4 ways to make data more manageable for midsize businesses


midsize business owners find ways to make data more manageableDon’t let the headlines about the success of innovators and disrupters dissuade you from using your data to make better decisions. You don't need to be a large enterprise to derive value from new channels and sources of data. In fact, midsize companies have a distinct advantage over their larger counterparts – agility and focus. Even so, many  find the prospect of managing data overwhelming. The following suggestions can help keep your data challenges more manageable.

4 tips you can use to keep your data manageable

  1. Find your data. Map data systems and sources. The goal is to promote sharing and minimize barriers to access and use. You can use data management and data governance to define standards for data sharing and access and to identify overlap in existing data activities. For example, I could ask you to meet me at Battery Park in New York City. Absent directions, instructions or a route guidance, you could probably find your way there by asking for directions, by finding a store that sells a map or by having some prior knowledge of the area. But wouldn’t it be faster if I gave you the map and told you the address?
  2. Consider the source. Having data doesn’t mean you have the right data. Activities like customer journey mapping can reveal data disparities. Identify potential opportunities to collect more specific and meaningful data about customers and how they interact with you. I list and describe journey mapping best practices in this SAS Best Practices white paper, “Analytics and the Customer Journey: 7 Best Practices for Delivering a Better Customer Experience.”
  3. Anticipate data use and distribution. Replications and repeated processes hinder business growth. To minimize replicated efforts, ensure you have mechanisms in place to identify duplicate processes and data sources. Having a strong standard of practice for onboarding new sources and sharing will also facilitate downstream analysis and reporting.
  4. Devise a strategy. Evan Levy, SAS Vice President of Business Consulting for Data Management, notes in The 5 Essential Components of a Data Strategy that a data strategy ensures data resources, “are positioned in such a way that they can be used, shared and moved easily and efficiently. Data is no longer a byproduct of business processing.” He also likes to say that data should be treated as a controlled substance. It isn’t that you shouldn’t take it; but dosing, distribution and prevention of abuse maximize its utility. A solid data strategy will prevent perfectly good data from gaining a bad reputation.

All these suggestions are exercises in focus, not abundance. Your ability to get the basics right and maintain a sense of data focus is paramount to your long-term analytics success. In this video, I explain how midsize business can generate value from data.

What other data challenges are you most worried about? Share your concerns with us in the comments section.


About Author

Analise Polsky

Business Solutions Manager

Analise Polsky’s keen understanding of people in diverse cultures gives her depth and insight into data-driven and organizational challenges. As a Thought Leader for SAS Best Practices, she couples her diverse experience as an anthropologist and certified data whiz, to build core assets and deliver dynamic presentations. Her areas of focus include data visualization, organizational culture and change management, as well as data quality and data stewardship. Her multi-lingual background offers a unique ability to help organizations assess strengths and incumbent skills in order to drive strategic shifts in culture, policy and governance, globally. Analise puts the skills she learned while living in the Amazon to use in the corporate jungle – showing organizations how to evolve data practices and principles to meet ever-changing data demands.

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