We’ve been using Microsoft Copilot here at Smile IT in recent months, and it’s given us solid insights into how AI can improve workflows and boost productivity. This handy chatbot has proved to be a massive time saver, earning positive plaudits from across the team.
A powerful takeaway from implementing Copilot is that without good data, AI falters. It needs to be fed with well-organised, up-to-date and accurate data to realise its full potential. It’s not unlike a management team – good data helps them make good decisions and fuels insights. It’s key to gaining a competitive advantage and keeping up with the rapidly evolving business environment.
Good data is well-managed data, from the collection phase through to storage and backup. It’s organised, consistent and accessible. Sounds easy, right? In today’s information age though, the sheer volume of data an organisation takes care of can be overwhelming. This is where a solid data management system is essential. Today we’ll look at data management and provide a guide to improve your company’s data landscape.
What is Data Management?
Data management is the collecting, storing, and processing of data in a secure and sustainable way. It includes the practices and tools that ensure the availability, reliability, and timeliness of the data through its lifecycle. It facilitates the processing of the raw data into meaningful information that can fuel AI and also drive informed decision-making and planning.
Harnessing the Data Lifecycle
Understanding the data lifecycle is important to learning how to control and manage your data. Michael de Ridder is a senior software engineer at YouTube who explains that there are six steps in the lifecycle of any piece of data. Managing these steps correctly preserves the integrity of your data and keeps it organised.
The steps are:
- Data Creation: This is the process of capture and acquisition of data. The data types collected need to be defined, as well as their usage details and sensitivity level.
- Data Storage: As well as having robust data security measures in place, you need to store your data so that it cannot be altered accidentally. Compliance with local data privacy laws is essential too, and data recovery plans need to be in place in the event of a failure.
- Data Use: Correct implementation of steps 1 and 2 should help you effectively map out data usage to employee’s roles. It’s essential to have strong permissions in place that are regularly reviewed, particularly if you are embarking on AI solutions such as Copilot.
- Data Sharing: This is always going to happen, whether it’s between employees, colleagues, friends or customers. A poorly managed data lifecycle will be extremely vulnerable at this point – it’s essential that data sharing is done through official channels and methods compliant with policy regulations.
- Data Archiving: Data reaches a point where it’s not needed on a day-to-day basis by your system or employees, but still may be need on an ad hoc basis. At this point, archiving the data is the next step to take. It’s still available if required but won’t get in the way of accessing more current data.
- Data Destruction: When it gets to the point where data is no longer needed, the archives are destroyed. This needs to comply with your own internal policies and applicable local or international laws.
Poor Data Management Side Effects
Haphazard, incomplete and disorganised data has further reaching effects than poor AI outcomes. The negative effects on your business can be difficult to deal with, including:
Compliance Issues
Data is the lifeblood of modern businesses, and it’s your responsibility to take care of it in compliance with the stringent rules and regulations surrounding data privacy. Heavy fines and damage to your reputation are consequences you’d rather avoid.
Vulnerability to Cyber Threats
If your data is all over the place, chances are high that your organisation is more vulnerable to cyber-attacks. There’s a lot at stake here, from your clients’ privacy to protecting your systems and processes. Unauthorised access or breaches will have a huge negative impact on your business.
Productivity Problems
If you’re relying on manual processes to seek out data that nobody can locate you’re wasting time and resources. Your ability to operate efficiently disappears.
Missed Opportunities
A well-informed and agile business is in a better position to outsmart their competitors in identifying potential opportunities that could prove profitable.
Poor Decisions
Inaccurate data leads to flawed insights, which can seriously jeopardise your organisational decision-making. Imagine making budgeting decisions around incorrect sales figures. It’s easy to envisage the knock-on effects that will result.
Principles to Managing Data Effectively
Your data management strategy should adhere to a set of solid principles that guide each stage of the lifecycle outlined above. These could include:
- Data Governance: This is the set of processes, policies and tools that safeguard the quality of data through its lifecycle. It should establish clear ownership and accountability for data, defining the roles and responsibilities for creation, storage, access, and maintenance.
- Data Quality: Data quality measures will help keep it accurate, consistent, and complete. Cleanse and review data regularly to remove errors and inconsistencies.
- Data Standardization: Putting in place formatting and storage standards for your data will help maintain consistency across the departments and systems.
- Data Security: You don’t want your data falling into the wrong hands, so safeguard it with strong security measures to prevent unauthorized access and breaches. Encryption, access controls, and regular security audits are critical.
- Data Accessibility: Data should be accessible by authorised users who need it for their jobs. Users should have the tools and knowledge to locate and use data they need, which will help streamline processes.
Advantages of Managing Your Data
Managing your data correctly through every stage of its lifecycle will have positive follow-on effects rippling through your organisation. These essentially reverse the negative side effects we spoke about above and include:
- Enhanced Operational Efficiency: Improved data access helps your team work better and faster, with resources being allocated more effectively.
- Data-Driven Decision Making: Accurate, timely data empowers informed decision-making at all levels in a business.
- Improved Customer Experience: On-point customer data helps you understand your customer better. This means better marketing campaigns, targeted offerings and improved customer service interactions.
- Reducing Compliance Issues: Effective data management within secure perimeters minimises potential fines and legal risks.
- Unleashing Data Analytics: Data analytics, particularly those powered by AI, are revolutionising insights into customer behaviour, operational performance and market trends. This can only mean positive things for your business.
Questions About Getting Your Organisation AI Ready?
Data is an important cog in the success of your business – manage it well and you’re on your way to improved decision-making and enhanced operational efficiency. Drop the ball and it could spell trouble in the form of compliance issues, productivity problems and missed vital opportunities.
Well-managed data is also key to fully leveraging the power of AI. If you’re looking to implement and enjoy AI in your organisation, you need an organised set of data for it to learn from. Hopefully the above has given you an idea of what you need to do to achieve that. We’re always here to help if you have any questions about getting your organisation AI ready. Give us a ring on 1300 766 720 or get in touch here.
When he’s not writing tech articles or turning IT startups into established and consistent managed service providers, Peter Drummond can be found kitesurfing on the Gold Coast or hanging out with his family!