Maybe you’ve moved your business forward and supported new initiatives in the past several years with data analytics. Powerful tools can help you throughout your enterprise, including operations, manufacturing, inventory, logistics, marketing, and sales. As technology advances, you can create even better opportunities to use it and make it work for you.
In 2021, you’re likely to see many such advances and changes, like cloud services that enable you to manage more data, new ways to organize your company around data decision-making, the availability of data to those outside of IT, data analysis on the edge, increased data literacy, creative methods for communicating data insights, and the lasting changes brought about by the COVID-19 pandemic.
Here we explore these trends and more.
COVID-19 Data Disruption
No discussion of “what’s new in technology in 2021” is complete without mention of how the COVID-19 pandemic has been disrupting the technology landscape since it started in early 2020. For starters, analysts will switch from looking at information about infection rates, possible treatments, and vaccine development to the monumental tasks of distribution and deployment.
Meanwhile, during the pandemic, companies have had to find new ways to perform tasks and this push has brought on many challenges — but also many improvements. In 2021, organizations will make good use of increased efficiencies, the shift to ecommerce, and real-time data reporting to become more agile and ready for sudden market shifts.
At the same time, they will be looking at data trends with the underlying question of what impact the pandemic may have had on the numbers and whether those trends can be expected to continue post-pandemic.
Data as a Service
Just as Software as a Service (SaaS) has made it possible for companies to move software services from CAPEX to OPEX and eliminate the hassle of regular upgrades, Data as a Service (DaaS) is making it possible for organizations to move their data operations into the cloud. The services offered by providers like Microsoft Azure and SAP deliver data storage, processing, integration, and analytics. The following video provides a simple description of how DaaS can be used effectively by organizations:
The cloud component means businesses can ramp up or down use as needed, creating more agility and cost-effectiveness. Additionally, DaaS provides companies with higher quality data. However, DaaS users will also have to address challenges that include privacy, security, and data governance issues.
Data for Decisions
Enterprises with many data sources will integrate them into their data analysis process. For example, customer communications can be considered along with financial information to create a “single source of truth.” This process will help companies, especially large global enterprises, become more unified in their focus.
The Chief Data Officer (CDO) role will expand, along with teams and budgets related to data management and analysis. Companies will expect a greater return on investment (ROI) from their data tools, especially across a wider variety of use cases, such as marketing intelligence to develop specific consumer profiles.
After scaling back in 2020, enterprises will become willing to spend more money on data-related tasks, including the “decision science” role, which involves transforming data insights into actionable business goals.
Data will become more accessible to everyone in the company, with helpful dashboards and customized reports. It will no longer be part of the IT function only but instead will have a place in every department. These factors will result in fewer data scientists and fewer outside sources. Instead, organizations will rely on a more direct approach. Companies like Airbnb, eBay, and Facebook have used this method for years.
Historically, the information conveyed with data has been relayed via numbers and graphs. Now those in charge of sharing this information with decision-makers are creating “data stories,” or narrative versions of the same set of facts. They can be in the form of video, audio, text, infographics, slide decks, or other formats. Content conveyed this way is easier for people without specialized data training to understand, allowing everyone to join the conversation on important ideas.
Dealing With Edge Data
Edge computing deals with data collected close to the source, such as laboratories or specialized equipment in the field. The edge computing system might do some initial analysis and determine which data to send on, via the cloud, to a central repository. Or, depending on the nature of the project, it might simply keep the data onsite.
The advantage is reducing the costs of data transfer and storage, as well as minimizing latency, by only sending data that is necessary for the project.
Companies will continue to find more use cases for edge computing. Among those already in operation are autonomous vehicles, oil and gas industry assets, smart grid operations, patient monitoring within hospitals and other healthcare settings, cloud gaming, streaming service delivery, and smart city and smart home features.
As the younger generations start to enter the workforce, it will be composed more and more of “digital natives,” those who were raised completely post-internet and expect everything in their world to be digitized. They bring new perspectives to work, as well as an innate understanding of consumers like themselves who are comfortable with this level of machine involvement in their lives.
Even from “digital immigrants,” which includes older Millennials and members of Generation X, companies will expect a higher level of data literacy and the ability to interpret data in their work, even in positions that have not required these skills in the past. Greater digital literacy from all generations will enable companies as a whole to become more data-dependent.
Exciting Possibilities in 2021 and Beyond
So, what will be the result of all these changes? That depends on your company and what you want to achieve. The possibilities of even greater success can come from many data initiatives. They include increased revenue, decreased spending, greater efficiency, streamlined inventory, an improved customer experience (CX) – or all of the above! Start thinking now about your goals for the remainder of 2021 and how you can use data to accomplish them.