Transitioning From Offline To Online – Analog To Digital

Data makes the invisible, visible. From supporting the most marginalized communities to measuring the full impact of your programs, data can empower all levels of your organization to achieve their full potential. Nevertheless, gathering high-quality, clean data—not to mention storing it in a secure, compliant, and interoperable format—can be a daunting task. Unfortunately, too often organizations don’t have access to the right data or proper visibility into existing data. This makes understanding the importance of data and realizing its potential a persistent challenge.

With the proliferation of new tools and resources available to capture and synthesize data, it can be hard to know how to start compiling usable information and actionable insights.

The most important first step to leveraging your data is to understand what type of data is being collected, how it’s being collected, and the risks associated with poor data collection and management.

Exposing the Invisible

Unknowingly, you’re probably already collecting a fair amount of data about your activities. In fact, data can be found in many of the tasks that are done on a daily basis. However, it might “live” in various applications and handwritten notes filed away by individual team members. Every employee, contractor, trainer, and volunteer is simultaneously acting as a data collector. By amassing thousands of points of information about the communities they work with, they not only help beneficiaries, they work to improve the effectiveness of the programs they are working on as well.

Data, then, must be thought of as the entire process of collecting, linking, cleaning, enriching, and augmenting internal information (potentially with additional external data sources), both offline and online.

One of the best ways to organize and access data is to digitize everything. After all, it is impossible to improve what you cannot measure. Taking offline interactions and information and bringing them online offers a distinct quantitative advantage. Digitizing customer and beneficiary interactions provides a wealth of information for marketing, sales, and program development. At the same time, digitizing internal processes generates data that can be used to optimize operations and improve productivity.

Furthermore, hard data can be used to help reliably quantify the effectiveness of a program and organization. While heart-felt stories are a great means of marketing and communication, program sustainability and indictors of longevity are just as important to stakeholders.

Types of Data

When discussing data collection, it’s helpful to outline the types of data that are often collected. Data is typically collected in the following formats:

Type	Source	Method	Example
active data	user generated data	explicitly solicited / offered data	answering questions on a survey
passive data	system generated data	automatically collected “in the background”	recording what time the survey was submitted

As data generation and collection grow in volume, data relevance will become even more significant. It is simply impractical to collect and save every bit of the terabytes of data that is generated on a minute-by-minute basis. Defining certain requirements based on particular use cases will help ensure that only relevant data is captured.

The following categories can be used to help define data collection:

Inputs– All of the resources required to run the organization and deliver on the mission, including financial and human capital.
Activities– Goals desired and the services, programs, activities and initiatives undertaken to achieve them.
Outputs– Progress made toward objectives and engagement in activities, such as program participation, outreach completed, etc.
Outcomes– Near- and intermediate-term results, such as changes in behavior, volume of sales, etc.
Evaluation– Evidence of long-term impact on target population(s) or issue(s), tracking data over a period of time.

In combination with data from third-party sources, there is a whole wealth of knowledge to be analyzed and protected. However, there are also inherent problems with data collection, which can cause issues with data quality.

Potential Problems When Collecting Data

Not knowing where or how data is being collected can lead to issues with proper analysis and the quality of data being stored. The reliability of your data is brought into question without appropriate visibility into its source. Reliability is the key concept by which data can be used to inform decisions. When data is unreliable, you run the risk of making poor decisions which will only harm the program in the long-run.

Problems can also arise when teams use multiple different solutions for data collection, many of which don’t integrate with one another, creating duplicate data sets or incomplete data sets. Faced with limited capacity and resources, many organizations turn to free solutions like Excel, Google Forms, MailChimp, and Survey Monkey. However, every step added to the process presents a risk for data duplication, omission or exposure. This disconnected and unacknowledged risk is often where failures, data breaches, and loss of data quality occurs.

Data collection also impacts how sensitive data is stored, identified, and ultimately protected. Organizations that collect and use personal data bear legal and ethical responsibility for the handling and protection of this data. However, many are unaware of this responsibility, de-prioritize it, or believe they lack the resources to comply with the complex and nuanced requirements of applicable data privacy rules.

