Testing the fitness of your organisation's preparedness for data.

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Day zero, you have arrived and you have 100 days to plan. (H0) How do you determine if your new company is addressing the underlying issues that hold back data from being what they imagine it can be? 

The issues that hold back an organisation from really capturing the value of data are at a  minimum: org structures, people issues, a lack of accountability, and incentives. Whilst having a CDO, doing data science, having analytics, using artificial intelligence, testing data quality, and a world class data governance structure make a difference; true transformation will remain a struggle if the structural issues remain.

The question is how do we, as a CDO, test the fitness of our organisation's preparedness for data.  If the results are acceptable to the leadership team is one of politics and is way beyond  the scope of this article.  

To test the fitness of your organisation's preparedness for data, it is worth looking at four areas. Is there a preparedness plan? How they put data to work today. Organizational Capability, and finally Culture.

Is there a preparedness plan?

This is really simple, ask the CEO if there is a preparedness plan. If there is, ask for a copy of it and review it with the framing of data. If there is not one, probably best to ask why not.  There may be one, but check the data of publication (issue), and if it does not address all the areas of responsibility that come under the CDO,  you need to flag that it needs work.

How they put data to work today.

Does the company equally value “small data” as well as big data and data science? Does it hold small data with the same level of importance and priority as big data. Small data is also termed thick data.  It is small in size but has depth of insights.  

The media attention on data science makes it appear far easier than it is. You need to determine if this organisation is based on data science from social media posts or on data science from the commitment of time and resources.  It is worth investigating if there is built-in structural animosity between the data science teams which are invested in driving change, and the rest of the business , which is driven by KPI and incentives.  Where do the teams sit and how are they bridged?

Lastly review past management and board papers and recommendations to determine if there is attestation of data or if the blind are leading the blind.  

Organizational Capability

A company’s organisation is supposed, amongst other things, to make it possible for people to do their work, with control in place to ensure they are doing the right work. Organisational capability can be a major hurdle when it comes to making data work, as divisions are often organised to optimise for different objectives. 

There are numerous issues including management’s confusion and conflation of data, technology, data silos, and the lack of clear responsibility around data roles. When there is a lack of skilled data architects, data engineers, and data quality professionals the organisation just does not have the capability or structure. 

All regular readers of this column know that I often verbally fight against leaders who opine that data is the new oil, preach that data is an asset, and demand data-driven decisions - as they don’t have a clue. The reality for most employees is that “data” to them is just another thing they need in order to do their jobs. Companies don’t sort out ways to create value from data as they don’t teach people how to use it to make better decisions. (my masterclass does) 

Organisation changes needed to address the structural issues are the responsibility of a company’s senior leadership. Yet most leaders appear to be sitting on the sidelines, perhaps fearful themselves or unsure of what to do and waiting for McKinsey, Deloitte, Accenture, PWC, BCG or one of the other global consulting firms to give them an answer.  This is want you are seeking to determine.  


The implications for all those interested in advancing data for better decisions are profound. Culture is often cited as the biggest barrier to progress with data, I will argue and my analysis confirms it, that it is in fact ontology and epistemology that holds companies back.  The questions to ask the organisation is, “Is there a top level ontology?” and “How do we know what we know is true”  

Note to the CEO

“Testing the fitness of your organisation's preparedness for data”is one of the most important jobs you will delegate.  When interviewing for your next CDO, ask them the question “how would they test this organisation for preparedness?”   There is no point in asking about their data expertise and capability, they would not be sat in front of you if they were not top of their game.   How will they address the politics and policies based on their review.  The point here is that if you like their smooth approach, they are likely the wrong person as you will just get more compromises and not the action focussed delivery required to become that data company you desire. 

Whilst our ongoing agile iteration into information beings is never-ending, there are the first 100 days in the new role. But what to focus on? Well, that rose-tinted period of conflicting priorities is what </Hello, CDO!> is all about. Maintaining sanity when all else has been lost to untested data assumptions is a different problem entirely.