What is Data Harmonization

In the consumer-packaged goods (CPG) and healthcare industry, data is more important than ever. It helps you understand what’s selling, where there are market gaps and which channels are the most effective to sell your products. 

But here comes the challenge: the data coming from different sources (sell out, sell in, e-commerce, retail direct, media etc.), in varying formats and with different priorities between local, regional and global needs, all speak different “languages”. So, how can you make sense of this chaos? 

Through the process of data harmonization, you can bring all your fragmented data together into one centralized source, allowing you to gain actionable insights. 

What is data harmonization?

Different organizations give different definitions of data harmonization.

At Redslim, we mean the whole journey from data to insights, from ingestion and enrichment to consumption and activation.

Forrester describes it as “the process of collating and standardizing disparate data sources”. The Boston Consulting Group (BCG) refers to it as a critical enabler for integrating and activating data across business units and categories.

When asking companies, they also give different definitions depending on where they are in their data harmonization journey. Organizations at the very beginning of their journey might mean taking the data from one provider and harmonizing it, so at least the periods or the markets and eventually also the product dimension are the same.

But as they mature, by adding more categories, countries and data sources (like consumer panel data, retail direct data or even internal data) to fill coverage gaps, the process becomes more complex which might change the definition slightly.

But in general, we can say that data harmonization means the process of cleaning, standardizing, and aligning data from multiple sources, so it can be used effectively across the whole company. Think of it like translating different dialects into one common language.

It makes sure that all your data – no matter where it comes from – is pulled together in consistent, scalable datasets across brands, markets, and channels to create a centralized source of truth with aligned product, store, and customer hierarchies which is ready for analytics.

When done right, harmonized data gives you a complete and unified view of your business. It helps teams across departments (sales, marketing, finance, supply chain) stay informed, aligned, and confident in the decisions they’re making.

Why companies should care?

Today consumer goods and healthcare companies have to make decisions quickly and backed by solid insights for better competitivity, and having harmonized data isn’t just a nice-to-have, but it’s a MUST.

Promotions, pricing, product launches and forecasting all rely on data. But if that data is messy or inconsistent, it’s really hard to trust the numbers. This results in low user adoption and negative ROI of your data investment.

A McKinsey study found that “only 40% of consumer-goods companies that have made digital and analytics investments are seeing returns above the cost of capital. The rest are stuck in “pilot purgatory”—running small tests that never scale.” 

Why? Because their data isn’t ready and reliable.

Going further, as brands are looking for advanced analytics and are working on AI initiatives, the need for clean, harmonized data becomes even more urgent. Without it, even the most sophisticated tools can’t deliver the desired results.

Indeed, according to a study conducted by the Promotion Optimization Institute (POI), “40% of CPG organizations state that proper data cleansing, harmonizing, and staging the data is holding them back from delivering trade promotion optimization and analytics”. That’s nearly half the industry still struggling to get the basics right.

Without harmonized data, your promotional strategies are built on shaky ground. You might be spending more than you should, targeting the wrong channels, or missing out on opportunities to boost ROI. And since your teams have to spend additional time cleaning and reconciling data, even before they can analyze it, it slows down the decision-making, holds insights, and makes it harder to respond to market changes quickly.

The benefits of data harmonization

Harmonized data brings a myriad of benefits to data analytics and enables better insights, smarter decisions, and more efficient operations. 

Translating third-party data into specific business contexts

One of the most valuable benefits of data harmonization is its ability to translate third-party data into formats and structures that align with your internal business context. It bridges the gap between the external data and your existing internal data standards, so you can easily integrate it into your existing workflows or reporting. 

Ensuring consistency across datasets

Consistency is the cornerstone of reliable analytics. Consistent data improves the performance of your analytics tools, reduces the risk of errors in reporting, and builds trust in the data at the whole company. It also simplifies governance and compliance, as harmonized data is easier to audit and trace. 

