One of the hot topics of our time is data management, particularly “big data,” a term that describes the voluminous amounts of information coming into a business on any given day.
 
Regardless of your type of business, you readily have, or can easily access, more data than you know what to do with. Your enterprise systems are capturing thousands of transactions a month, customers are talking about your company on social channels and new market intelligence continually surfaces. How do you analyze and use all this available data to develop a competitive advantage and avoid “analysis paralysis”?
 
Finding the right data strategy starts with addressing four areas:

1. Focus on the basics. What are the most important metrics that drive your business; what questions do you regularly need to answer?
2. Understand data availability. Can the answers you need be developed using existing internal and external data sources?
3. Define enabling technology. Do you have the tools to provide these insights in a usable way?
4. Capture consistent data. Do your processes ensure high-quality data and accurate information?  

Once you have a starting point for thinking about data in your organization, the next step is to refine your questions and dig a little deeper, focusing on driving value — in the key areas of revenue growth, operating margin and asset efficiency — through analytics. Unlocking the value in your data requires building internal data management and analytical capabilities. However, before investing in data scientists and powerful data visualization tools, understand where your company lies on the spectrum of data maturity to know what the next step should be. 

Level 1: Transactional Reporting and Master Data Management
Is your data accurate and governed? Will reporting provide trusted information? If not, looking at how your data is structured, who has access to it, and which transactional systems author and consume the data is critical. 

Level 2: Management Reporting and Business Intelligence
What systems are you using to run the business? Do they provide the functionality needed to interact with your employees, customers and suppliers? Are sales and operating metrics available to monitor business performance? 

Level 3: Predictive Analytics and Visualization
What external data sources can be pulled in to show correlations to performance? How can scenario models highlight areas to drive performance improvement? Where can these insights be showcased for ease of access and action?
 
While companies have made great strides in the past 10 years, most private businesses would categorize themselves in Level 1. If you don’t have plans in place to maximize the value from your big data, you aren’t alone. Data management can be overwhelming, but the steps to get started don’t have to be. Creating a plan to slowly build this capability can help your business realize real value rather quickly. 
 
Cohen & Company is not rendering legal, accounting or other professional advice. Any action taken based on information in this blog should be taken only after a detailed review of the specific facts and circumstances.