5 Harvard-Recommended Ways to Improve Data Management for Your Business


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In order to improve their data management, businesses must craft better systems and approaches. That starts with clarifying management responsibilities for everyone who touches data in any way, across the entire company. 

Here are five ways to improve data management for your business as recommended by Harvard Business Review:

Introduce Data-Specific Responsibilities

Real data action is mostly carried out by everyday individuals whose job descriptions do not include the word "data." They develop and interpret the material, and utilise the material to appease consumers and regulators. They monitor inventories and finances, make plans and choices, and so on. However, they are often overlooked throughout the planning process. 

The most crucial thing businesses can do to speed up their data projects is to include these employees.

Companies must define the workers’ responsibilities and duties as data customers, data scientists, data contributors and so on so forth. This is done in order to realise the full potential of data management. The first action that leaders should take is to prioritise these duties and normal people.

Introduce Infrastructure To Be Productive Despite Silos

Like it or not, work silos aren’t going anywhere for now. Instead, to compete with them, businesses must create an infrastructure that can transmit and coordinate the orderly flow of a lot of data. Enterprises need to define and measure how data is generated and how it flows from one location to another and how it is evaluated.

They need to create a “data science bridge” to facilitate communication between corporate teams and world-class data science institutions. It is challenging for employees to collaborate across silos and for data scientists to interpret the company's data. By identifying roughly 150 fundamental concepts that unite the organisation and settling on shared definitions, businesses may advance significantly.

Don’t Depend On Your IT Team For Data Management

Too many businesses mistakenly depend on their IT teams with primary responsibility for data. Technology and data are separate types of assets. However, the majority of data is neither generated nor utilised by IT. Companies should allow the IT team to work on the technology so that it may develop infrastructure capabilities, automate clear procedures, and eventually pay off technical debt.

Train And Build Professional Data Teams

Businesses require small, competent data teams with in-depth knowledge of a variety of subjects, including data quality, data science, metadata management, privacy, and security. These data teams should spend half of their time teaching and assisting normal individuals so they can fill the jobs and carry out the duties mentioned above.

Professional data teams must also set aside a portion of their time for specialised tasks including analysing privacy laws, creating data models, and overseeing particularly challenging data science activities.

Involve Senior Management

In innumerable situations in the past, excellent data science and data quality techniques have proved their mettle, resolving challenging issues, producing fresh consumer insights, and lowering costs. However, the failure rate of data science initiatives continues to be alarmingly high. Senior leadership is desperately needed for data programmes to assist tackle these issues.

The top leaders do wish to act and do the right thing, but they are unsure of what those actions should be. In their defence, they are confronted with an avalanche of options with regard to choosing a course of action which threaten severe repercussions if disregarded. 

Two Tips for Senior Management:

Very often, companies have amazing ideas in the data realm but far too frequently, they are unable to connect with each other, leaving business issues unresolved and individuals with brilliant ideas dejected. Senior leaders are uniquely suited to link the two.

Gradually develop the necessary human resources. Hire a fantastic Chief Data Officer who should have the courage to stand on the front lines of change every day and the patience to think long-term and not be sidetracked by small squabbles.


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