Enabling unified lenses across various categories and regions

For companies operating across multiple categories and regions, harmonized data enables a unified lens through which performance can be viewed and compared. Without harmonization, each business unit or market might be using its own definitions and metrics, making cross-category or cross-regional analysis nearly impossible.  

Harmonization aligns these differences, allowing leadership to assess performance holistically, identify best practices, and scale successful strategies across markets. 

Facilitating advanced analytics with rule-based smart coding

As already mentioned, advanced analytics, machine learning, and AI models require structured, high-quality data to deliver the desired outcomes. Data harmonization lays the groundwork by applying rule-based smart coding to categorize, tag, and enrich data in ways that support deeper analysis.  

For example, harmonized product hierarchies and promotional attributes allow algorithms to detect patterns, forecast demand, and optimize pricing with greater precision. Rule-based coding also enables automation in data processing, reducing manual effort and accelerating time-to-insight.  

So, it’s clear that harmonized data isn’t just cleaner, but it’s also smarter. 

The data harmonization process

Now that we’ve seen the importance and benefits of data harmonization, let’s see how the process typically works. 

1. Data ingestion

This first step is about integrating your data from multiple sources and formats (data provider specific formats, Excel, CSV). You might be pulling sell-in data from one system, sell-out data from another, such as retail direct data like ePOS, or syndicated market data. On top of that, you may also be tracking market trends from third-party research or consumer behavior platforms. Each of these sources has its own format, structure, and level of granularity, which makes it difficult to compare or analyze them side by side. So, the goal at this stage is to bring everything together in one place. 

This is the phase where quality checks happen. You have to check the structure, the completeness and consistency. This involves removing duplicates and fixing errors. In other words, it’s all about making sure that the quality of your data meets high standards and is ready for the next steps. 

2. Data enrichment

Once the data is standardized, you have to ensure that they speak the same language. You have to harmonize the data across 4 dimensions: product, market, fact and period dimension. This means aligning naming conventions, units of measure, product hierarchies, and other variables. 

At Redslim, we have an advanced form of data enrichment called smart coding purposely designed for more advanced analysis. We use smart coding for segmenting product clusters for various price tiers, or determining if a product is truly new or not. 

This step is crucial for making comparisons across markets and channels for your pricing and innovation strategies. Without it, you lose a comprehensive view on what is truly happening in the market.

3. Consolidation

Once your data has been cleaned and standardized, the next step is to arrange it in a way that makes it easy to access, interpret, and analyze. This involves mapping data fields from different systems into a common structure, so that every data point fits into a clearly defined place, allowing you to create a global database. 

So, at this stage, you can combine all the countries, making sure that all the countries have the same product definition, same segmentations, and manufacturers have the same labels. Also, the periods are fully aligned, and the facts have the same name. 

This is what we call a consolidated database, and this is what most companies in the industry are looking for because it enables them to do cross-country and cross-category analysis. 

4. Delivery and consumption

After going through all the above steps, you’ll get consistent, scalable datasets across brands, markets, and channels, all in one centralized place. But there are multiple formats of the output. 

Some companies prefer to get their harmonized data as a flat file, so they can upload it into their data lake and use it for internal projects. They can give access to it to other vendors to do modeling or forecasting analysis. Some others want to receive the data in Snowflake. But most CPG and CHC companies choose to get the data directly in a data visualization tool like Power BI or our unique software called Redslim SPRINT. In this way they can do ad hoc analysis and reporting and dashboarding. 

However, data harmonization isn’t a one-time project, and it doesn’t stop once the data is delivered. With data provided on a regular basis, it becomes an ongoing process that needs your regular attention.

Data harmonization use cases

Harmonized data is a powerful asset that consumer goods and healthcare companies can leverage across a wide range of strategic and operational use cases. Here are some of the key areas where it can make a real impact. 

Global reporting – With harmonized data, you can build consistent KPIs across markets, retailers, and regions. You can access dashboards that show performance across business units in a comparable and reliable way and enable global leadership to make informed decisions. 

