An Ultimate Guide to Data Harmonization & Its Best Practices

We see many organizations having ever-growing sheer volumes of unstructured datasets across their databases, business applications, ERP systems, online services, etc. All this enterprise data is stored and managed individually, thereby creating data silos, inconsistencies, duplicates, and redundancies.

In this scenario, how can businesses gain in-depth insights and make data-driven decisions when they have inaccurate and incomplete data?.

This is where the importance of data harmonization comes into the picture. In this data-driven world, businesses will be at risk and miss a myriad of growth opportunities if they do not harmonize their data. This blog digs into the topic of data harmonization, including its importance, significant benefits, cross-industry use cases, best practices, and more. In addition, we are going to explore PiLog’s Data Harmonization tool.

Without further ado, let’s get started with the basics!.

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What is data harmonization?

Data harmonization is one of the data management strategies that reconciles data from diverse sources to ensure uniformity, consistency, and compatibility. In other terms, it is the process of standardizing and integrating data from disparate sources that are of different dimensions and formats.

What are the benefits of Data Harmonization?

The benefits of data harmonization are profound and multi-faceted. Read on!.

01

Improved data quality

We know that data harmonization ensures data compatibility and consistency across different sources, formats, and standards. Thus, it improves the quality of enterprise data.

02

Enhanced decision-making

The data harmonization process unifies and organizes data so that it can be reliable, consistent, and accurate across all systems. Now, various teams in an organization can view and access data for business operations. As the data is updated and accurate, they can make better-informed decisions.

03

Increased operational efficiency

No doubt!. Accurate and unified data will ultimately minimize redundancies, improve resource usage, streamline business processes, and speed up decision-making, thus improving overall operational efficiency.

04

Accelerated innovation

As mentioned earlier, the unified data improves data quality and eliminates duplicates. It helps in gaining faster insights and making data-driven decisions without effort. Thus, it fosters innovation.

05

Mitigates risks

Data harmonization consolidates data from diverse sources and identifies and rectifies operational, financial, and compliance risks of an organization. It addresses all the errors, discrepancies, and other potential issues by establishing uniform data management standards and protocols. Thus, it mitigates risks and helps businesses from making incorrect decisions.

06

Fosters regulatory compliance

Data harmonization approaches organize and standardize data as per regulatory requirements that ensure to adhering both industry and legal standards. Through regular processes such as monitoring, auditing, and reporting, businesses can adhere to regulatory compliance and mitigate risks along the way.

07

Enhances organizational agility

Harmonized data allows seamless and hassle-free integration of new data sources, business processes, and technologies that enable organizations to adopt ever-changing market conditions. This agility enables organizations to respond quickly to challenges and opportunities, develop more effectively, and outperform competitors in dynamic business environments.

Hope, you understand the significance of data harmonization. Let’s understand PiLog’s data harmonization solution, its process, and its capabilities. Read on!

What is the process of PiLog’s data harmonization?

PiLog’s data harmonization process encompasses

  • Identifying data sources (customer databases, product catalogues, financial records, and other external data sources such as market research data, social media, and weather information)
  • Defining data elements (customer name, product ID, sales data, data types, and data formats)
  • Cleansing data (removing errors, inconsistencies, and duplicates)
  • Normalizing or standardizing data formats
  • Building a data dictionary (includes the information related to data types, formats, values, and relationships among data elements)
  • Implementing a data harmonization tool (to automate the harmonization process so that businesses can save their time and effort)
  • Monitoring the data (checking errors, duplicates, and inconsistencies regularly)

Thus, it enables the organization’s data for seamless integration and analysis.

What are the capabilities of PiLog’s Data Harmonization?

The data harmonization solution from PiLog vouches for automating the process of data cleansing, standardization, and harmonization of free text or unstructured data using Auto Structured Algorithms (ASA) which is built on Pilog’s catalogue repositors and taxonomy of master data records. The capabilities include:
  • Analysis of the source data for completeness, consistency, redundancy, standardization, richness, etc.
  • Auto Assignment of Class & Characteristics from the PiLog’s Taxonomy to each record.
  • Extraction of the characteristic values & UOMs from the source descriptions for each record
  • Extraction of reference data from the source descriptions such as Part#/Model#/Drawing#/Mnfr/Vendor etc for each record.
  • Bulk review of materials (QC Tools & DQ Assessment).
  • Auto mapping of source data with PiLog repositories & other reliable sources.
  • Assigning the data sets to relevant user groups based on various criteria.
  • Capturing additional information (or) Validate processed/structured data.
  • Provision to collect the field data & update (Physical Walkdown).
  • Auto generation of Short & PO text based on User configuration.
  • Identification of redundant records.
  • Exporting the data to be migrated to the Target system(s).
  • Integrating in real-time with other systems.
  • Data Quality assessment & progress reports.

