Whether you are a business owner, a business executive or a business manager, or you just like to keep up with industry trends, you no doubt have read about the transition of business users to Citizen Data Scientists. The topic has been in industry journals and publications for years, and it is still relevant today.
Technology research and analysis firm, Gartner, coined the term, ‘analytic process automation.’ This process ‘converges data science, analytic and process automation into a single platform—which helps companies automate and integrate the way data and business processes come together. Companies can also make data more actionable across the organization.’
‘By providing augmented analytics tools to all business users, with appropriate access and security, each team member has seamless, clear insight into data and can apply analytics to support their roles and responsibilities.’
When an enterprise undertakes a Citizen Data Scientist initiative, it is striving to do just that. In other words, the business wants to make data more actionable across the organization.
In this article, we review the possibilities of the Citizen Data Scientist environment in an effort to help your organization imagine the new business landscape.
With the right augmented analytics tools, designed specifically for business users, team members can leverage analytics, smart data visualization, self-serve data prep and predictive analytics and all of the sophisticated analytical techniques they will need to make fact-based decisions and recommendations. Those team members who are curious about analytics and comfortable sharing knowledge of these technology tools will become power users and champion the democratization of data and data literacy throughout the organization. This cultural shift will take team members out of the ‘wait and see’ environment and avoid guesswork and opinion, and the delays and data gaps that occur when a business user must depend on IT or on data scientists to get detailed, concise reports.
By enabling personalized dashboards and pushing alerts and reports, businesses processes can be streamlined and users can create dependable processes and actionable data without wading through restrictive reports, or trying to interpret information coming from disparate sources and staff members. Key Performance Indicators (KPIs) provide streamlined, data-based metrics and measurements and keep the team on track.
Augmented Analytics solutions that support business users encourage collaboration and data sharing and allow users to test theories and hypothesize, sharing the results of their research and creating business use cases that can be applied to real-world issues, challenges and opportunities.
By providing augmented analytics tools to all business users, with appropriate access and security, each team member has seamless, clear insight into data and can apply analytics to support their roles and responsibilities. Actions and tasks can be tied to appropriate metrics and to specific goals and objectives to ensure that every team member is working to achieve business goals in a timely, accurate fashion.
‘When an enterprise undertakes a Citizen Data Scientist initiative, it is striving to make data more actionable across the organization.’
Transforming business users into Citizen Data Scientists, provides advantages to the organization, to the business users and to data scientists. With appropriate Citizen Data Scientist Training, the right augmented analytics solution, and organizational planning, the business can provide a solid foundation and build business user confidence by providing an introduction and fundamental information on Predictive Analytics and other tools these users will employ. The business should also consider engaging an IT consulting partner with knowledge of the augmented analytics market, and a solution and support services to provide the guidance and Products And Services your business will need to succeed.
Gartner research states that, ‘90% of corporate strategies will explicitly mention information as a critical enterprise asset and analytics as an essential competency.’ This prediction is supported by initiatives in businesses around the world, as the average enterprise recognizes the value of fact-based decisions and improved business agility.
For a business to succeed in transforming business users to Citizen Data Scientists, it must have a firm grasp on how to use – and encourage team members to use – augmented analytics. Simply providing the advanced analytics solution and integrated data across the enterprise does not ensure user adoption. But, if a user can understand how these solutions will make their jobs easier, and how augmented analytics can help a team member improve their contribution, speed the business process and increase their career potential, user adoption is more likely.
‘Appropriate Citizen Data Scientist training and organizational planning will provide a solid foundation and build business user confidence by providing an introduction, fundamental information and the tools these users will need to succeed.’
In this article, we explore a few examples of business use cases to illustrate how a business user can examine real world business issues within the augmented analytics environment to create data stories and reveal clear, concise results to support recommendations and actionable direction.
By understanding why customers abandon your business, you can address the root causes and issues that create customer churn and prioritize these issues to address the most important factors first. You can alter marketing messages and campaigns to improve results and even create new products or services that will improve customer satisfaction and retention.
Among the many considerations you might analyze for customer churn, your business use case might include services that each customer uses like phones, the number of phones lines, internet services, online security, online backup, device protection, tech support, and streaming TV and movies or you might look at customer account information such as how long they have been a customer, the contract length and detail, payment method, paperless billing, monthly charges, and total charge. Customer churn analysis might also include demographic information about customers like gender, age range, and if they have partners and/or dependents
When considering customer churn analysis, one might use the binary logistic regression technique.
