team

It will be difficult to find people for all of the above roles in the current recruitment climate.  Insead, consider training suitably technical and business-oriented candidates, internal or external to your organisation, in these various areas. Don’t underestimate the tacit knowledge an internal candidate brings: each of the roles demands in-depth knowledge of your business data, systems and processes.

The Analytics Store works with organisations to develop a custom skills matrix identifying the skills that they need for their particular organisation. The table below shows an example of the templates used for this.

Figure 4. The data analytics skills matrix, a diagnostic tool to assist with training needs analysis

After identifying the skills required, a training needs analysis can be completed to identify the skills each member in the team requires in order to deliver the performance that’s required of their role.  With the skills matrix, and the training needs analysis complete, your organisation can move to developing the programme of training, and, most importantly, measuring its success.


Creating a Data Literate Workforce

It’s not just your analytics team that needs to understand data – it’s the entire organisation.  The Analytics Store works with people in business and analytics, senior and junior, to ensure data literacy runs throughout the organisation.  The graphic below shows the ripples of data literacy spreading through an organisation from the core analytics team out to key decision makers.


Figure 5. The four layers of data literacy required. The outer three are all business leaders, needing various levels of data literacy, while the inner layer, the analytics team, is the only layer that needs deep analytics skills.

The outer three layers are all business roles, needing various levels of data literacy, while the inner layer, the analytics team, is the only layer that needs deep analytics skills. It is vital that all of these roles acquire the appropriate level of skills development to meet their specific needs.

Also, don’t underestimate how varied and specialist the world of analytics has become.  We often hear of people tiring of the jargon, believing that most of it is hype.  The big data landscape is now so large, however, that it would be a mistake to describe the last decade as anything but a revolution.  Data analytics and machine learning algorithms have evolved with this landscape and huge breakthroughs have been made: giving us varied applications across the areas of  image processing, speech recognition, predictive modelling, …..  There is legitimate reason for the explosion in terminology, and therefore, for the continual development of the skills within your organisation.

Figure 6. Big Data Landscape, 2012

Figure 7. Big Data Landscape, 2016

To illustrate this we can compare the Big Data Landscape graphics from 2012 and 2016. As we can see above, the technology landscape has changed enormously in this four year period.  Your multi-faceted team is difficult to keep up to date. Even trying to understand the different technologies and how they may be useful for your business is a genuine challenge.  It adds to the complexity of managing a team that the technical environment is in constant flux, so therefore the technical abilities of your team has to be constantly updating.  Somebody who completed a computer science degree just 10 years ago probably never studied Hadoop.  That person is now probably only 30 and already their skills will have to expand into a whole new space of learning.

The key take-aways from this discussion then are:

  • Assess and understand your data maturity. Improvements made on the data side improve the ability to implement your analytics strategy.
  • Analytics is a team sport.
  • Develop a skills matrix for your organisation to assist in a skills development program.
  • Understand that everyone across the organisation must be data literate, albeit at different levels.

In our next blog post we will look at data, systems and decision making processes, but in the meantime, please feel free to contact us with any queries or comments on the series so far. Tweet us @analyticsStore, or email us at

The Analytics Store is the leading training and consultancy firm in Ireland.  We assist companies in developing and implementing data and analytics strategies (from people to data environments).  Depending on your lifecycle maturity, we offer products that bring you to the next level. 

Kickstarter: €2,500.  This one-day workshop, facilitated by Aoife D’Arcy, will support your organisation in generating a strategy for the implementation of an in-house Analytics Function.  By the end of the day we will have created a road map for building a team and direction for analytics in your organisation.

Mentoring: priced on a consultancy basis, this service ensures that your analytics professionals can implement their analytics training back at their desks in your organisation.  Our consultants will work directly with your analysts, answering their specific questions and offering guidance around implementing both the strategy and practicalities of model building, deployment and measurement.