The synergies that increase a company’s value post-acquisition usually come from things like combining talent, reducing costs from economies of scale, or an increase in sales thanks to new products or expanded geographic reach.
The problem is that up to 90% of acquisitions don’t deliver the value promised, according to a Harvard Business Review study. In fact, more than half destroy shareholder value, KPMG found.
The primary reason? Failure to integrate the businesses effectively. Developing and executing a data strategy is critical to a successful integration.
What is data strategy?
If you want to stay relevant, you must understand what’s driving your business and what’s making your customer successful. Data is the key to that. But as a company grows – adding more units, acquiring other companies and expanding globally – their data grows more complicated.
That’s where data strategy comes in. Data must be viewed and shared across the organization to drive better decision-making. To do that, data must be standardized, so that it can be exposed and shared with different platforms, and then delivered to the employees who need it in an easy-to-use, quick-to-understand format. Without it, your team is driving blind.
In an acquisition, this means having a plan to pull in data from the new business so that you can quickly identify and capitalize on opportunities that will come after the deal closes.
Different ERP systems? No problem
Historically, one of the biggest hurdles to integrating an acquisition has been technology. If the acquiring company runs a different system than the company it is acquiring, it lacks important visibility. Much of the next 12 months or more is spent on an ERP implementation rather than hitting the ground running and acting on opportunities that will drive real value for the combined businesses.
Today’s technology allows you to bring data across disparate systems together for analysis and action – immediately. And by immediately, I do not mean months. I mean days. A data warehouse allows businesses to aggregate data from multiple sources, including different ERP and CRM systems; that normalized data can then be used to create a holistic view of the business.
This is where technology like machine learning and Artificial Intelligence (AI) come into play. They help manufacturers and distributors quickly make sense of the data – from day one of the acquisition. The insights are then delivered in easy-to-use dashboards to decision-makers across the organization.
The power of this is incredible, considering many of these companies have decades of history in their systems: sales, service, orders and everything else that goes into the core blocking and tackling of their business.
We’re working with a heavy equipment manufacturing company that has invested heavily in acquiring companies that make complementary products. Having a strong data strategy in place, they’re able to quickly identify what they're already doing (in terms of geography or existing customer relationships) and uncover where the opportunities lie for cross-selling. It also allows them to profile their existing customers to identify prospects that may need the same basket of products.
The insights delivered are real-time – not based on aggregated historical data. This move to real-time allows you to be far more agile and responsive to the trends that emerge in your markets.
Thanks to vast improvements in computing power and a corresponding decrease in costs, manufacturers and distributors of all sizes have gained the ability to not only easily consolidate their data, but to look forward based on what’s happening right now. The closer you can get to viewing an organization at scale as it operates in real-time, the more accurate your forecasts will be and the quicker you can respond to opportunities in your markets.
The risk of not having a data strategy in M&A
Go back to why you’re acquiring your target:
- Why are they a good fit?
- What will they bring to your business?
- Where are the cross-selling opportunities?
- How can you reduce costs?
If you don’t have a clear data strategy, you can’t answer these questions with confidence. And you risk not realizing the full value of the acquisition. It’s that simple. Avoid being part of the up to 90 percent of acquisitions that don’t deliver the value that was promised.
Make building a data strategy part of your standard process for acquisitions; become one of the few that comes out ahead, giving you a competitive advantage that you can sustain long into the future.
Stefan Siwiecki is an Enterprise Account Executive at Columbus, a technology service and consulting business that designs, implements and maintains business applications for organizations worldwide. His background includes roles focused on manufacturing and distribution, as well as a stint leading an IT organization. Reach him at firstname.lastname@example.org.