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Abstract

MDM for a single view of customer, products and other entities. But how can IT teams cope with big data sources and increasing volume, variety and velocity, while managing veracity. More critically, how can frontline business teams get the analytics and data‐driven applications they need to achieve their goals. This lunchtime session will describe how all this was achieved as part of a multi‐billion dollar merger, and some of the major and side benefits from the project

Going Beyond Traditional MDM to Deliver the next generation of Modern Data Management

Neil Cowburn, CEORobert Quinn, Practice Lead

October 5th, 2015

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Agenda

1. About iMiDiA

2. The Challenges of M&A

3. Case Study

4. Modern Data Management

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About iMiDiA

iMiDiA is a unique services and solutions company. We take the core principles of Enterprise Data Management, integrate Cloud computing, and move organizations to the next generation of Modern Data Management.

During the previous 18 months iMiDiA has proven the benefits of Modern Data Management during the implementation of a multi-billion dollar merger and today we will highlight how organizations can benefit from this approach.

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Challenges of M&A – M&A Operations in the ‘Dark Ages’

In this era of “business agility” and “enablement” M&A operates as it has for last 20 years—especially when it comes to the technology.

People are still doing things the way they’ve always done and are comfortable with…perhaps it’s how they originally established their expertise in this area.

To that end, they’re still using legacy systems that can’t do what we’d want them to… the technologies that would do everything we wanted didn't exist before.

As a result of not changing with the times, they’re bogged down by the same old issues; complexity, high cost, and inefficiency.

M&A still relies on the use of spreadsheets that are used by tens or even hundreds of accountants.

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Challenges of M&A – Key Business Challenges & Impediments

PEOPLE

Who survives post-merger?

“Change” is not easilyreceived or achieved.

PROCESS

What are the agreed common processes?

What about our ‘secret sauce?’

How can we be more efficient nowand later?

TECHNOLOGY

Which technology is better?

Data must be kept separate

for competitive and legal reasons.

Combined assets must be available

post-merger.

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Challenges of M&A – Technology Challenges

Using spreadsheets actually blocks progress before, during and especially after the merger.

Information gathered to justify the merger is difficult to leverage and validate

The effort to collect the information is substantial and costly

It is time to consider a modern approach, which enables you to leverage and obtain additional value from data.

Today’s technology allows you to; Reduce collection costs, track changes and better control access Repurpose pre-merger analysis for post-merger competitive

advantage Increase the volume and variety of the data analyzed

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▪ Sales quota and territory realignment▪ Product Substitution and Category Management▪ Vendor spend and contract re-negotiations▪ Redundant distribution centers, warehouses and office space▪ Post-merger consolidated reporting and historical comparisons

▪ Master Data scope; Entity overlap and cross-entity relationships:- Customers and Accounts- Products and Services- Locations- Vendors and Contracts

Challenges of M&A – Business Linked Data Challenges

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PEOPLE

Complete re-organization from top to bottom takes

several years during which time competitors

take advantage ofthe chaos

PROCESS

Attempting to standardize on a common business process during a merger is impossible with all the change about to

take place

TECHNOLOGY

CIO/CTO request the build out of technology roadmap with tendencyto expand current costly

investments.

LEGAL

Everyone has to waitfor legal approval

to start Post Merger Integration.

Typical Approach to M&A

PRE-MERGER POST MERGER

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PEOPLE

Leverage both organizations resources as much as possible. Partner highly experienced data

management professionals with in-house business

and IT experts.

PROCESS

Follow the principle of Best of Both. Harmonize

core repeatable processes. Build ‘secret sauce’ into data driven

applications to eliminate competition.

TECHNOLOGY

Data driven approach uses the merger a catalyst for a new innovative technology

layer. Data driven applications utilize the data that supported the merger

benefits case.

LEGAL

Addressed via Cloudand start Pre-Merger

integration.

A New Data Driven Approach

PRE-MERGER POST MERGER

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Case Study

Background: In December 2013, the two largest Food Service companies in the US announced plans to merge. The combined company would be expected to have sales of $65bn. Annual synergies of $600m would be achieved.

The Challenge: iMiDiA was charged with integrating both companies’ data management strategies, data and technologies as quickly as possible in support of the synergy targets.

