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Data Management matters!  Even in the early years.

May 15, 2018

 

After many years of working with start-up and early-stage companies, I have observed a common problem. Many of these companies include “monetizing data” as a key component of their overall business strategy but do little to establish a process to ensure data collected through the early stages of their growth are managed in a way that enables them leverage or trust it in the future.

 

“Entrepreneurial” shouldn’t mean abandon all data management principals.

 

Entrepreneurial companies thrive on moving fast, staying nimble and delivering an “experience” to the customer. A typical startup company is hyper-focused on product development, sales and marketing – rightfully so.  Time to market is critical and today’s practices include adopting an agile approach to delivery of minimally viable products or services. Startups and early stage companies often have few resources and are insufficiently funded to have formal processes or tools to support data design, collection and storage of quality, consistent data. In fact, with today’s application development tools, websites, mobile apps and entire systems can be created and deployed with little consideration for data integrity or relationships between data.

 

My experience has been that many typical start-up and early stage companies build their first-generation applications using modern development tools that mask the need for structured data architecture and meta data management. Companies are able to stand-up an application to support their business very quickly and often without engagement from IT organizations. This approach is often prudent and can be integral to meeting sales and time to market demands. Unfortunately, it can also result in solutions that have not considered consistency in content and meaning of data across the company or the interrelationships between existing and future data.

 

If fortunate, a company grows to the point where they must depend on data analytics to inform business operations and sales growth.  When this happens, they are suddenly eager to leverage data they have compiled over time to drive these analytical insights. What they commonly realize is that they have a data crisis on their hands.  They cannot trust their historical data’s reliability, there is no common understanding of what their data means, and simple analytics and calculated metrics cannot be relied upon due to an unmanaged approach to data collection. Companies in this predicament are forced to rely on the heroics and “best guess” of their data analysts and data developers to map and aggregate data to run their business. This not only results in inconsistent outcomes and metrics, but also leads to invalid assumptions and poor business decisions. Does this sound familiar?  

 

I have experienced other start-up and early stage companies that clearly see the strategic value of the data that they will be collecting over time. They recognize data as a critical company asset from the start. These companies develop data strategy as part of their overall business strategy and ensure that there is a framework for executing that strategy even if it is deferred during the early days. They recognize that their vision and strategy are fluid and will change before they are positioned to fully develop and fund a formal data management program, but the framework provides minimally invasive processes and a foundation for ensuring that the data the collect will be trustworthy and useful.  

 

Simple steps that can be taken…

 

Companies that are just starting out can reduce the impact of unreliable data by extending the “minimally viable” concept to data management. Establishing a culture that embraces data as an asset  and taking some fundamental steps toward a data management program with help to ensure that they don’t encounter a “data crisis” when they are ready to depend on their data to accelerate business growth and manage existing business.

 

Steps that can be taken early on to ensure reliable data for future analytics and decision making include:

  • start with a “data mindset” – data is the new oil and it should be managed as an asset

  • ensure data ownership and usage rights are clearly defined when contracting with vendors, partners, service providers and suppliers

  • define and educate your teams on data concepts that are critical to the success of the business

  • implement a simple change management process around those definitions and do not allow those definitions to be compromised

  • compile an inventory of all data flowing in and out of your organization. Includes data origin, where it moves over time and relationship(s) to other data

  • ensure all historical data are securely archived and retrievable

These simple steps will help to ensure confidence in the fact that data collected throughout the early stages of your organization’s evolution will be accessible, reliable and capable of providing meaningful analytic insights when it is time to execute your strategic data roadmap.

 

Twelve Oaks Advisors can help. Our team of IT experts can help you think differently about your data management needs and bring sound, executable solutions to your business.  The best way for you and your team to learn more about our what we can do for you is to join us for a 120-Minute Meeting.  Together we'll take a deeper dive into your Data Management opportunities and craft a solution to optimize your business performance.

 

 

 

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