Planning and executing M&A and Divestiture have lots of challenges. Having been involved in a few, I’ve noticed that one of the often overlooked challenges is the Data Challenge: the risk of key information loss. On the face of it, it seems strategically unimportant and an after thought, getting it wrong can wreck havoc in the new organization(s).
On Jan 26, 2016, AIG announced* that it will streamline its operations and spin off some parts. Along this journey they will also find out how much better their portfolio of businesses can be. A good plan but, it can be derailed if they don’t focus on the connective tissue that keeps their disparate businesses together- Information; because AIG is in the risk-information business.
AIG plans to break up into a more modular structure with BU leaders having full accountability for cost and performance. This will no doubt open up strategic flexibility. They will be leaner, more focused and more profitable if they execute well. Their plan includes, among other initiatives:
- Return $25Bil to shareholders over the next 2 years.
- IPO United Guarantee (UGC), Mortgage insurance (19.9% will be listed)
- Sell AIG Advisory group
Key success factors for AIG’s new business entities will be (i) Risk expertise and (ii) Financial strength to deliver on long-term promises they make. The latter can be deduced by accountants relatively easily. The former, Risk expertise, is hard to quantify and dwells in AIG’s historical information repository.
Key challenge for AIG will be to disentangle the businesses without handicapping them by denying them access to crucial information needed to evaluate risk and run their business. And, do this quickly on time and on budget.
They need to sieve through their massive amounts of data and separate them for use by the new business entities. As they untangle the data, errors will creep in due to a number of issues including transformation and process errors and their vision of the risk will get blurred. They could lose the “battle” because their Big Data repository was not moved completely and with full integrity. In addition, data errors will result in significant operational challenges for the new business units impacting customers and bottom line. I’ve been involved in (divestiture/) M&A deals where data (dis)integration nearly killed the great strategy.
Data Validation is an often overlooked, yet vital component for success of information businesses like Insurance and Financial Institutions. Accurate data is the life blood of these organizations.