Data Driven Mergers & Acquisitions: Addressing the 70 percent Failure Rate Through the Use of Relationship Analytics
Manish Goel, Co-Founder & CEO, TrustSphere
Manish Goel, Co-Founder & CEO, TrustSphere
Despite the vast majority of M&A’s failing to deliver the anticipated increase in combined business value, the rate of M&A’s across the world continues to rise. A recent McKinsey survey of M&A professionals identified the single most important challenge to effective integrations as being the streamlining and integration of sales and other customer centric functions. Early integration of the sales teams of the newly merged company enables an organisation to rapidly deliver against the forecast synergy benefits. Issues relating to how individuals and teams actually work across the newly merged entity is traditionally complex and hard to quantify or visualize, making them challenging to resolve. Relationship analytics changes this by providing new insights through quantifying the coverage of both an organization’s and an individual’s relationship network. The network surfaced is both the internal network as well as the external network i.e. that with clients, business partners and suppliers.
Due diligence teams spend significant time analyzing financial and customer data. Historically as limited data has been available about teams and their networks, this important area of value has typically been left untested. Much of the value of an acquisition is derived from increased market access – to major accounts or particular stakeholders. Relationship analytics allows an investor or acquirer to objectively validate the true depth of relationships which an organization has with these important contacts. Using data analytics allows them to focus their diligence efforts on those relationships which are material to the business case and better understand the strength and activity around these relationships.
Social network analysis is not a new science. The academic community has analyzed networks for many years and has derived significant value by understanding how orgainzations really function. Research has typically been conducted using staff interviews and surveys which often take months of analysis. This has typically limited the scope of analysis to small groups or internal teams. Latest methodologies enable clients to analyse the entire organizations internal and external network in a matter of days – providing timely and objective insights for use during M&A transactions. TrustSphere’s methodology makes use of archived information to enable clients to quickly gain context even where the service was not in use previously.
“Relationships” are distinguished from mere “connections” based on behaviour observed from corporate communication systems such as email. A real relationship is one where there is has been prolonged, bilateral observed communication patterns, not just limited or one way communication flow. Content of messages is never analyzed. Only log data is ever analyzed; and in order to protect privacy, subject lines are excluded. This ensures the analysis is highly objective and strictly evidence based.
Relationship Analytics: Enabling data driven M&A
Surfacing of previously invisible relationship data is being used to transform three traditional M&A challenges:
- Identifying ownership of key accounts and relationships
When mapping out who should own major accounts, it can be challenging to determine which individuals actually have the strongest relationship with them. Now that the strength of relationships can be objectively measured, they can be compared and contrasted to help provide an informed view to help determine who should own these relationships moving forward.
- Enabling upselling and cross selling
When two organizations come together, it takes time to leverage their combined networks. This makes achieving revenue growth slower than it should be. Relationship Analytics mobilizes the combined network for leverage whilst still protecting all individual relationships. This empowers sales teams to systematically find colleagues who can help with clients and prospecting, increasing the likelihood of delivering on the M&A business case.
Are the “red team” and the “blue team” actually integrating?Significant effort is spent trying to establish whether integration is progressing or if teams are continuing to operate in silos.Relationship analytics provides the data to objectively assess this. It empirically identifies departments and groups where intervention may be required.
Summary
Relationship analytics helps M&A teams solve a variety of challenges. It does so by providing quantifiable, evidence based data and analytics about employees and their relationships. It enables M&A teams to better understand organizational dynamics and informs a set of decisions which help increase the speed of integration.
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