The use case for product and service cross-selling and up-selling is useful to understand what your customers like, and where you can cross-sell, bundle or up-sell other products by leveraging what you know about your customer’s buying behavior. Every business needs to know what makes a customer buy or try another product and what features, design or product or service combinations might help the business sell more units. For example, a retail store manager may want to analyze the optimal and strategic placement of various products in order to increase cross sales.
By looking at transactions, the date of a purchase and what the customer purchased, the business can develop a comprehensive understanding of behavior and brand loyalty. The enterprise will benefit by increasing revenue, targeting new products and services, creating marketing messages to target a particular customer demographic and improving brand loyalty and the product and service mix. One could consider the date of purchase and the products purchased to find item combinations and the frequency of purchase.
To perform analysis on this type of use case, the business might use Frequent Pattern Mining.
This use case focuses on human resource attrition. Like customer retention, human resource retention is important because stable retention eliminates the cost of advertising, interviewing, hiring and training a new employee. Human resource attrition analysis allows the business to see which employees are likely to leave and which will remain loyal, based on tenure, training, job responsibilities, and other factors.
The analytical data set will include pay, performance and reward information, past work experience, team member demographic information like gender, age, education, marital status and employment tenure, as well as job satisfaction rankings for things like satisfaction with pay, and surveys and more. The business might also include performance-reward contingencies.
By reducing employee turnover, the business can improve hiring and screening processes, optimize human resources and compensation, improve training programs and increase employee loyalty and satisfaction.
For this business use case, the business might use the Binary Logistic Regression technique.
For any or all of these Business Use Case examples or any of the many other use cases a team member might want to examine, the augmented analytics solution will provide a sophisticated underpinning of machine learning, natural language processing (NLP) search capability and an intuitive interface to enable and speed the analytics process with tools that are designed for the average business user and require no data science or IT experience or knowledge.
‘For a business to succeed in transforming business users to Citizen Data Scientists, it must have a firm grasp on how to use – and encourage team members to use – augmented analytics.’
Transforming business users into Citizen Data Scientists, provides advantages to the organization, to the business users and to data scientists. Appropriate Citizen Data Scientist Training and organizational planning will provide a solid foundation and build business user confidence by providing an introduction and fundamental information on Predictive Analytics and other tools these users will employ. The business should also consider engaging an IT consulting partner with knowledge of the augmented analytics market, and a solution and support services to provide the guidance and Products And Services your business will need to succeed.
Gartner has predicted that, ‘90% the world’s top 500 companies will have converged analytics governance into broader data and analytics governance initiatives.’ If you wish to compete, your business will want to follow the lead of these top companies. By incorporating analytics into day-to-day activities and allowing access for business users, the business can encourage the transition from business user to Citizen Data Scientist and create a comprehensive system of analytics with governance and collaboration to ensure security, appropriate access, mobile use and fact-based decision-making.
‘The path to Citizen Data Scientist does not have to be fraught with uncertainty.’
If you are a team member in a business environment, your role within that business is unique. But, it doesn’t matter what your role is or what your responsibilities are, it doesn’t matter what tasks or activities you must perform, you need good, solid data to make effective, fact-based decisions. And, your decisions must be swift because business is moving at the speed of light! Add to this the fact that your responsibilities seem to grow in scope and depth every day, and you can see how crucial it is to have the right support and solutions to help you achieve your goals.
If you are considering a transition to Citizen Data Scientist, or your business management team has informed you of their intent to make that transition, you probably have a lot of questions about the process and the role.
Citizen Data Scientists are not business analysts or data scientists. They are business users and team members within the organization. The typical profile of an ideal Citizen Data Scientist is a person who is respected within the organization, and often shares data and information with other users to collaborate and produce outcomes that are designed to achieve goals and objectives and produce a successful outcome. These individuals may already be ‘power users’ of business applications and may have developed and reported or presented data to others with an eye toward clarifying their decision-making. Citizen Data Scientist candidates may also be IT team members who are interested in data science. In any case, these candidates will typically be uniquely curious, interested in data analytics and devoted to fact-based decisions and team collaboration. To fulfill the role of Citizen Data Scientists, business users will leverage augmented analytics solutions; that is analytics that provide simple recommendations and suggestions to help users easily choose visualization and predictive analytics techniques from within the analytical tool without the need for expert analytical skills.
