A successful merger requires melding all enterprise data within a single environment.
When two companies join through a merger or acquisition, creating cultural cohesion isn’t just a function of executive leadership—unity also requires bringing both enterprises onto the same data platform in order to have a consistent view of the newly forged organization.
Establishing a single environment prevents the type of inefficiencies and data loss that can come with using multiple systems. Attempting to bring numerous pieces of information together from disparate sources can lead to data gaps. These gaps can be serious, and they may include customer information that’s necessary for financial bookkeeping and billing, marketing campaigns, product research, sales efforts and pricing strategies. Without a unified platform, organizations could spend more time determining which information is correct than leveraging that information to propel the business forward.
By contrast, an enterprise data warehouse (EDW) environment enables different departments to interact on business strategies, use the same data to launch fresh research and development, and communicate more effectively with customers. Cohesion within the organization becomes the norm, and for companies undergoing a merger or acquisition, this integration is key.
"The first thing to do is gather data and look through it. How are you going to integrate your customer records, sales, suppliers and all that transactional data? From an operations perspective, you want to understand the books and where you stand there."
The best approach
After a merger or acquisition, the new entity might opt for simply using the larger organization’s data platform. However, that’s not always the best option, because it might run counter to the newly merged company’s business goals and processes, says Rob Toguri, Capgemini Global Vice President of Business Intelligence (BI).
Instead, taking the time to develop a fresh strategy around an EDW can prevent data silos, cultural clashes and inefficiencies. Planning should begin as soon as two companies agree to merge, Toguri suggests, long before the deal actually closes.
Companies must be cognizant of the challenges that lie ahead, however. Turf battles can arise if employees resist a new system or if best practices aren’t adopted early. Integrating an EDW at a cultural level is absolutely critical, Toguri notes, but other issues must be taken into consideration as well. These include de-coupling from application models, developing an information-sharing model and gaining consensus about what types of data should be shared.
A new beginning
Moving toward one data environment should be part of a transition team’s objectives, notes Daniel Fisher, Executive Partner–Accenture Information Management Services. “The first thing to do is gather data and look through it,” Fisher says. “How are you going to integrate your customer records, sales, suppliers and all that transactional data? From an operations perspective, you want to understand the books and where you stand there.”
Discussion should always start with business outcomes, Toguri adds, such as the new company’s go-to-market strategy. With information assets combined, a fresh operating model will emerge, and the decision-making team must envision what that new organization will look like. Also included in the process will be scalability issues, flexibility and common areas of data sharing, all discussed within the framework of proposed outcomes and compliance issues.
A primary team led by senior management and other executives should create a function map across high-level business processes before selecting the data platform, Toguri notes. In some cases, companies establish a team of one, such as the CFO, who owns the entire process. The person must not only understand how information assets overlap but also possess the vision necessary to see how shared data can be harnessed to meet business goals.
“Once you’ve established common areas, you have a sense of how much data is going to be shared. Then you’re looking at the outcomes that you’re trying to achieve with your information strategy,” he says. “Coming to the table with an information-driven approach to architecture is key, and that starts with the newly formed business model.”
In addition to a primary decision-making team or individual, a secondary operations team is required to tackle the issues of day-to-day data processes. This secondary team should include representation from all divisions within an organization, but it will most often include individuals from human resources, operations, marketing and finance.
“This is the ‘cleanroom stage’ where you’re just looking at all the data,” Fisher says. “By understanding how the two businesses overlap and have common processes, you can think about how to sell additional products or services through new channel creation, for example. In order to get to that level, you bring in data assessment teams that can pull it all together.”
Creating a culture
In terms of in-house cohesion, focusing on business processes can help sell the idea of a data warehouse option, Fisher adds. Articulating the advantages of advanced analytics, predictive analysis and financial reporting can create understanding about how the EDW will affect performance across the entire organization.
However, cultural unity extends beyond the just-merged enterprise as employees attempt to unify their divisions. As Toguri explains, it includes customers, who will be affected by the choice of a data warehouse platform.
Fisher points to a “merger of equals” scenario: “A combined supply chain system can be created that offers a virtual view of the entire company.” In this situation, customers could benefit from having a salesperson mention upcoming product development that might be relevant to their business. For instance, two technology companies of equal size might consolidate, and the firm may see that cohesion comes not just from putting together their engineering and development teams, but also from merging customer data onto one platform. Sales and marketing will mesh through shared data, but customers will also benefit because the supply chain—from campaign creation to order tracking to fulfillment to maintenance—is more visible to everyone in the newly merged organization.
Consolidation is a people and process issue at the top level, Toguri adds, and that leads to leveraging best-in-class technology for an outcome-driven solution. “This type of an approach allows you to avoid iterative cycles at the end of the delivery cycle,” he says. “You also create really tight management and understanding of governance.” Once the major data warehousing components are in place, clients can be approached with the new model of information sharing.
One obstacle that may crop up is resistance to the cost of implementing an EDW solution, Toguri says. Many organizations find it difficult to fund a large data warehouse because it requires multiple stakeholders to invest in it. As a result, a common attitude is that the marketing department would prefer to implement its own departmental system in isolation rather than pay for part of an EDW.
Toguri recommends that companies prepare for this type of attitude and develop a plan for overcoming objections. In the long run, an enterprise-wide platform will be more cost-effective because it eliminates silos and stovepipes. Employees and departments should be convinced not that a “big bang” approach is in the works but rather that everyone is on a journey toward a more mature information strategy.
The primary team or leader should spearhead this drive toward integration, Toguri says: “If you have two banks that join together, for example, you’re trying to sell this vision of combined forces. You use that framework to get everyone on the same page.”
Integral to integration
In general, cohesion after a merger or acquisition is a complex undertaking, but establishing an EDW can help the integration effort dramatically. As data systems and departments align, cultural issues may crop up, but they can also be handled more effectively when there’s a single view of the organization.
“It’s the idea of having your cake and eating it, too,” says Toguri. “With an enterprise data warehouse, you get very strong data governance and management and a framework that ties those back to the business model.”