Startups like Uber and Lyft have all but changed the face of the taxi industry and the customer experience. Many are huge fans. You don’t have to flag anyone down or have an awkward street scuffle to get a ride. Uber has skipped the web and gone straight to the mobile device as its target platform for order management and fulfillment.

Every customer transaction goes into Uber’s database: name, address, credit card info, cell number, pickup location, drop off location, where you travel and when, and the list goes on. But it’s not just the ride that is valuable to Uber. Their database is where the real value is. And guess what? Uber was recently valued at over $50 billion.

Every company has data. And every company needs a data strategy to take advantage of its value. Elements of a winning strategy are:

1. Make Data Management and Analytics a Priority

Increasingly, business and personal transactions and interactions are going through digital channels. As they move to digital channels, they leave behind a lot of data that was not available to companies before. New sources of data exist everywhere – social media, geolocation data, etc. There’s just a lot more digital content available now to help a business understand its performance, relationships and reputation.

But you need to know what to do with it. For example, as Uber’s database grows, it becomes more valuable. They can look at their customers’ digital footprint through analytics and, over time, they can see distinct types of users emerge from their travel and interaction patterns. They can then use these analytics to expand and refine their service offering to better serve the needs of users and travelers with similar digital footprints.

2. Overcome IT Challenges

There are many new choices of data technologies. You need to figure out how to incorporate them into your company’s existing technology stack. But even before that, you need to understand how to manage data as an asset and consider:

  • How data is governed
  • Who owns the data
  • How to manage data quality and security
  • How to handle demand management as new data requests come in and new data sources are identified

In addition, you need to understand how it will be integrated into the infrastructure and environment. That said, it’s hard to find the people right now who understand all of these technologies. There is a shortage of data scientists and Hadoop engineers, for example. Having access to the resources with the skills to implement and manage these new technologies can be one of your biggest constraints and barriers.

Legacy Systems vs. Open Source

There are also challenges associated with the whole technology space. Legacy vendors, such as Oracle, Teradata and Microsoft, want to maintain their hold. They’re all fighting to remain relevant in a technology market space where open source is creating more compelling and cost effective solutions for businesses.

Microsoft, which has a huge research component, has had difficulty embracing the open source movement in the past. Today they are in full support of open source projects in Azure and Visual Studio and release many of their own code bases, such as .NET. Open source is actually much more valuable because it’s run by people who are constantly working on issues of security or lack of performance. These folks will immediately address your issues for one over-riding reason, they are passionate about code – Wikipedia all over again!

3. Prepare for Organizational Change

We’re not just dealing with our own transactional data any more. We’re dealing with data from our industry or sector, as well as external data, such as weather. Though weather might not seem like it has anything to do with your business, weather data can provide great insight that can enable you to positively impact business. Many other datasets are also available, some for a fee, which organizations have discovered they must pay attention to, in addition to their own operational data.

The technologies of today’s data management agenda are new and emerging and are not technologies for which IT traditionally has the skills. There’s a big divide between IT capability and what the business demands for integrating and managing data. As a result, roles like data scientist and data analyst ,with the kinds of necessary skills, are not yet common within organizations, making organizational and change management a requirement.

4. Embrace the Role of a CDO

Until recently, we’ve pretended as if the people who are responsible for the technology (the wires, pliers, software and ERP systems) actually care about the data, but they don’t.

A CIO is not the best person to manage the data. There’s a new paradigm out there, the chief data officer or CDO. Data is such a critical corporate asset that it needs to be managed strategically and at the executive level outside of IT. Technology is an enabler, but data is an asset. Currently many account for them in the exact opposite paradigm.

Many organizations are now appointing a CDO, reporting to the COO or CEO, and their role is to oversee and manage quality, integrity and use of the organization’s data assets, just like the CFO governs the organization’s financial data.

Start Implementing a Winning Data Strategy Today

The elements covered here will get your business off to a strategic start toward more effective management of your data and analytics. I also recommend remaining open to new ideas, getting help from outside and embracing new paradigms for how your business should interact with data as it continues to evolve.

It’s critical to understand that you should absolutely take advantage of anything that can accelerate driving insights from the data already just sitting in your systems out into the marketplace. Having a strategic partner who brings the required expertise and ability to implement proven methodologies will enable your company to create successful data capabilities, and you’ll be able to groom and train internal resources at the same time. That’s what’s going to enable you to beat your competition.

Today’s business intelligence, data management, and analytics strategies seek to enable predictive decision-making and pinpoint areas of revenue growth. Please download: “3 Essential Keys to Today's Data Journey” to find out more.