Business users can leverage domain and primary skills and expertise to gain insight into results using augmented analytics. Your team can interact with and collaborate with IT and data scientists to define business use cases and refine outcomes, and users are empowered to use analytical tools to hypothesize, prototype, forecast and predict, so the organization can identify issues, challenges and results prior to implementing changes in pricing, products, customer outreach, organizational structure, and all manner of operational decisions. The Citizen Data Scientist initiative will improve the accuracy of decisions, and allow users to share data and models with other users, thereby adding value to the organization. The enterprise can create and manage goals and objectives using measurable data and can improve time to market and make better decisions. The Citizen Data Scientist approach is crucial to sustained competitive advantage and to nurturing human resource assets, improving productivity and making the right decisions at the right time. Businesses and users can get ahead of the curve in the market and enable true collaboration.
‘The business can encourage the transition from business user to Citizen Data Scientist and create a comprehensive system of analytics.’
When a business makes the decision to implement a Citizen Data Scientist initiative, it must have a clear vision of the path to get business users to a new role, and to support those users with the augmented analytics tools and cultural changes required to encourage user adoption of analytics solutions and techniques. The path to Citizen Data Scientist does not have to be fraught with uncertainty. With the right cultural changes and management and technology support, the team can improve data literacy and encourage data democratization. Training is a key component of this success. But it needn’t be a lengthy, complex process.
An in-person or online training program that introduces the role and provides examples of Use Cases and Case Studies can help business users see how these tools might be used within the confines of their own role in the organization.
Explore the options her: One-Day In-Person Or Online Workshop For Citizen Data Scientists or Self-Paced eLearning Citizen Data Scientist sessions.
Find out more about the Citizen Data Scientist Path, Citizen Data Scientist Training and Augmented Analytics. We can help your business succeed and improve user adoption and data literacy.
Original Post : The What, Why and How of the Citizen Data Scientist Role!
Gartner has predicted that, ‘30% of organizations will harness the collective intelligence of their analytics communities, outperforming competitors that rely solely on centralized analytics or self-service.’ What does this mean for business Citizen Data Scientist initiatives? It does NOT mean that the organization should turn away from this type of initiative. What it DOES mean is that a business should recognize the value and purpose of each aspect of its analytical community.
Whether you have recently been nominated to become a Citizen Data Scientist or you are considering the value of this type of transition for your business, managers and team members alike often ask exactly what a Citizen Data Scientist can do. According to technology research firm, Gartner, the number of Citizen Data Scientists will grow at five times the rate of traditional data scientists. If that’s the case, there must be something to this trend, right?
The technology research firm, Gartner has predicted that, ‘predictive and prescriptive analytics will attract 40% of net new enterprise investment in the overall business intelligence and analytics market.’ When combined with Citizen Data Scientist initiatives, the adoption and use of predictive modeling and forecasting techniques can be a boon to any enterprise. Team members who have access to augmented analytics and assisted predictive modeling can plan better, predict more accurately and dependably meet goals and objectives.
A business that does not optimize its resources is doomed to fail. In this rapidly changing business environment and market, every organization must make the best of precious human resources. No one has enough funding to hire additional resources to get the job done and, when there are extra funds, those funds are quickly earmarked for new products, marketing and other crucial activities.
If you are a business owner, executive or manager, you have already heard about (and are probably implementing) strategies for Citizen Data Scientists. If you are a business user, you may be hearing rumblings of this in your everyday work and wondering exactly what this type of initiative means for you and why you should consider it beneficial.
By now, every wise business team has acknowledged the advent of digital transformation and the transformation of business users into Citizen Data Scientists. But acknowledging the reality and enabling that reality within the walls of an enterprise are two very different things. Where many businesses fail in implementing the Citizen Data Scientist initiative, it is typical to find that the business has simply decided to deploy the strategy without much planning or culture change. Without understanding the shift in workflow, responsibilities and how the use of data will change the enterprise, it is unlikely that the business will succeed in its Citizen Data Scientist initiative.
