According to the DATAVERSITY® Trends in Data Management Report, data management evolves in stages across the company. One or a few teams take the lead in Data Management, ensuring that projects or products have successful data knowledge, security, access, and value. The beneficial practises then stick with that team or project, while others are left out of the loop. This issue appears to be getting worse.
According to a Harvard Business Review article, the percentage of companies claiming to be data-driven, that is, using data as important evidence to assist inform and impact strategy, has decreased in each of the last three years since 2017, indicating inadequate Data Management. To be data-driven throughout and to take advantage of new technologies such as AI, businesses must have strong data management. The faster good Data Management spreads, the more data-driven an organisation becomes.
There are numerous articles that provide general data management tips and tactics. However, coordinating other teams with effective Data Management activities in the past or present can be difficult. First, leaders aren’t always aware of successful projects in their organisations, and not all of their staff are interested in learning about them. Consider the case of Kodak. Robert Hills and Sasson collaborated to create the digital camera. This research and its data were rejected by Kodak’s marketing department, which contributed to the company’s bankruptcy. Second, rules such as the General Data Protection Regulation (GDPR) make team members wary of sharing project-specific data with other teams or projects. Finally, data silos make it difficult to transfer effective Data Management methods from one team to another. Executives who are dealing with a combination of these issues may find it difficult to transfer strong Data Management from one project to another.
Investing in a Chief Data Officer to Lead Data Management
To begin, consider appointing a Chief Data Officer (CDO) to oversee data management across the entire organisation, particularly in a firm. A CDO has a broad view of a company’s data, including how inputs and outputs flow between different corporate teams and departments. This necessitates an enterprise-wide focus. Data Management gets perplexing without an executive in this position. As an example. Because their Data Management tasks overlap, IT and business don’t know who needs to clear up bad data. “A business strategist, counsellor, Data Quality steward, and Data Management ambassador” are all positions that need to be filled. That person must be a senior executive.
Data Management has previously been controlled by the Chief Information Officer (CIO), as some firms view it as primarily a technical solution. Good Data Management, on the other hand, encompasses more than simply technical solutions; it also includes people, activities, and a variety of procedures. A CEMEX case study indicates that good data management necessitates good business teams as well.
In addition, according to Mark Samuels of ZDNet, “the CIO remains the go-to executive for enterprise IT challenges.” A CDO, on the other hand, possesses strong communication and Data Strategy design skills to persuade teams and individuals of all types to use digital technologies and collaborate while sharing knowledge. CIOs and CDOs may collaborate, but they do not have the same responsibilities.
Similarly, increasing the job of a Chief Analytics Operator (CAO) to supervise Data Management is insufficient. A CAO is a person that converts data-driven insights into data-driven actions, focusing on how data is used. A CDO considers not only how data is used, but also how data is maintained and governed. Successful Data Management teams consider all three of these factors and benefit from the presence of a CDO. A CDO is a resource dedicated to good Data Management across the organisation, which includes ensuring that teams can learn from one another’s best practises.
Identifying Successful Data Management Teams Skilled CDOs understand how to develop a relevant Data Plan that is in line with the company strategy. These CEOs employ a Data Strategy to make a firm more competitive and cohesive, all while adhering to a unified Data Management goal. Data Strategy considers the entire firm, casting a wide net over all of the Data Management team’s accomplishments. The CEMEX case study, for example, demonstrates how “an end-to-end consumer Data Strategy” aids in seeing the “full company picture – from attracting new customers through social media, digital campaigns, and other channels to keeping them by improving the customer experience.” CDOs can provide templates of what excellent Data Management procedures look like from this perspective.
CDOs should hunt for strong examples throughout the organisation after discovering Data Management accomplishments. Transparency can be achieved by project retrospectives, which may reveal Data Management accomplishments for a few data points. An enterprise-wide capability maturity model will not only give organisational Data Management capabilities, but will also uncover Data Management triumphs if customised to do so.
A case study from the State of Arizona demonstrates how the CMMI Institute’s capability maturity model was used to evaluate a decentralised departmental network in Data Management. As a result of this assessment, a Data Steward training course for state agency employees was developed to teach them how to effectively manage their data. Arizona also established a state-wide Data Governance programme as a result of the CMMI evaluation, putting what they had learnt into practise.
Providing Authority to Data Governance
Data Governance, defined as “a collection of procedures and activities that serve to assure the formal management of data assets within an organisation,” must be spread and supported across an organisation to achieve successful Data Management.
“Data Governance” “coordinates activities to ensure that they are not only legally compliant, but also that best practises are passed down from one team to the next.” A CDO can step in and guarantee that Data Governance is in place, as well as offer the authority to validate Data Governance policies. Meanwhile, several teams discover a secure environment in which to discuss their data requirements.
Other businesses have profited from Data Governance, which is backed up by an authority. Freddie Mac, for example, was locked in a terrible Data Governance cycle. As a result, even if a team had great success with Data Management, others wouldn’t have to think twice about adopting the techniques. By recruiting “top-down support” to get individuals on board with effective Data Management practises, Freddie Mac was able to turn around Data Governance issues. Departments become more motivated to adopt new Data Management methods as a result of leadership push. It helps to have top-down support, such as from a CDO, when it comes to spreading Data Management triumphs.
Mentorship in Data Management with Successful Teams
A CDO, competent data management, and authority-based data governance may not be sufficient or realistic. Workers may feel adrift as a result of new Data Management processes and procedures. Establishing a Data Management mentorship in a way that is compatible with the business culture aids in the transfer of effective Data Management practises. Mentors may assist promote a positive perspective by listening to Data Management frustrations, validating them, and reframing them to be more data-driven if they have the time.
Mentors would also help mentees with their technical skills, making data systems and solutions less scary. Third, good mentors would recognise Data Management triumphs and highlight them. This kind of assistance would hasten the adoption of a data-driven culture.
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