What is Data Governance?
The systems, people and processes that are involved in the storing, processing, understanding, socializing and owning of data within an organization.
Many companies are realizing the power of data and the value that is has to offer. The Chief Data Officer (CDO) role is becoming a must-have for the companies leading the way in the digital era. No longer is Data Governance implemented just for regulatory compliance. It has the ability to set the foundation to get maximum value from data and empowers teams and individuals to do more with data and take advantage of opportunities in a fast paced, competitive world.
Data Governance covers areas such as Data Stewardship and Ownership, Data Quality, Data Dictionaries/Glossaries/Catalogs, Data Lineage, and other areas to help companies understand and control their data assets and focus on the proper management of data. It can also cover data security, integrity, usability, integration, compliance, availability and the overall management of internal and external data flows.
A CMO has a system for their data (e.g. Salesforce), a CFO has a system for their data (e.g. SAP) and a CIO has a system for their data (e.g. ServiceNow). So why isn’t there a system for what could arguably be the most important asset a company has, Data? This is where Data Governance comes in, and often, Data Governance is where the Business and IT finally meet.
Why Data Governance?
1. Regulatory Compliance
Data is everywhere and so are regulations, so it is not surprising that the two are having quite a large impact on each other. In fact, while it is possible to have data without regulation and regulation without data, you are highly unlikely to find one without the other. Companies are going to need to have their data readily available for the people that need it, where it originated from, and will have confidence in the quality. This doesn’t only apply to financial services companies. Most companies are holding Personally Identifiable Information (PII) on their customers, partners, vendors etc. and this data must be handled correctly for regulations such as GDPR.
2. Digital Transformation
Whether it’s business transformation or architecture modernization, to differentiate themselves, companies are constantly evolving to create new value through product and process innovation, new business models that address constraints from new regulations, or an under served market, and as a result, help capture a larger share of the wallet. To succeed, enterprises need the ability to reorganize themselves, adapt business processes to new operating and business models, simplify and streamline IT systems to be more agile, and be able to introduce changes in a controlled manner.
3. Operational efficiency
Operational efficiency or operationalizing business analytics needs to become increasingly inserted into daily business functions, not just the decision-making of the enterprise. They need to facilitate the delivery of key financial measures, related hierarchies, mappings, and reporting attributes. The more “operationalized” they can become the more effective they can be with predictive and prescriptive around the business metrics. By matching the right data to the right people you will get maximum value for your data and it lays the foundation for advanced analytics and AI/ML initiatives.
Where do we start? – The Enterprise Data Dilemma
Often the biggest hurdle is the first one, getting started. It goes without saying, but you need buy in from the top down. This has to be an initiative with firm goals and criteria for success that everyone is working towards. You need key people committed and a committee to drive it. Define the scope early on. Do you want (or need) to govern ALL of your data?
The image below outlines the typical process for implementing a Data Governance framework. At each step in the process, the business and IT will need to come together and agree on a number of key items. Is Data Quality really an IT issue? How do we define what quality data is? Is Cust_ID in one database the same as CustomerID in another? Who ‘owns’ this data? How did the data change along the way to create my report? How do we make best use of this data set?
We already have Data Governance, don’t we?
Most companies have some type of Data Governance in place. Whether it be tracking who has access to certain data, how to onboard new data sets, common terms for data types etc. But often this information is in disparate places, not updated regularly and isn’t bound to a particular framework or standard. The below image outlines the most common issues with patched together Data Governance programs.
Common user stories related to Data Governance issues
Everyone who values data needs to be involved
Below are some of the most common roles within a Data Governance program. These vary depending on each company and Data Governance maturity level.
Data Governance empowers teams and individuals to do more, with confidence. Data is everyone’s business.
So what could it look like if implemented correctly?
A common problem with data within the enterprise is getting access to quality data and in a timely manner. This affects both the business (not getting access to the data) and IT (getting inundated with data requests that are hard to decipher). Below is a sample workflow to show how Data Governance can speed up the process and at the same time govern access. This may be a business unit getting access to the data they need to run analytics or create a report to make business decisions.
Change Request/Issue Management
In addition to the above data access workflow, efficient change and issue management are also important in keeping the flow of quality data moving. Data is constantly changing. New or changed fields (e.g. rename a CRM field), new definitions, new applications, new databases etc. Each time a change happens it needs to be managed through an efficient process. Below is an example of a new HR SaaS being implemented in a company (e.g. Workday). As the application and associated data is brought into the company and the HR team wants to make use of the data, there is a number of steps that needs to be followed before they can use it. If the process is held up at any of the points below it can have a negative knock-on effect. Add this to an already busy queue of work and the time taken to reach business goals will be pushed back and may start to affect critical business functions.
What software or frameworks are available that can make the process more manageable and increase the chances of success?
There is no right or wrong way to implement a Data Governance program. Every company is different in it’s own way. At the same time, there is a lot of similarities between them and the way data needs to be managed. There is a number of tools and frameworks that have identified this and can make the whole process much easier. DAMA (The Global Data Management Community) has a comprehensive framework outlined in their DAMA-DMBOK: Data Management Body of Knowledge and another popular framework is MIKE 2.0 Method for an Integrated Knowledge Environment. These are often considered the industry standard. There are a number of software vendors (both in-house and SaaS) that provide solutions targeted towards making Data Governance easier to implement and manage for the enterprise. These include Erwin, Collibra and Informatica. Even Microsoft Azure and AWS cloud providers have some Data Governance functionality built-in, or offer tools to assist their customers.
The difference between these various offerings is usually the depth of features the vendor has and whether they are targeted towards the business or IT. Typically, products targeted towards the business are better received because they have a higher rate of adoption and keep the business users engaged. It’s recommended that companies should conduct a vendor assessment when looking to implement a solution to ensure it fits their needs. The key thing to remember is, Data Governance is not a project, it’s a practice.
If you would like to talk to one of our consultants about performing a data governance gap analysis for your organisation, assistance with a vendor assessment or anything data governance related, please head to our contact page.