Thus, it enables the organization’s data for seamless integration and analysis.

Use Cases Across Industries

Data harmonization is not confined to one industry. However, here we have explored some of the industries where data harmonization is most commonly used.

01

Healthcare:

Healthcare data is growing in volume, value, and velocity. Having the right set of data and updated information for each patient will help healthcare professionals diagnose and treat their patients with ease. For this, having data harmonization will be a great advantage. This unifies all the fragmented data and provides a holistic view for healthcare professionals across all their systems.

In addition, it helps in patient health records management, clinical research and trials, regulatory compliance, preventative analytics, and patient engagement and experience.

02

Banking & Finance:

No doubt!. Handling enormous amounts of data (structured, unstructured, semi-structured, time series, geospatial, multi-media, and external) collected and generated from banking and financial institutions through transactions, customer interactions, market feeds, etc. will be a daunting task. Traditional data processing methods will no longer handle this sheer amount of data volume.

So, harmonizing data will provide them with a comprehensive and 360-degree view of their customer and all financial data. In addition, to ensure accuracy and consistency and to improve data accessibility, data harmonization is a must for both banking and finance institutions. Moreover, data harmonization aids in risk management, fraud detection and protection, regulatory reporting and compliance, and operational efficiency.

03

Retail:

As the number of data sources and data grows, manufacturers and retailers will face even greater challenges in ensuring the consistency and reliability of the data in their supply chain management (SCM) systems. To stay ahead of the competition, companies must implement ongoing data harmonization and cleansing processes. We already know data harmonization involves bringing data from multiple sources into a unified format, which can then be cleansed to ensure accuracy and dependability.

So, retail business owners or CPG (Consumer Packaged Goods) industries must implement ongoing data harmonization processes that ensure data needed to establish an agile supply chain that is highly responsive to customer trends and insights needed to make strategic business decisions.

04

Manufacturing:

Data harmonization is best utilized in manufacturing conglomerates that own and manage multiple industries, warehouses, and suppliers across the globe. Each of them will have different sets of data formats, systems, and standards. Managing inventory levels, anticipating demand, and assuring timely delivery of supplies becomes a difficult and frequently unreliable task if the associated datasets are not harmonized. In addition, data discrepancies across supply chains lead to inefficiencies such as delays in production, overstocking, and understocking, etc.

This is where data harmonization plays a crucial role in tackling all the above challenges through data standardization that allows seamless communication, supplier collaboration, and data exchange among entities. Furthermore, it helps in product information management, quality control and assurance, predictive maintenance, and regulatory compliance, thereby enhancing the performance of the overall supply chain.

04

Education & Online Learning Platforms:

Many educational institutes and online learning platforms collect vast amounts of data from in-house student information systems, learning management systems, and other third-party applications. So, all this information is stored across disparate systems. This is where data harmonization services are required by them.

Data harmonization collects raw data sets from different sources and applies harmonization techniques such as unifying, cleansing, removing redundancies, eliminating duplicates, etc. The holistic view of data of all the students and online learners helps institutions identify at-risk students, improve student’s knowledge, measure educational programs’ effectiveness, and make better decisions on personalized learning.

What are the best practices for data harmonization?

The answer is simple. It’s the blend of manual techniques and automation tasks.

01

With the inclusion of AI, organizations can reduce errors and increase the speed of their business operations.

02

Create data models that anticipate future needs along with the current needs of your business.

03

Having a no-code environment will be another add-on for faster execution of data harmonization without having any technical expertise.

Wrapping Up

In a nutshell, organizations can’t manage and make better decisions with the ever-growing fragmented data collected and generated from diverse sources and business applications. Having the right data harmonization will definitely reap benefits including improved efficiency, streamlined operations, high-quality data, and informed decision-making.

Is your organization ready for data harmonization?

It is never too late to invest in a prosperous tomorrow. Reach us today for unparalleled data harmonization services tailored to your business objectives.