What Is The Value Of Data Governance

Hold onto your hat's folks, because we're about to dive into the world of data governance - and let me tell you, it's a wild ride. 

Now, I don't know about you, but I find it fascinating how people react to the world of data. It's like everyone wants to know the value of every single data initiative, as if we must prove ourselves worthy of existing. And don't get me wrong, I get it - every initiative should provide value for money and be justified. But why is it that data comes under more scrutiny than any other activity? 

Let's compare it to corporate governance, for example. We all know that our board of directors and non-executive directors must demonstrate they are doing an appropriate job in governing the company to ensure it is run appropriately. But has anyone ever asked, "What is the value of continuing to provide governance at board level to run our organisation?" Of course not - we wouldn't have an organisation without corporate governance. 

Corporate Governance Is:  

Effective governance involves supervising the management of a company, managing risks and identifying opportunity, so that business is done competently, with integrity and with due regard to the interests of all stakeholders. It embraces regulation, structure, good practice and board ability - CIPD 

Let's take this lens from the requirement of Corporate Governance and look at Data Governance. 

What Does Data Governance Do? 

So, what exactly is data governance? According to the Data Governance Institute, it's "a system of decision rights and accountabilities for information-related processes, executed according to agreed-upon models which describe who can take what actions with what information, and when, under what circumstances, using what methods." In other words, it enables the appropriate and secure use of data in alignment with our policies. Think of it as the rugby referee - just as the referee enables the game to continue while ensuring the safety and fairness of the game by enforcing the rules, data governance enables data to be used appropriately while ensuring compliance with policies and regulations. 

 Data Governance should be an enabler, not the data police! 

Adaptive Data Governance flexes and adapts to the different needs of data use. For instance, if data is used internally in a sandbox, less governance is required than if data is used to create a report to be sent outside the organisation to a regulatory body. 

Data Governance Definition Is: 

Data Governance is a system of decision rights and accountabilities for information-related processes, executed according to agreed-upon models which describe who can take what actions with what information, and when, under what circumstances, using what methods.”  - The Data Governance Institute 

 Without data governance, it’s almost impossible to comply with privacy laws like GDPR and CCPA. You don’t want to receive regulatory fines, by breaching any of these laws, which can set you back hundreds of millions of pounds and damage your brand reputation. 

Is This Any Difference To Corporate Governance? 

We can rewrite the definition of Corporate Governance to be the definition of Data Governance by replacing the crossed-out words with those in red below. 

Effective governance involves supervising the management of a company data, managing risks and identifying opportunity, so that business is done competently, with integrity and with due regard to the interests of all stakeholders. It embraces regulation, structure, good practice and board organisational ability – Data Queen 

However, I think one of the challenges with organisations scrutinising the set-up of Data Governance and data management (you need both), is the relative newness of the data capability, in comparison to Finance, HR, Customer Services, etc. Which no one can recall as they have been embedded into the organisation's fabric for as long as anyone can remember.  

And here's where things get a little tricky. Our lovely friends in those tech companies who want to sell their solutions as a silver bullet for your data woes are now determining everything under the data umbrella as data governance. I wholeheartedly disapprove of that approach - it's a sales tactic, plain and simple. Do these tactics work? Who knows - only they can tell us that. 

Don't get me wrong, we may need some technology for data governance, much like we have a few technology approaches for corporate governance. But in reality, you do not need a technology solution to implement data governance - unless you are a very large, data-mature organisation. Then, I agree, the tech will support your compliance efforts. Whereas Data Management very much needs a tech solution. Trying doing Data Quality without a technology solution! 

My View Of The Data World For Data Governance & Data Management 

Data Governance is an integral part of managing data. Without Data Governance, Data Management activities will not work beneficially. By performing one without the other, is like only having one glove. It works partially (to keep only one hand warm) but not effectively, as you will always have a cold hand, even if you keep swapping the gloves between hands – not a good way to keep yours hands warm or for any organisation to operate. 

Data Governance 

Policies – That we must comply to. Ensuring data is managed appropriately for security, privacy and access. Examples are; Retention, Privacy, Data Protection, Data Classification, Data Encryption, etc. 

People – The roles, responsibilities, operating model and forums or committees to ensure we are openly sharing and discussing our views and collaborating on the direction of managing our data 

Principles – Those high level easy to be understood by everyone, of what we what to use to guide behaviours, expectations and understanding. Examples of Data Principles:  

Data is Shared; Data is Protected; Data is Not Sold; Data is Owned by the Business; Data is Trusted; 

Data Management 

This is the How and What will be done to ensure data is fit for purpose and easy to use, for example, 

Data Quality, Master, Reference & Metadata Management, Data Catalog (incl. Lineage, Glossary), Metrics, Processes, Analytics (incl. Wrangling, Visualisation). All with a sprinkle of AI capability to enable users to be consistent and maybe ever a ChatGPT type Large Language Model to enable everyone to access the data and information they need at the right time.  

