Talk about the ten mistakes often made in implementing data governance

One 、​ Failure to address data culture issues

1. Error description

The biggest mistake I have ever seen is that companies do not include cultural change as part of their data governance initiatives . up to now , This error is the biggest and most common error , It may eventually lead to the complete failure of the data governance plan . A common situation is , People have designed a great framework , Ideal for their organization , But it did not succeed , Because it has not been properly implemented , Because they didn't solve the problem of cultural change .

2. Consequences affect

The result is business users 、 stakeholders , They just feel that data governance is for them , Not for them or with them . under these circumstances , They tend to do as little as they are asked to do , Even if they get away with it , Don't even do anything . In short , If we do not solve the problem of cultural change , You can't start managing data as an asset , And realize its value . It is necessary to bring in the business personnel , Take them to carry out data governance work together .

3. How to avoid

First , The simplest thing is to apply some really good change management techniques , If you are not proficient in these techniques , I'm sure someone in your organization is proficient in , But at the end of the day , This requires high-quality communication with all business stakeholders . This will allow different stakeholder groups to communicate about their roles in the implementation of data governance , And ensure that each role in the data governance framework ( Such as data owner or data administrator ) Good training . It is very important to bring these people to your team , Because if you don't solve the problem of cultural change , Your data governance plan will never deliver the benefits you want

 

Two . Data governance is driven by IT Driven

1. Error description

The key to the success of data governance is to let stakeholders have ownership of their data , And play a leading role in the data governance plan . When I perform data governance checks for troubled companies , Usually by IT Department leader data governance plan . It's always the best intention . Although it doesn't have data , But they understand the impact of incorrectly managing data , So they tend to be the first in any organization to realize the need for proper data governance . Enterprises often let IT To handle data governance , Because they confuse infrastructure with data . If your organization still thinks IT Own data , Then allocate IT It seems logical to run a data governance plan . However ,IT Leading data governance initiatives can be fraught with problems . True data governance only happens when the enterprise owns data ownership , and IT Leading projects make this even more difficult .

2. Consequences affect

In my experience ,IT Leaders' plans focus too much on tools that do things like cleaning up data . It's understandable , Because the company tends to sell tools from IT Get advice from suppliers . The problem lies in , Unless the enterprise changes the way it captures data at the entry point , Otherwise, the quality of data will never improve .

3. How to avoid

in any case , Enterprises need to recognize the need to have their own data , And be responsible for the data governance plan . This is usually easier said than done , An independent expert from outside the organization may be required to act as a catalyst . Outsiders can facilitate high-level discussions between different business units . This will help companies understand the benefits , And increase their desire to take the initiative . This is, of course, an ideal scenario , But at least , The business needs to have policies and processes related to how the business creates and manages data .

 

3、 ... and 、 Do not understand the maturity of the organization's data governance

1. Error description

This mistake is about not knowing the maturity of the organization in data management , More specifically , Maturity in data governance . This does involve a basic problem : Are you ready for data governance ? occasionally , An organization is not ready to implement a data governance plan . Even if the organization is ready , It may not be mature enough , Not enough to achieve their ultimate goal . The bottom line is , Unless your organization can think about data in the right way , Otherwise, comprehensive data governance initiatives are likely to fail , Because the necessary communication and education can either confuse the public , Or be ignored .

2. Consequences affect

You need to know where you start , So you can plan your journey . If you don't understand how mature your organization is in data governance , You may try to introduce something that your organization is not prepared for or does not need . When there is a lack of clear understanding of the maturity of data governance within your organization , It is quite certain that , Communications will be adversely affected . Your communication with the program should send the right message to the right people at the right time . If maturity is not clear , It will be difficult to deliver a hit the nail on the head message , And you may receive negative reactions from those who are critical to the ultimate success of your plan .

3. How to avoid it

Obviously , The first step is to assess the current level of maturity in data governance . This is not necessarily an expensive job , Because there are a lot of free resources available . The second way to avoid this mistake is to be clear about what you want to achieve through data governance . If you know your goals , It is easier to understand what stakeholders need to hear in order to welcome data governance . Once you have defined your organization's reasons for data governance , Include how stakeholders will benefit from it , I suggest you create a strategy document . This will ensure that everyone involved in your plan clearly understands what the plan's objectives are , And how it will positively affect their organization , This will undoubtedly stimulate interest in communication .

 

Four 、 Treat data governance as a project

1. Error description

This common mistake is easy to make , Because it seems logical to treat the implementation of data governance as any other project . Engaging stakeholders is critical to the successful implementation and support of the data governance plan . However , This is not something that can be reduced to a task list . Once you get stakeholder recognition , You face a bigger challenge , change front , Behavior , Even the culture of data management . I hope you understand that this requires something more complex than traditional project management .

