We are living at the time when two most interesting things happen in business world. On the one hand, “data-driven business” trend is gaining momentum. Every year new BI startups get funding. Big Data is almost an old topic. Now, Internet of Things and Real Time analytics are getting hot. All major tech companies claim that data is the key resource and focus of their strategies.
On the other hand, many companies face tough times in maintaining growth, so they pursue M&A as an option to feed up and accelerate growth. 2014 has seen 47% increase in deal volume globally, comparing to 2013 (Thomson Reuters). 2015 is widely expected to demonstrate further growth in M&A deals. Despite such optimism in M&A opportunities, 50-80% (according to various estimates) of all deals fails to deliver expected value. At the same time, more and more business executives realize importance of IT in M&A process, which is reflected in the evaluation that 30-60% of all merger synergies come from or are enabled by IT (Bain, McKinsey).
What is in common between “data-driven enterprise” trend and M&A boom? In both cases, managers forget to properly manage the backbone of today’s business – Master Data. But let’s take a closer look at this topic.
The increasing value of Master Data Management (MDM)
With the adoption of business intelligence and analytics solutions many companies have realized that implementing BI becomes a tough challenge, when a company has poor master data management processes or doesn’t have them at all. Apart from failing to realize the value of BI, what are other typical challenges businesses face when no harmonized and streamlined master data are in place?
- High-level of duplicates, which creates distortion in the picture of what is going on with the business. Duplicates might lead to wrong perception of business performance with suppliers, partners, clients or products, which results in wrong decisions. According to the study of The Institute of Internal Auditors, on average 0.1% of payments are duplicates. It means that for an average company with $1bln in payables, duplicate payments results in $1mln.
- High admin, support and process costs, caused by necessity to periodically look for data errors across end-to-end processes and clean the data. According to Gartner and the Bureau of Labor Statistics, 70% of the annual productivity growth of 2.7%, or 1.9%, comes from IT. This means that for an average enterprise with $2.8 billion in revenue and $1.1 billion in labor cost, an average annual increase in IT productivity of 1.9% results in $21.7 million of potential savings. The problem is that 10% of this savings, or $2.12 million, is lost due to poor data quality.
- Fraud risk. Part of the master data management is access control, which segregates the roles of those who create master data and those who use them in business transactions. The absence of either access control processes or master data management poses a risk of having fraud schemes.
- Non-compliance risks. Certain types of regulations (Sarbanes-Oxley, 21 CFR Part 11, Basel II) require compliance in reports and documents, published by an organization, which means accuracy and auditability of reporting. Ability to perform auditing across end-to-end business processes requires established practices in master data management, that ensure accuracy and consistency of data, used across all business domains.
According to Jane Thomson, executive director of EOH, 75% of enterprises don’t have an effective master data management strategy. Lack of master data management greatly affects the quality of decisions made, compliance risks and efficiency in business processes, which are the key reasons for starting MDM projects, according to PwC:
So what? Why M&A and MDM?
According to EY, IT gets significant emphasis as part of approach to M&A transactions only in 38% cases (EY, IT as a driver of M&A success). Traditionally, MDM is perceived by managers as pure IT topic. But in fact, the value of MDM lies not in the IT system itself, but in changing and harmonizing business processes, which requires clear business ownership and commitment (PwC, Hidden Treasure. A global study on master data management, 2011). The conclusion is that when it comes to master data management in the post-merger integration, business executives tackle master data integration too late, losing money and time on compliance issues, increased process costs, increased cost of administrative and IT support, false or double payments, mixed customers and so on.How tackling master data challenge early on can help to set up the right direction for yourpost-merger integration program?
- Creating unified language for merged business units. Once you ask business managers to harmonize master data, you set them to find and/or create a single language in supply, operations, products, categories, customers, financials and other areas. Having a unified language creates shared thinking among managers of a merged company and defines a playground for achieving merger objectives.
- Discovering and realizing synergy opportunities. Harmonizing master data allows to see a comprehensive and accurate picture of a merged business, for example, the total spend across all units, attributed to a specific supplier, share of revenue attributable to a specific customer, product or market segment. This in turn fosters discovery and realization of synergies in the key areas of supply, procurement, sales, service and finance, which might be difficult when the data are not harmonized and require multiple validation and cross checks.
- Harmonized master data supports accurate reporting and timely decision making, crucial in post-merger integration to track the progress and pro-actively approach arising issues.
- In addition, accurate reporting, based on synchronized master data, defines the framework for planning, tracking and rewarding integration performance results. With clean and trusted data, serving as a single source of truth, it is much easier to have discussion on planned and achieved integration results.
- “You cannot manage what you can’t measure”. Some of post-merger IT integration decisions are highly dependent on types, size and structure of master data, used by both companies. Tackling master data first allows to better understand the operational models and IT architecture of merging companies and to make critical decisions on which approach to use in each business area – adopting and leaving only the best of IT system and business processes, leaving both untouched or creating the new one.
When more and more companies rely their business models on leveraging and utilizing vast amount of data they have, and when data become the key enterprise asset, the comprehensive master data management practices become crucial not only in daily operations, but in M&A projects particularly. Gartner says that 40% of business initiatives fail to achieve desired objectives due to poor master data management. Any M&A deal, which is of a highest business risk by nature, can boost this number dramatically. So, it’s better to think about your merged master data first to facilitate your whole post-merger integration thinking in the right direction.
The original of this post was published here.
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