What complicates the fact is we have a Data Governance Framework where all the data components relating to Governance, Management, Culture, Exploration and Architecture live, this in my opinion is called the wrong name and that causes confusion as Governance is one of the 5 areas for data, not the main or only one. All 5 are needed to work together seamlessly to be effective. 

I would recommend it should be called a Data Framework....Simple...but I can't change this on my own. We must live with the mislabelled assets of the past. 

What Is The Value Of Data Governance 

Data governance is a critical component of any organization that uses data, but it can be challenging to justify its value. To fully understand the importance of data governance, it's essential to define what it is and why it is necessary. Without proper data governance, organizations can face challenges that impact their efficiency, decision-making processes, and compliance with regulations. 

With it -  

• You can demonstrate control and understanding which is likely needed for legislative compliance 
• The entire organisation has a clear understanding of roles, responsibilities and accountabilities with; Owners and Stewards which are key in Data Quality Management; reporting and resolving data issues with route cause analysis to reduce reoccurrence. Thus, developing trust in your data  
• With your Data Owners in place, it is easy to manage data security, sharing and access control. As the decisions required can be made effectively. For example, The HR Data Owner can define who sees and has access to employee data. We would not want everyone seeing their managers address and salary, would you as this may cause disconcertment.  
• Policies will ensure appropriate usage to reduce the risk of breaches or loss of data, in turn protecting the organisations reputation 

Without it - 

• Efficiency is a significant concern when it comes to data. Without data governance, workarounds are often necessary to deal with issues related to data. This can be costly, as manual cleansing and fixing of data can take a significant amount of time and resources. By implementing a data governance framework, organizations can reduce or even eliminate these manual processes, saving time and money. An unchanged statistic for many years is that Data Scientists / analysts spend 80% of their time finding and preparing data for insight creation. Taking the average salary of ￡50k that’s ￡40k a year for each of your scientists /analysts lost each year to administrative tasks that good data governance could reduce substantially   
• You risk fines, reputation and increased costs to rectify issues after the fact, which for Data Quality can be as high as 100 times more. For example: without Owners & Stewards managing Data Quality the cost could be calculated using the 1/10/100 rule in data quality. ￡1 cost for correcting data at the outset. You lose ￡10 for every ￡1 due to a reactive approach to data quality.  You lose ￡100 for every data quality issue you do nothing to rectify. 
• Departmental functions develop a lack of trust in company-wide data, which leads to increased costs as functions set up shadow data/IT to silo their data which they will trust and not share it with others, leading to duplicated capabilities within each function keeping their own data. This siloing leads to difficulties in developing a data culture of trust, transparency and sharing further leading to opportunities and innovation for revenue generation and customer retention being missed 
• Poor decision-making is another major challenge that can result from inadequate data governance. When decisions are based on reports that contain poor quality data, it can lead to inaccurate and ineffective decision-making. By ensuring that data is properly managed through data governance, organizations can rely on accurate data for their decision-making processes. 
• Compliance with regulations is critical in today's business world. Most organizations operate in industries that require compliance with regulations, and many of these regulations require proper governance of data. For example, GDPR & CCPA where solid data governance can help organizations meet regulatory requirements. Fines for non-compliance and breaches can be as high as 4% of global turnover. 

For those who live by the DAMA approach to data, the Dama wheel has Data Governance at the centre because it forms the foundations for all data management capabilities to operate effectively.  What more justification do you need for Data Governance and Data Management without the high scrutiny of what is the value. 

When communicating to your leadership team, make the comparison between corporate and data governance as data governance is as much a critical need as your corporate governance! 

In conclusion, while some may see data governance as a generic best practice that every organization should implement, it's essential to understand that it is necessary for every organization that uses data. Data is used in almost every aspect of an organization, from dealing with customers to generating reports and understanding revenue and expenditures. Data governance provides the foundation for everything else to work correctly, including obvious data-related activities like master data management, business intelligence, big data analytics, machine learning, and artificial intelligence. However, it's essential to remember that data governance is not limited to data-related activities. Many processes in an organization can go wrong if the data is incorrect, leading to customer complaints, damaged stock, and halted production lines. 

While some may not find data governance "sexy," it's crucial for everyone in an organization to understand its importance. Data governance should not be an overly complex burden that adds controls and obstacles to getting things done. Instead, it should be a practical thing, designed to proactively manage the data that is essential to an organization. 

if your organization uses data (which most organizations do), data governance is essential. However, it's crucial to spend time working out the specific reasons your company should be implementing data governance. By doing so, you can effectively engage your senior stakeholders and gain their buy-in. 

More frameworks, insights and practical advice at: https://lizhendersondata.wordpress.com/

References:  

Corporate Governance | Factsheets | CIPD 

Defining Data Governance - The Data Governance Institute 

Principle - Wikipedia 

https://www.nicolaaskham.com/blog/2019/4/29/why-is-data-governance-important-for-everyone 

Image credits: 

https://edps.europa.eu/data-protection/our-work/subjects/police-directive_en 

https://www.irishrugby.ie/2019/11/20/irfu-referees-in-action-across-europe-this-weekend/ 

https://damadach.org/dama-dmbok-functional-framework/