2. Consequences affect

When a data governance plan is led as a project , It seems that progress has been made with the completion of the task . However , Except for human change , Otherwise there will be no substantial change . To change behavior 、 Attitude and culture , You must win hearts and minds . When the success of the plan is measured by the deliverables on the checklist , This is almost always overlooked . If you don't involve stakeholders , It will be difficult for you to integrate your data governance framework , So as to make it a normal business . Without the support of stakeholders , Enterprises will eventually return to the way they used to manage data . In short , The whole plan will be a complete waste of time and money , Subsequent attempts to re implement data governance will be resisted by stakeholders , Because they think it's a waste of time .

3. How to avoid

The secret is to implement the plan as a change plan for different workflow . Some people will deal with difficult tasks , Others will deal with behavioral issues . This means that you may need a team with different skills . for example , You will need a good facilitator , You may find him outside the organization . You need a soft skills trainer , And experts in communication and influence . One cannot have all these skills . You also need a leader who is good at coordination . Your change plan should outline the transition from the current situation to the normal operation of data governance . You should also apply best practices for organizational change management , And assign a realistic time frame . Last , When implementing data governance , Please do not underestimate the importance of soft skills . Communication and impact are critical to the successful implementation of the data governance framework .

 

5、 ... and 、 Data governance is not aligned with strategy

1. Error description

Inconsistent with strategy is a fairly common mistake , Especially if the business is not fully involved in the data governance plan . The strategic objectives of the enterprise will promote the daily management of the enterprise . Unless stakeholders see how data governance will help them achieve their strategic goals , Otherwise, it is unlikely to have any relevance in gaining their recognition and ultimately using their influence to promote cultural change .

2. Consequences affect

If you can't show how your initiative will help your organization achieve its overall strategy , Then you may make your stakeholders think it is a waste of time . If that happens , They will probably do their best to cancel or shelve your plan . They always focus on what they think is important to achieve strategic goals , And will resist anything they think doesn't matter . If you encounter major stakeholder resistance , And it is generally believed that data governance plans do not add any real value , So in the end , Your plan may face a serious risk of losing money . It is sad , This is not exaggeration , I often see this happen . I learned a painful lesson in the early days of implementing data governance .

3. How to avoid

The key to avoiding this mistake is to understand why the data governance plan should be implemented , And how it helps organizations achieve their strategic goals . Be able to express this clearly , To ensure continued funding and support for the initiative is critical . In the case of business changes , This helps to get a clear result , You need to be able to communicate this clearly and concisely to the rest of the business . They want to know how this plan will help them achieve their department's goals , And how much effort is needed . Understanding where your organization is from the perspective of the data governance maturity model will help you determine what you should expect to achieve . Once you have identified the reason and direction for data governance , You can better plan the path to data governance , And milestones , To measure progress .

 

6、 ... and 、 Do not understand the data architecture

1. Error description

You need a high-level understanding of how to save and manage data in your organization . It does not need to be too detailed , And as long as you start with a broad understanding , You can add details when it makes sense . However , If you can't do that , This means that you are always looking for solutions to the symptoms of lack of data governance , Instead of finding the root cause of the data problem .

2. Consequences affect

If you don't understand the relationship between data and systems , If the data stored in the system changes , Even for the right reasons , It will also have a negative impact . You will address symptoms related to data problems , Instead of really finding the root cause . When you make small changes in a particular area , There will also be downstream consequences , Because no one understands what data is used for and how to use it , This can lead to many unexpected effects . This in turn can lead to a bad reputation for your data governance plan .

3. How to avoid

The obvious way to avoid this mistake is to define the data schema before you begin . You can do this in stages , So you can start with a high-level overview of your organization's data landscape . Before making any changes , You should also do some form of impact analysis . Always remember , Implementing a data governance framework is too important , It cannot be solved at one time , And it's too big , You can't understand everything . The key is to identify specific stages , Prioritize them , And study them in more detail throughout the whole phase . If you start by defining the highest concept level , Then define the details down , You can deal with important aspects , Instead of trying to record everything at once . Sometimes no documentation is required , This will save you valuable time . I strongly recommend that you consider using a conceptual data model , This is both a way to document the data architecture , It is also a way to communicate data governance to your enterprise .

 

7、 ... and 、 Failed to embed data governance framework

1. Error description

Another common mistake I often see is that there is no embedded data governance framework . This is related to the mistake of managing data governance as a project . Unless you effectively integrate the data governance framework into your organization , Otherwise, any benefit will be short-lived .

If the data governance framework is not an integral part of your business , Then the business will slowly but surely return to its previous behavior .

2. Consequences affect

If your organization does not have an embedded data governance framework , You are less likely to achieve long-term changes in the way people manage data . Although you may get some quick wins , But if there is no data governance framework to support change , It may take many attempts to make the change last . Organizations often make multiple attempts to embed data frameworks in their organizations , This not only annoys stakeholders , It also hinders success . As you try further , It is becoming more and more difficult to achieve stakeholder cooperation , Because they will start to think that initiatives are just a waste of time .

3. How to avoid

Roles and responsibilities are a key part of the data governance framework . If no one is responsible for embedding the framework , Then probably no one will do it ! Make sure your roles and responsibilities are properly defined , And you have found the right people for each role .

