B2B2C in Data Management

The Business-to-Business-to-Consumer (B2B2C) scenario is increasingly important in Master Data Management (MDM), Product Information Management (PIM) and Data Quality Management (DQM).

This scenario is usually seen in manufacturing including pharmaceuticals as examined in the post Six MDMographic Stereotypes.

One challenge here is how to extend the capabilities in MDM / PIM / DQM solutions that are build for Business-to-Business (B2B) and Business-to-Consumer (B2C) use cases. Doing B2B2C requires a Multidomain MDM approach with solid PIM and DQM elements either as one solution, a suite of solutions or as a wisely assembled set of best-of-breed solutions.B2B2C MDM PIM DQMIn the MDM sphere a key challenge with B2B2C is that you probably must encompass more surrounding applications and ensure a 360-degree view of party, location and product entities as they have varying roles with varying purposes at varying times tracked by these applications. You will also need to cover a broader range of data types that goes beyond what is traditionally seen as master data.

In DQM you need data matching capabilities that can identify and compare both real-world persons, organizations and the grey zone of persons in professional roles. You need DQM of a deep hierarchy of location data and you need to profile product data completeness for both professional use cases and consumer use cases.

In PIM the content must be suitable for both the professional audience and the end consumers. The issues in achieving this stretch over having a flexible in-house PIM solution and a comprehensive outbound Product Data Syndication (PDS) setup.

As the middle B in B2B2C supply chains you must have a strategic partnership with your suppliers/vendors with a comprehensive inbound Product Data Syndication (PDS) setup and increasingly also a framework for sharing customer master data taking into account the privacy and confidentiality aspects of this.

This emerging MDM / PIM / DQM scope is also referred to as Multienterprise MDM.

TCO, ROI and Business Case for Your MDM / PIM / DQM Solution

Any implementation of a Master Data Management (MDM), Product Information Management (PIM) and/or Data Quality Management (DQM) solution will need a business case to tell if the intended solution has a positive business outcome.

Prior to the solution selection you will typically have:

  • Identified the vision and mission for the intended solution
  • Nailed the pain points the solution is going to solve
  • Framed the scope in terms of the organizational coverage and the data domain coverage
  • Gathered the high-level requirements for a possible solution
  • Estimated the financial results achieved if the solution removes the pain points within the scope and adhering to the requirements

The solution selection (jump-starting with the Disruptive MDM / PIM / DQM Select Your Solution service) will then inform you about the Total Cost of Ownership (TCO) of the best fit solution(s).

From here you can, put very simple, calculate the Return of Investment (ROI) by withdrawing the TCO from the estimated financial results.

MDM PIM DQM TCO ROI Business Case

You can check out more inspiration about ROI and other business case considerations on The Disruptive MDM / PIM /DQM Resource List.

Congrats to Datactics for Having the Happiest DQM Customers

The latest Information Difference Data Quality Landscape is out. The Data Quality Management (DQM) market is, based on the changes seen from last year, a stable market with little movement.

Information Difference DQ Landscape 2019 and 2020

Atacama and Active Prime have joined this year’s landscape and Pitney Bowes has left the market after the take over by Syncsort as reported in the post Syncsort Nabs Pitney Bowes Software Solutions.

The report also measures how happy the end customers are with the vendors: “The happiest customers based on this survey were those of Datactics, followed by those of Syncsort and Active Prime, closely followed by those of Innovative Systems and Melissa Data, then Experian. Congratulations to those vendors.”

Also, this time it strikes again that the mega vendors (IBM, SAP, Informatica) are not in this crowd.

Check out The Information Difference Data Quality Landscape Q1 2020 here.