Mergers and acquisitions often fail to create value due to data complexity and subjective opinions rather than objective data insights. Most M&A deals do not deliver sustainable added value, with 70-90% failing according to research. For M&A to succeed, organizations must address data complexity early on by improving data accuracy and management through tools like analytical appliances and cloud processing to unify and validate data for strategic decision making. Only with high quality, unified data can the anticipated synergies of M&A deals be fully realized.

1. THE EXPERT VIEWPOINT
Industrial
Restructuration
Avoiding the
M&A Nightmare

2. The expert viewpoint
Alexander Kopriwa
Copyright © 2016 datonix SpA
Today many sectors face overcapacity with shrinking markets and margins
and hyper competition. This prompts cost cutting and a frenzy of mergers
and acquisitions (M&A). Stakeholders seek to drive ROI and maximizing
future financial shareholder valuations.
However, when looking underneath the M&A “engine hood”, most mergers
fail to add value. According to Harvard Business Review, research (2011),
findings indicate that between 70 and 90 per cent of M&A don’t deliver
sustainable added value, caused by “data complexity” and subjective
C-Level “opinions” instead of factual and quantitative (objective) data
insights.
Mergers are complex processes, with multiple interdependent causality
reasons, including a lack of management foresight, the inability to
overcome practical challenges and loss of revenue from poorly managed
day-to-day operations. For example quantitative complexity analysis can
(and should be) measured prior to engaging talks, and during M&A
integration to warn about synergies or incompatibility. M&A advisory
processes are driven by success a fee’s only defeating the purpose of
“success”.
How long time available
to analyze and report?
23%
Not enough time
to extract
meaningful
C-Level Dashboard
insights.
More then 77% of
the controller effort
is spent for data
acquisition
and preparation
77%
For these reasons, substantial gains can be
realized by modernizing the tools, and the
methodologies, for use in data preparation.
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On the contrary, a break up or
de-merger, known as LBO
(leveraged buy-out), provides
opportunities to raise additional
equity, unlock hidden shareholder
value and sharpen management
focus. De-mergers can occur by
means of divestitures, carve-outs
spinoffs or tracking stocks (a.k.a.
such stock "tracks" the
performance of a business unit or
operating division of a company).
Both M&A and LBO Cause Data
Complexity!
The benefits of mergers and
acquisitions (M&A) include, among
others:
· diversification of product and
service offerings
· increased plant capacity
· larger market share
· leverage operational know-how
and R&D
· reduction of financial risk
However, C-Level execs frequently
face stumbling blocks after the deal
is consummated despite due
diligence. There is the risk of brand
dilution, too high assessment of
synergies and poor understanding
of the target firm can destroy
shareholder value and lead to
decreasing stock price after the
transaction. Enterprise culture and
turf wars can prevent proper
post-execution and the longer it
takes the worse it gets as staff need
strategic guidance. In addition
companies always have different
management cultures, use different
systems and processes.

3. The expert viewpoint
Alexander Kopriwa
Copyright © 2016 datonix SpA 3
However, if a merger is well executed, the new company value appreciates
as investors anticipate the future synergies, creating cost savings and/or
increased revenue for the new entity.
Only when data is unified and quality assured, then the analytics become
fully meaningful for strategic decision making… and M&A strategies can be
implemented better.
Conclusion
Organizations must address M&A complexity as early as possible; success
is achieved earlier with optimal data accuracy. This is difficult to achieve
manually as ERP and transactional data base systems are fed by humans,
it requires data management infrastructure like analytical appliances or
Cloud processing facilities. As business velocity and rapid change
effectively challenges organizational restructuring teams should use near
automated data restructure tools audits to help perform better M&A
execution.
DATA SOURCE
Active
Dashboard
Operativie
KPI’s Reporting
C-Level Integrative
Reports TBD
DISCLOSE
FIX AND
ADJUSTMENT
DATA MINING
SOURCE
SCAN
CLEANSED
DATA
REVIEWED
DATA
Figure
M&A MDM and Reference
Data Analysis
The Datonix Solution
Datonix data governance framework, resolves most
analytics challenges. It is a powerful framework to ready
and improve DQA, including key ERP definitions of
suppliers, customers, SKU (stock-keeping unit), BOM (bill
of materials) and MRP (material requirements planning)
and more. Management can quickly identify, correct,
unify and validate such data to avoid unproductive
complexity costs. In addition Datonix FDA (fractal data
guardian) ensures solid fiduciary audit trails of
information assets which cannot be falsified after sign-off
validation.
ERP users DQA initiatives must be performed on a
periodic basis (monthly/quarterly), as well as, before and
after ERP application upgrades or modifications.
All of Datonix periodic reporting and procedures can be
fully automated to help clients save time. Monthly tasks
like procurement purchase balance reporting are easily
augmented with insightful graphical reporting configured
to customer preferences both for desktops, tablets and
smart mobile devices. In addition popular dynamic data
journalism tools caters for Dynamic-PDF,
Dynamic-WordPress, Dynamic PowerPoint formats and
custom formats can also be implemented.
The Datonix solution can process detailed granular
data-points with offers user-friendly methodologies to
intervene to speed-up mining and data classification
tasks.
The analytical process consists of three simple steps:
· Scan and correct relevant data-points from accounts
and off-book records
· Review, adjust, consolidate all relevant resource usage
consumtions
· Publicize and disseminate all analytical report findings
to the target constituents
The datonix solution

4. The expert viewpoint
Alexander Kopriwa
Copyright © 2016 datonix SpA
Biography
Alexander Kopriwa, provides advisory services for organizations seeking
competitive and strategic business advantages. Mr. Kopriwa has lived and
worked on five continents and is fluent in five languages. Passionate about
introducing innovative technology to organizations eager to become
market leaders, he is also vice president of international expansion for
Ontonix. A former research director for Gartner Group (and META Group),
he is a proficient handler of global accounts and excels at applying modern
digital methodologies to help clients define disruptive business processes.
Mr. Kopriwa has more than 30 years of experience helping organizations
focus on what matters for expansion and economic survival. Trained in
international economics, IT architectures (Sweden) and change-manage-
ment consulting (Austria), his expansive know-how covers an array of
enterprise constraints in cross-cultural and international environments,
including Mainland China, the United States, Europe and Southeast Asia.
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