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Enterprise Product Data Goes Digital

Product Data X-Ray: Data insights and analysis

As we are entering the fourth industrial revolution, organizations are deploying a plethora of data migration strategies aimed at increasing revenues and market share including a more customer-centric strategy, optimizing their supply chains to reduce costs, and others. One common denominator in every strategy is the collection and insightful analysis of product data.

Entering the digital era

The world is now generating data at the fastest pace ever; in 2016, more than 44 billion gigabytes of data were generated per day, and the number is only going to increase multifold as the International Data Corporation (IDC) predicts that by 2025 the world will be producing 163 zettabytes of data annually1. In addition, the Enterprise 4.0 is revolutionizing its value proposition by shifting from traditional products to digital solutions and services. To facilitate this new direction, companies need to have a consistent product definition and a traceable digital thread and to effectively transition from one product offering to the other. We are seeing an increased number of companies transforming the traditional, rigid product structure into nimble product bundles as a response to constantly changing customer needs, which subsequently requires simple, readily available data across all digital enterprise systems.

Not all data, however, are in a readable and usable format. We are constantly generating data through social media posts, texts, calls, and emails, or even by talking to customer representatives. We have seen the power of unstructured data unravel even in global political campaigns; retailers, forced by increasing competition, aim at gathering customers’ perceptions through data to improve the shopping experience as well as to generate data insights into their product lines. Particularly within the product lifecycle approximately 80 percent of data is unstructured and can be found in various formats, documents, scans, handwritten forms, and emails. Companies struggle to have full visibility and real-time access to their product data, often resulting in suboptimal analyses and performance management.

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Product data comes with challenges

Billion-dollar enterprises with large product portfolios, complex supply chain networks, and extensive global footprint are making substantial IT investments in product data and business systems such as product lifecycle management (PLM) and enterprise resource planning (ERP) among others, to increase visibility and oversight into their processes as well as to generate data insights to shift from reactionary to predictive analysis.

What usually results from large technology implementation programs is the proliferation of product data and multiple options to manage similar processes and tasks with significant importance placed on “governance.” Internal and external stakeholders end up spending more time in locating product prices, specifications, and geographic locations of suppliers, rather than developing new products. In some cases, the inability to effectively track and manage data can potentially lead to compliance gaps and/or executives spending excessive ad hoc effort on product investigations.

For instance, a large biopharmaceutical company received a food and drug administration (FDA) warning letter on one of their manufacturing sites noting issues with their product quality. These issues raised patient safety concerns. The company is now going through a cumbersome and months-long manual effort to identify the root cause and can potentially face hefty fines by the regulatory agency.

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The perfect storm

The limited visibility to end-to-end product management combined with the proliferation of products and parts not only affects product profitability but further exposes businesses to quality compliance risks, particularly when tasked with responding to changes. Companies spend millions of dollars on insights generation to further drive profitability and improve operations. Due to different data formats existing in current systems and data not properly captured in standardized templates, usually, 80 percent of the data analysis effort is allocated to cleaning and preparing the data before they can be utilized for analysis. This drawback has immense cost implications to organizations and slows down decision making and issue resolution.

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Deloitte Product Data X-ray (DPDx)

Based on our experience helping clients across industries, most organizations struggle with acquiring the digital capabilities to accelerate data digitization and harmonization, both of which are critical in reducing the overall cost of insight generation, increasing end-to-end traceability across business systems and functions, and proactively addressing potential compliance gaps.

A focus on data variability assessment is key to prioritizing data rebuilding efforts and to driving scalable solutions. This assessment coupled with clearly defined, managed data governance allows organizations to effectively operate in a multiproduct solution environment while maintaining data integrity and easily scaling up.

Deloitte’s next-gen solution Product Data X-Ray (DPDx) brings together digital technologies with Deloitte’s unparalleled industry knowledge to help organizations better understand their data, define data migration strategy, and accelerate unstructured data digitization by:

  • Aggregating and profiling unstructured and structured data from multiple sources 
  • Auto-classifying documents using “intelligent tagging” 
  • Extracting data from various formats and multiple document formats using pattern recognition methods
  • Enforcing standardization into industry-specific templates, leveraging machine learning algorithms
  • Leveraging open source and big data technologies as underlying architecture for scalable solutions
  • Incorporating descriptive and predictive analytics to monitor product data transformation from “meaningless” to “insightful”

DPDx has helped many of our clients address a range of business challenges including, but not limited to, stock keeping unit (SKU) evaluation for rationalization effort, material equivalency analysis for direct material cost reduction programs, bill of material (BOM) creation, material code harmonization, and clinical documents transformation, with the following measurable benefits realized:

  • Reduces 50–80 percent "non-value add" work depending on system complexity
  • Improves data quality and data profiling assessment with near accurate scope definitions for data transformation activities
  • Automates data classification and drives industry standardization
  • Automates attribute conversion and creates target attributes by appropriately mapping thousands of specs/attributes
  • Drives data migration strategies
  • Provides a baseline for data governance

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Deloitte named a global leader in Product Development Operations Consulting by ALM

Deloitte targets its consulting approach at helping clients manage the complexity in their product development operations to increase efficiency, reduce time to market, and improve commercial outcomes.

–ALM Intelligence, Buyer Ratings Guide, March 2018


Learn more about Deloitte’s Product Development Services.

Stavros Stefanis
Principal | Product Development
Deloitte Consulting LLP
+1 617 437 2352


Balaji Manivasagam
Managing Director | Product Development
Deloitte Consulting LLP
+1 734 306 5367


Venkat Ravichandran
Senior Manager | Product Development
Deloitte Consulting LLP
+1 212 618 4090



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