Protecting Sensitive Data

One of the most significant challenges posed to organizations by data protection law is simply a lack of awareness. New policies and regulations have expanded data protection laws around the globe in recent years, which restrict the way companies can use, manage, and retain customer and employee data. Since so many documents today are stored online, many people assume the new laws apply only to electronic files. But consumer rights to the protection of their personal information apply just as much to paper documents as electronic ones. Understanding what data is being collected, how it is collected, and how the regulations apply to the security of that data can help ensure compliance.

Data Privacy and Protection Legislation

The US does not have a single, comprehensive federal law regulating privacy and the collection, use, processing, disclosure, and security of personal information. Instead, there is a patchwork of laws governing privacy such as:

System of federal rules that are sector-specific: (COPPA, GLBA, HIPAA, TCPA, FCRA, FERPA, etc.)
System of state laws (i.e., data breach notifications laws)
Government regulators (FCC, FTC, State AGs – “unfair or deceptive practices”)
Common law principles (invasion of privacy, negligence, etc.)

After European Parliament passed the European General Data Protection Regulation (GDPR), many organizations have focused their efforts on complying with the European’s standardized set of rules on protecting user data due to its comprehensive approach. While enforcement of these rules pertains mostly to organizations located within Europe, the EU GDPR has essentially become a standard for data protection across the world. The regulations behind GDPR are broken down into 8 major principles.

8 Key Principles of the European General Data Protection Regulation (GDPR)

The right to access– This means that individuals have the right to request access to their personal data and to ask how their data is used by an organization after it has been gathered. The company must provide a copy of the personal data, free of charge if requested.
The right to be forgotten– If consumers are no longer customers, or if they withdraw their consent from a company to use their personal data, then they have the right for their data to be deleted.
The right to data portability– Individuals have a right to transfer their data from one service provider to another.
The right to be informed– This covers any gathering of data by companies, and individuals must be informed before data is gathered. Consumers have to opt-in for their data to be gathered and provide consent.
The right to have information corrected– This ensures that individuals can have their data updated if it is out of date, incomplete or incorrect.
The right to restrict processing– Individuals can request that their data is not used for processing. Their record can remain in place, but not be used.
The right to object– This includes the right of individuals to stop the processing of their data for direct marketing.
The right to be notified– If there has been a data breach which compromises an individual’s personal data, the individual has a right to be informed within 72 hours of first having become aware of the breach.

Once an organization has identified where and how it collects and stores personal data, and informed itself about the data privacy rules that may apply, the next step is to adopt internal policies and procedures to bring the organization into compliance. Compliance is not always easy, however, especially with limited resources or know-how. It is advisable to consult with privacy experts to help develop internal policies and best practices, and consider leveling up your data collection and storage mechanisms.

How the Cloud Can Help

Cloud computing refers to technologies that use the Internet as a platform to give users nearly ubiquitous access to highly scalable, flexible, and powerful computing resources through online services that are hosted in off-site data centers. Anyone who has used a search engine, online email service, or social network has already experienced a version of cloud computing. Today, however, organizations are rapidly moving “to the cloud” to make their operations more effective, efficient, and more secure.

Cloud computing can help organizations achieve their cybersecurity and privacy goals in the following ways:

Focusing resources. Cloud Computing is highly scalable and flexible, making it an accessible and affordable solution for almost every organization. By leveraging the versatility of cloud computing, organizations can use less time and finances to maximize value.
Simplifying governance. Because applications and services are hosted in data centers that are operated and maintained by the cloud service provider, cloud computing reduces the burden on organizations to install, maintain, and update hardware and software.
Leveraging existing Cloud security. Perhaps most significantly, the cloud also delivers an immediate step change in security for organizations, without a large upfront investment. This is valuable for both cybersecurity and data protection compliance.

Conclusion

The benefits of clean and efficient data collection extends beyond organizational optimization and can significantly impact a business’s ability to execute their goals. Data digitization increases an organization’s capacity to become more efficient by deploying modern, resilient technology solutions. Organizations that successfully modernize their data practices will be better positioned to fulfill their mission in the long run.

At the same time, there are clear risks involved with scaling data strategies that don’t include data protection considerations. Those that neglect to address privacy and security vulnerabilities are at risk for data breaches, exposing the individuals they are meant to serve to even more risks. There are no magic solutions— organizations are responsible for investing the time and resources necessary to address these challenges. However, in many cases, cloud computing can help by offering scalable and powerful online solutions that decrease overhead and increase data security.

Want to know more? Contact us to see how CropConex can help you bring your offline data online.