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Project Goals

Ingest and process master data from the current disparate applications at the two companies

Duplicate detection of master data within the two companies

Consolidated and efficient management of master data post merger in a single company scenario

Support enrichment to enable the combined business teams to get more value out of the master data

Syndicate master data to operational applications and analytic platforms

Support a single point of governance

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M&A Case Study - Timeline

PRE-DAY 1Start Data Consolidation

5 months (Day 60)Customer Segmentation

3 months (Day 30)Customer Matching

7 months (Day 90)Product MatchingCategory Management

POST MERGERDay X – EDWDay X –Single MDM/DG

8 months (Day 100+)Integration to EDW

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1234

CONSOLIDATEPre Day 1 – Objective: Accelerate & maximize data support of value captureCombine data for Customer, Item, Location and Vendor to support Day 1 Value Capture

ENRICHPre Day 1 – Objective: Accelerate & maximize data support of value capture Integrate CHD for Customer, and Lotting attributes for Item

SINGLE POINT OF GOVERNANCEPost Day 1 – Objective: Eliminates redundancies in processes & data entryRollout rationalized workflow and process for master data element creation and maintenance

SINGLE MDMPost Day 1 – Objective: Rationalize system landscapeConsolidate MDM technologies based on harmonized processes

Steps 1 and 2 targeted pre-merger, steps 3 and 4 target post-merger

MDM consolidates Customer, Item, Location and Vendor; including enrichment (3rd party attributes for Customer, Categorization for Item)

Data Driven Approach

The approach for MDM closes the identified gaps across both companies.

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Pre-Day 1 – MDM Solution Implementation

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Post-Day 1 – MDM Solution Implementation

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A set of data management principles that align to and support Business objectives

Principles drive decision making (resource allocation, architecture, technology choices)

Support the changes required by merger while;

Building new competitive capabilities available post-merger

Simplifying the technology landscape

Modern Data Management – Business Alignment

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Modern Data Management – Business Alignment

Data Management prioritized to support strategic business objectives

Today’s Challenges

Missing Organization Insight - No clear solution to reflect different business views of data across the organization and data domains

Increased Costs with Duplicate Systems – Multiple overlapping technologies with inconsistent data exist across the organization

Decentralized Data – Multiple entry and governance routes with unclear accountability

Scalability Issues – No quick or clear solutions for expanding data domains, attributes, and hierarchies

Future State Goals

Single, Comprehensive Master - Transition awayfrom multiple sources to a single location where enriched data can be stored

Quality of Data - Proactively detect and correct data and improve the to optimize the customer experience

Common Definitions - Define and manage consistent data with different views across the organization

Common Data Provisioning - Accommodate evolving business needs while supporting acquisitions, provide additional data functionality, and organization growth

Data Management Guiding Principles

Data is an Enterprise Asset Innovation & Agility

Customer Centric DesignOpen Standards

Secure

Service OrientedSingle View of Master DataAgility Layer to build apps quicker

“Rent b4 Buy, Buy b4 Build”

Business Strategy“Continue acquisition and international growth”

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Modern Data Management – People & Process

People▪ Partner / Pair (combine internal resources with outside expertise)▪ Small teams of highly experience data management resources▪ Internal resources responsible for source system integration▪ Internal resources develop “platform 2.0” in conjunction with

experienced system integrators▪ Business users / data experts for “expert sourcing”

Process▪ Surface data early and often to Business users / data experts▪ Utilize sampling for rule refinement▪ Develop materiality metrics to drive prioritization▪ Utilize collaboration features to minimize meetings▪ Leverage out of box lineage to improve confidence and debug issues▪ Maintain “native” attributes for consistency and system co-existence▪ Create “enterprise” attributes using DQ capabilities and support

enrichment requirements

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Agile and FlexibleDomain independent; Flexible data model. Can support master and transactional data as needed

ScalableProvides platform for rapid assimilation of future growth

UsableIntuitive user interface, business user governance, search, tagging and powerful relationship visualization.

UniversalCross-application / vendor capability supports EA “best of breed” principle for the near and distant future

InnovativeSaaS, Big Data infrastructure, “batteries included”; Data Quality, Consolidation and micro services support

Modern Data Management – Key technology features

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Modern Data Management - Summary

Merger: In June 2015, the FTC ruled against the merger. What does this mean?

Company A: The two data driven applications for customer segmentation and category management are being incorporated into the companies sales and merchandising strategies. In addition MDM application rationalization can be realized due to the advanced capabilities of the platform.

Company B: They are re-evaluating their MDM strategy and footprint at this time. The tenant for this company is being kept alive for future potential use.

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Q & A

Thank you for attending

See our Whitepaper at: https://tdwi.org/articles/2015/09/01/mergers-and-modern-data-management.aspx