If you are a business manager who wants to enable a Citizen Data Scientist environment, but you find yourself up against resistance, it is often because your business users believe that advanced analytics is just too hard for them to learn and that the use of these types of techniques and systems will slow them down and confuse their otherwise familiar processes.
Many businesses have embraced the Gartner prediction that transforms business users into Citizen Data Scientists to help organizations democratize analytics with simple tools that will improve the quality and timeliness of decisions. You can read white papers, industry articles and other publications that will support and articulate this approach to business flexibility, agility and success. But, if you do not embrace the culture change required to deploy this strategy across your enterprise, your Citizen Data Scientist initiative will not succeed.
Why do your business team members need to be data literate? If your business is like most, it struggles to keep up with trends and to understand whether, when and how to implement enterprise-wide initiatives. You must convince your senior team and board of directors that these changes (which may be time-consuming and costly) are worth the effort. So, when a business manager says that her/his team needs to be more data literate, these same questions will arise.
The Smarten Partner is a healthcare service provider in the United States, providing a web-based, patient-centric, healthcare management solution and workflow solutions to assist hospitals and healthcare facilities, increase operational efficiency and reduce costs. One of the Partner Clients is a multispecialty physicians group offering medical management clinical research and other primary and urgent care services. This Client offers COVID-19 vaccination programs with services including COVID testing and vaccination management.
Today, business planning is harder than ever. No one knows what is coming next and considering the changes in customer needs and expectations is just one of the issues. How about competition? What about new technology and how it will affect your products and services? What about the need for skills and new training for your team members and candidates? How about access to capital and investors?
Preparing data for analysis used to be a long, difficult process performed by IT or data scientists. Needless to say, that process meant that business users could not get the job done. They were forced to make a request, wait for the process to be completed and then, more than likely, for the same team to actually perform the analysis. If the data prep was not accurate or was incomplete, the process starts all over OR produces poor results and, in many cases, those poor results are not obvious to the business user. What does that mean? It means that the business is using information and results that they do not know are wrong!
The use of business intelligence and business analytics is growing in every industry, business function and in companies of every size. 48% of small and medium sized business CIOs responding to a Gartner survey revealed that business intelligence (BI), data and analytics is one of the technology areas that will have the largest amount of new or additional spending.
There are a lot of business intelligence and analytical tools on the market today and if your business has recognized the need to implement this type of solution for self-serve analytics among business users, it is important to understand the advantages of augmented analytics. Advanced analytics benefits are numerous but, when a business chooses augmented analytics tools, it can ensure that its business users have full access to analytical features and sophisticated techniques without having to learn complex systems and without having to acquire data scientist skills. That ease-of-use takes advanced analytics advantages to the next level by democratizing use and allowing for digital transformation and increased data literacy across the enterprise.
When a business wants to roll out advanced analytics to its business users, it must consider the average skill level and understanding of analytical techniques and ensure that the solution it chooses will support its project goals. One of the most important factors of business user analytics is user-friendly, simple analytics in an augmented analytics environment.
If you are considering an advanced analytics solution, you are probably wondering what you might get from the solution. Are there real benefits to this type of solution and to the democratization of data and the implementation of a self-serve augmented analytics solution that is meant for business users?
