As your company’s connected and online business activities increase, so does the data generated by these interactions.
But, how are you using this data? Are you harnessing the insights it imparts to increase sales or launch new products? If not, why not? This post gives you 5 steps on how to improve your data management efforts.
A study by the Global Association of Risk Professionals and SAS revealed that fewer than half of the managers surveyed said their financial institution’s expertise on data management was adequate or strong.
If you’re not quite there yet, it would appear on this basis that you’re not alone.
This lack of expertise is widespread across many sectors and industries, and it could be depriving you of the opportunity to capitalize on the data you possess.
In addition, it could put you in risk of neglecting the protection of data, risking your brand reputation and regulatory sanctions, such as the ones listed in the General Data Protection Regulation (GDPR) where fines run up to 4% of annual turnover.
If you want a structured guide, our ebook: Get More Value from AI with MDM shows how to align your data management efforts with AI-led insight delivery.
If you’re in the process of examining your organization’s data management position, these five steps will help you improve your data management processes to the point of profitable impact.
5 steps to improve your data management process and plan
1) Take business ownership of data management
Many organizations are now employing Chief Data Officers (CDOs) to help them manage data governance and the use of data as a business asset. And, with good reason: a survey by Forrester Research ("Top Performers Appoint Chief Data Officers") found organizations with a CDO were 70% more likely to reduce risk and better ensure compliance than an organization without a CDO.
But still, a considerable number of enterprises — 60.6% according to a survey from NewVantage Partners ("The Chief Data Officer Dilemma") — identify others as the point of primary responsibility for data strategy and results, or claim no single point of accountability.
Often the “others” are from operational IT and not from the business. This can often lead to an unclear viewpoint on how the organizations data helps realize strategic value for the business.
So, the first step is to place data management responsibility where it makes the most sense. By re-shaping your business approach to data strategy, and by appointing individuals to take responsibility for implementing and governing it, you begin to take ownership of your data.
You’ll now have accountability, and with this comes procedures and processes to help govern your usage of data to uncover intelligence and insights from it, allowing you to tap into its value in order to use it as a key asset for delivering business success.
2) Connect data sources
How do you collect, process, store and consume data across your business? The likelihood is that as your organization has grown, data management has become decentralized with no real management strategy in place to support it, and, to be frank, it’s become a bit of a nightmare to manage.
Disparate systems need to be connected and data architecture standardized. Once you’ve achieved this, it becomes easier to take business ownership of data management, enabling you to align your use of data with your business strategy.
Organizations working with fragmented legacy systems are experiencing insurmountable gaps when they try to retrieve and utilise their data.
They’re also risking non-compliance with new regulations as they can’t provide the transparency needed to show how their information was acquired and where it will ultimately be used.
You can choose to link your existing systems, replace them with a new one, or opt for a combination. The essential thing is that your data system(s) primarily support your business strategy.
Secondly, they should provide data coherence and visibility, as well as deduplication, and use archive technologies to allow you to protect more, while storing only what you need. It also needs to be flexible enough to support future growth.
3) Manage your metadata
Metadata provides information on your primary data such as when it was acquired, created or revised — plus its location and how it’s formatted.
Managing your metadata and creating a consistent business information infrastructure is vital when it comes to referencing, accessing and consuming business data. Many organizations are missing basic facts including who owns specific information, how important that information is and how relevant it is to the business.
Managing your metadata will help you map and classify information and assess its value so you can protect and prioritise data that’s valuable to you.
4) Plan how to deliver your data
Once your data is under control, how can you format and deliver it for optimum use across the business? This is particularly important if your company operates multiple ERP and CRM technologies and ecommerce platforms.
Data delivery is about putting relevant information into the right systems and into the hands of the right people in the right way. As the GDPR and other data privacy regulations require, accurate reporting is essential. Businesses will be required to provide detailed information on the acquisition, management and protection of the data they possess.
You need to have systems in place that enable users to take intelligent business decisions based on data-driven insight, for instance by using customer data reports to enhance existing products and create new ones geared towards an identified customer need or having a sustainability data process management in place to help you reach and measure your organizational goals.
5) Adopt consistent data governance policies
A data governance operating model will help bring roles, policies and processes together to help your organization guide and enable ownership, accountability and performance of data. Many organizations fall into the trap of thinking technology alone brings successful data governance.
However, data governance is much more about people — in terms of organizational change management than it is about the technology.
Of course technology can help enable data governance in terms of providing analytics, insights etc., but only when a robust and flexible data governance operating model has been defined and adopted into the business.
This will ensure that data is recognized as a valuable, strategic asset and its accountability is clearly defined and implemented to follow internal and external regulations throughout the data lifecycle.
Metrics for measuring your data management success
An important aspect of ensuring continuous improvement and achieving your business goals is measuring the success of the data management initiatives.
Generally, monitoring key performance indicators (KPIs) and other essential business metrics can help you assess, revamp or double down on your current data management strategy.
A few key metrics to consider include:
- Data quality & accuracy: Data quality issues can distort the numbers and have a major impact on all facets of your business. Regular audits and validation checks of your data sets are necessary to ensure effective data management.
- Data usage rates: Track the frequency of data access and usage to improve overall business intelligence and enhance decision-making.
- Compliance: Conduct regular audits on data collection, data security methods and how data assets are used to ensure they comply with regulations like GDPR and others.
- Business impact metrics: Your data governance framework and its effect on business processes and outcomes (i.e., improved customer experience, increased revenue, etc.) should be measured regularly.
By focusing on these core metrics, your company’s data can help you identify areas in need of improvement and ensure your data management initiatives deliver clear and lasting results.
The Importance of creating a data culture
Collecting, maintaining, and effectively using the types of data at your disposal requires more than high-quality data management software. As such, fostering a data-driven organization from the ground up can ensure stakeholders use the right data, at the right time, to get the best outcomes, consistently.
This requires a mindset shift as well as the implementation of data management best practices that promote data as a critical business asset.
- Keep data at the forefront: Encourage employees and other relevant parties to incorporate data into every decision and business process.
- Management strategies: Clearly communicate the importance and benefit of data, which may require a shift in management strategy.
- Training programs: Improve data literacy and skills among employees by providing comprehensive training.
- Encourage automation & proper data management: Use a data management platform to automate and streamline data processes while emphasizing data security, quality and usefulness.
Not only can these strategies help create a culture that recognizes the importance of data as a critical asset, but they can also help leverage your company's data to obtain a competitive advantage, lower costs, increase customer retention and so much more.
EBOOK
Achieving perfection in data governance
Summing up how to plan and improve your data management
Although data management is an evolving process for many organizations, reaching this stage of being able to apply company-wide policies around data feels like quite an achievement in order to improve your data management.
And, the pressure is on for businesses to reach this milestone sooner rather than later—if they’re to optimize their business and avoid penalties for the mishandling of data.
EXPLORE
Multidomain Master Data Management