Revenue growth management (RGM) – With harmonized data, you can optimize pricing strategies, promotional mixes, and trade investments. It allows for more accurate analysis of what’s working and what’s not about your discount structure, bundling strategy, or promotional calendar, and helps to refine your strategy and maximize profitability on the different channels. With the harmonized data being readily available, RGM teams can reduce the cycle by 50% [1], so they can run the analysis with a much higher frequency, resulting in incremental revenues. 

Retailer collaboration (joint business planning) – When you’re working with retailers using the same harmonized dataset, collaboration becomes more strategic and transparent. It also helps to build trust and negotiate more effectively when it comes to joint business planning. 

Perfect store (sales execution) – Harmonized data supports also store-level tracking of metrics like product availability, shelf presence, and compliance. Sales teams can use this data to identify gaps and take corrective action to further improve the shopping experience and, especially when having SKU-level data, further increase revenue by 1% [1]. 

Innovation and product launch tracking – Launching a new product is a big investment, but with harmonized data you can measure its success more accurately. You can track trial rates, repeat purchases, and regional performance to understand how well a new item resonates with consumers. 

Digital shelf analytics – Harmonized data helps you to monitor your e-commerce presence as well. From search rankings and product content accuracy to availability and pricing, you can make sure that your products are always visible, competitive, and well-represented across online retailers. 

Media & marketing effectiveness – In order to link marketing activities to sales outcomes, you need clean, connected data. With harmonized datasets you can measure the impact of your media spend (including digital advertising, in-store promotions, or influencer campaigns) and plan your future campaigns more accurately, leading to an additional 1% revenue increase. [1] 

Demand forecasting and supply chain optimization – Harmonized datasets improve planning accuracy by aligning demand signals across the different channels and regions. In this way, you can reduce stockouts, minimize waste, and streamline your supply chain operations.  

The risks of not harmonizing the data

Data from many different sources poses challenges to CPG, CHC and Pharma companies. 

Reduced usability – If you leave your data untouched or don’t leverage its full potential, you will never know the performance on a global level. This means fewer use cases and fewer users of the data that you have invested heavily in, leading to a lower ROI. And if you decide to use an external provider, you can unlock up to the highest level of granularity for use cases (UPC level) with multiple mixed data sources, resulting in up to ~2% increased revenue by use case. 

Misleading insights – If your data isn’t aligned, your analysis will be only partial. And so will your decisions. You might think a promotion is working when it’s not or miss a trend that could drive growth. 

Program delays – Teams spend hours manually cleaning and reconciling data instead of focusing on strategy. That’s time and talent that you can’t afford to waste. According to our research (conducted by Kearney), using a specialized external provider like Redslim can free the time of data harmonization teams (up to 40 hours / month) as well as end-users’ (up to 13 hours / month / user), allowing them to focus on high value-added tasks. 

Missed opportunities – Without a clear view of performance, your promotions and pricing strategies may fall flat. You might miss out on key growth opportunities or fail to respond to market changes. 

Tech roadblocks – AI and analytics tools can’t do their job if the data feeding them is messy. You’ll end up with unreliable models, poor predictions, and frustrated teams. 

Redslim makes data harmonization faster

If you’ve ever thought that your team is spending too much time on data harmonization and are still not getting the full picture, then this might be the right time to rethink your approach.

By partnering with a specialized data harmonization provider like Redslim, you can improve the way your organization leverages data. From unlocking new use cases like revenue growth management (RGM) and digital shelf analytics, to accelerating deployment timelines and boosting data ROI, the impact can be huge.

You can gain higher accuracy, reduce errors, and increase your team’s confidence in data. And with harmonized and consolidated dataset, your teams across all departments can focus on more value-added tasks. 

To really understand the potential impact that Redslim can have on your data harmonization journey, contact our team for more information and to get a demonstration of how we can elevate your data analytics to help you achieve your business goals.

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[1] Source: Redslim study conducted by Kearney