What are Key Data Management Principles?
Globally renowned futurist Bernard Marr stated ,
“As the world becomes smarter and smarter, data becomes the key to competitive advantage, meaning a company’s ability to compete will increasingly be driven by how well it can leverage data, apply analytics and implement new technologies.
In fact, according to the International Institute for Analytics, by 2020, businesses using data will see $430 billion in productivity benefits over competitors who are not using data.”
Senior management leads the creation of straightforward principles for the acquisition and management of data. These principles are then linked to SMART Outcome Key Results (OKRs) to ensure that your data controls and maintenance allow agile problem solving, decision making, customer analysis and business protection.
The most fundamental Data Management Principles and Data Governance principles are:
Design a strategy and vision on what data is required to keep you in business secure and competitive
Create data accountability by having every piece of information owned by a business domain leader or product owner
Make data a responsibility of everyone
Understand and monitor the lifecycle of data from acquisition to destruction
Benefit from the DevOps and Agile principles of “Right the First Time” to ensure quality, timely, accurate, secure, and relevant data
Create metadata to automate the use, storage and maintenance of data
Design a data management strategy
You generate data every time you perform a task. You acquire data from the Internet, IoT devices, mobile devices, newsfeeds, vendors, social media and more.
How do you know what data is needed and that it is of the quality and type required?
What will you do with the data once available in your business? Senior management can address these concerns using a powerful lean technique called Value Stream Management (VSM).
Using nothing more than a few post-it notes or tools such as Tasktop , leaders can better understand:
How and where data is used
What data is used
What happens to data after use
Where is data redundant or repetitive
Where are the data gaps that block the flow of work
The outcome of a value stream mapping event is a list of iterative steps that will create the vision for mature data management as defined within your master data management framework. Your data management strategy should articulate:
Guardrail governance controls and policies
Archival, storage, and recovery of data policies against global regulatory requirements
Domain or business area rules for data applications, services and products
Role definitions which could include significant vendor partners
Data protection and security, with actions to take if hacked or data infringement occurs
Pilot schemes to ensure that your strategy is viable, flexible and will not negate your agility in the market
Data incident and defect monitoring, alerting and actions
Financial rules for the cost of data acquisition, control and storage
Training on data use and management is required
Your critical Data Management Principles should enable an agile and flexible organization ready for the digital economy by giving each principle an OKR or KPI. You should track these metrics on real-time dashboards for all critical data and as needed for the rest.
Roles in the data management system
Senior management must make it clear that data management, security and safety is the obligation of every employee and vendor partner. Poor data mismanagement should be finable, costing an employee a job offence or a vendor its partnership with you.
Data management is a team effort. The VSM exercises mentioned earlier mapped the flow of data across tasks concerning customer services and products.