If you don't explain to them what you want them to do and what they should do , So it doesn't make sense to define roles and responsibilities and then find someone to fill them . It sounds obvious , But be sure to document your process , And provide adequate guidance , So that everyone knows what they should do . Implementation is the hardest part of any data governance plan . relatively speaking , Writing framework documents 、 It's easy to draft roles and responsibilities and draw a nice flow chart . However , You really need to go out , Let it happen . This is often where data governance plans encounter real problems . You may also need leadership support , To ensure that your data governance framework works . This can be assigned to a person called a data Governance Manager , Or it can even be assigned to the entire team .

 

8、 ... and 、 Take a disruptive approach

1. Error description

I have tried subversive methods , But there are still scars that remind me that this is a bad idea ! By subversive approach, I mean trying a major plan to implement everything related to the data governance framework . If you are a business user , Carry out your daily work , If everything related to your job changes dramatically at once , How would you feel ? Believe in , It's not a good feeling , And it's stressful . This approach is unlikely to lead to long-term success .

2. Consequences affect

“ Subversive ” The result of the method is , The initial plan is probably too big to start . perhaps , Business users will be too focused on their daily work , So by loading their plates with too many tasks , You will find yourself struggling with other priorities on their agenda . In short , It will be a hard struggle to get people to take time to start work .“ Subversive ” Methods quickly turn data governance into a major project that undoubtedly requires a lot of time and resources . Make it sound more frightening than it really is , This may prevent you from getting the resources and funds you need to achieve higher-level strategic goals . please remember , You shouldn't do data governance just because someone told you it was a good idea . You should do data governance , To help your organization achieve its strategic goals .

3. How to avoid

When it comes to implementation , You can avoid this mistake by taking a structured approach . When figuring out why you want data governance and what you want it to accomplish for your organization , Please step back , Follow an organized approach . then , You can try to execute your plan in manageable blocks . Never underestimate the time it will take . Once you have effectively defined your data governance strategy , And align it with your organizational strategy , You can well define your phases , This should be relevant to your organization's priorities .

 

Nine 、 Terms and methods of compliance

1. Error description

If the pressure to implement data governance comes from regulators , that , Enterprises are likely to consider meeting the absolute minimum requirements to the satisfaction of regulators . This is a big mistake , Because in the long run , These organizations will eventually do more than they did to properly implement data governance in the first place . They also missed out on all the business benefits of improving data management practices .

2. Consequences affect

The checkbox approach to data governance is usually task centric , Completely ignoring the people involved . They make a list of things that need to be done , And threaten when the task is not completed . therefore , People go through the motions because they have to , They don't see the real benefits of daily work . therefore , Embedding your data governance framework in your organization will be difficult , You will always chase people , To make sure they follow the rules . Regulators are notorious for changing objectives , therefore , If you don't embed data governance in your organization , So every time they change regulations and update checklists , You can all go back to the starting point , This means executing a new checklist .

3. How to avoid

from the beginning , Consider using regulatory requirements as a driver , But don't limit the scope of action to a minimum . Think about how you can meet the rules , And get some commercial benefits . If you adopt good data governance principles , Then you should be able to follow whatever they say , And it will just be a by-product of what you are already doing . In the worst case , You will have to make some minor adjustments , Not from the beginning . Prepare the basic data governance framework , And outline the scope to all data owners at the same time . This is not just about data owners who need to meet regulatory requirements —— First, get the entire organization to support the data governance initiative . Get them used to the idea , And emphasize that if they accept the change , The business interests they can expect .

 

Ten 、 Think that tools can achieve data governance

1. Error description

There are many tools on the market that can really help data governance . Existing tools can help organizations achieve 、 Manage and support data governance , Make it an integral part of the business . however , Don't mistakenly think that these tools are the most important to achieve good data governance .

2. Consequences affect

If the entire data governance plan revolves around one tool , Then the enterprise is unlikely to participate , Because they mistakenly think that this tool will do all the work for them . You still need to involve stakeholders in the process , Because without their support , The whole plan is likely to fail . Unless the entire business has signed a data governance agreement at the beginning , Otherwise the tool will not work . Tools do not relieve them of any responsibility . contrary , Tools should be positioned as tools that make it easier for people to perform their data governance responsibilities . Final , It is not the tools that cause the data governance plan to hit a wall . When too much attention is focused on tools , When too little attention is focused on getting stakeholder purchases and change management , The plan failed .

3. How to avoid

The answer is a structured approach to data governance . Before you start thinking about potential tools , Make sure you fully understand what you are doing and why you are doing it . In order to make the most of the tools , You should have a clear idea of what you will do with the tools . First draft your data governance framework , As part of the practice , Consider whether your organization is mature enough to understand data governance . in fact , It may be too early to start thinking about tools . Do all the things we have mentioned , So that the business can participate in the initiative , If you decide to use a tool , Keep in mind that these tools do not avoid any of your responsibilities in achieving organizational change .