A unified data strategy is the centralization of data management and governance. Multiple data tools and technologies will enable the collection of data from disparate sources and consolidate it within a single source. Adopting a unified data strategy has many wins:

• Data integration and optimization

Data that exists in different formats (e.g: spreadsheets, documents, databases), is stored on-premises or in the cloud, and can be structured or unstructured. When you adopt a unified data strategy, however challenging it may be during the initial stages of data integration due to legacy architectures and the use of multiple vendors, your data is available in one place. With all the data in one place, businesses can analyze and optimize the cost and the technology mix to gain insights, and make informed decisions that can help them stay ahead of the competition.

• IImproved data visibility and workflows

By viewing all data in centralized dashboards, businesses can improve data accuracy, eliminate obsolete data, and determine relevant data requirements. This higher data quality aids in decision making and forecasting, empowering businesses to save costs, minimize expenditures, and maximize revenue. Additionally, a unified data strategy streamlines data management, reduces duplication of effort, and improves collaboration, resulting in more efficient and effective workflows.

• Decision making flexibility

With access to near real-time data and predictive analytics, you’re aware of fluctuations and are more prepared to adopt greater flexibility in your organizations. At times you will be required to respond rapidly to an evolving situation – and this decision-making flexibility is best achieved through a unified data strategy.

• Operational efficiency

Automation solutions are increasingly becoming a component of unified data strategies. Functions such as data collection, cleansing, and compliance are now becoming automated. The benefits of automation are of course well known – they specifically help to eliminate human errors and ensure that data is accurate. Incorporating automation solutions will fast-track certain operational functions so that you can keep your stakeholders updated with the correct information and improve service/delivery standards.

• Better team collaboration

You can reduce having data silos by adopting a unified data strategy. But it does not end there. Promote a data driven culture in your organization to educate team members about the importance of data, provide them with the required access, and train them to handle data responsibly. A team that is well-knowledgeable about organizational data and its uses, and is not hampered by the existence of data silos – is one that will be able to collaborate more effectively.

• Security and compliance

Security and regulatory compliance are integral to any unified data strategy. Regardless of the size of your organization, you are bound to comply with regional data protection regulations. The data tools and technologies that you use must have the capabilities to collect, transfer, and store data securely – and enact policies that will maintain the integrity of your data. The biggest benefit of adopting a unified data strategy is enhanced security, as it allows you to know where all your data is stored and how it’s used. This, in turn, can improve your ability to reach customers while also addressing data protection regulations like GDPR and other security issues.

Unified data strategies in action

Unified data strategies are now deployed in many industries and customized to achieve their specific business needs:

• Retail: Track product inventories and customer behavior over time (i.e., purchase history and preferences) to drive sales and marketing strategies.
• Hospitals and healthcare providers: Analyze a range of patient data (i.e, medical history and treatment outcomes) to improve treatment options made available to patients and offer better patient care.
  
  
• Banks and financial institutions: Monitor financial performance and macroeconomic trends, detect fraudulent activities, and make data-driven investment decisions.
  
  
• Transportation and logistics: Improve route planning and fuel consumption to optimize operations, improve the efficiency of the transportation fleet, monitor warehouse operations, and cut costs.
  
  
• Insurance: Customer segmentation, risk assessment, fraud detection, and improving the claims process. For example, a leading life insurer in the APAC region implemented a unified data strategy that enhanced the visibility of performance metrics, shortened time-to-insight, and democratized data access company-wide for better collaboration. The insurer now has access to more accurate data that supports their decision making across a range of functions.
  

Internal tech teams also have to work around the clock to pick up the slack of outdated systems as legacy ERPs don’t tend to easily integrate with other business applications. For example, when the business wants a new feature, needs to create an integration, or even generate a simple report, the tech team has to step in to customize the outdated system. Over time, these customizations can turn older ERP systems into a one-of-a-kind puzzle that only those who’ve worked on it for years can manage. If these trained resources leave the company or if the system breaks down, the business would have to scramble to fix these issues, resulting in downtimes and mounting expenses.