BI Tools and Augmented Analytics That Ensure User Adoption and ROI

Ensure ROI, TCO and User Adoption with the Right BI Tools

When a business sets out to implement BI tools or self-serve augmented analytics, it must consider the entire technology landscape of the business, the expectations of end-users, the cost of the solution, how easily it can be upgraded and integrated and, well…so much more!

 

‘To ensure user adoption and achieve the ROI and TCO the business deserves, take the time to do the work. Develop requirements, consider the features and functionality of a solution and compare those to your use cases and your user expectations.’

 

Management teams do not take kindly to poor Return on Investment (ROI ) or Total Cost of Ownership (TCO) and if the business has had difficult projects in the past, the next time a software solution is presented for approval, senior managers will remember the challenges and failures of the past!

 

Still, when you are attempting to transition business users into Citizen Data Scientists, there is bound to be some pushback from users and that pushback, combined with senior management concerns can and WILL bring your project to its knees if you do not anticipate and address these concerns.

 

Here are some statistics that will help you to understand the issues faced by businesses in implementing BI tools and analytics:
  • The global BI adoption rate is 26%
  • On average, businesses use at least four different BI tools
  • 97% of the data gathered by businesses is not used
  • 74% of employees express dissatisfaction and are overwhelmed when working with business data

 

In order to assure successful deployment, user adoption, improved Return on Investment (ROI) and Total Cost of Ownership (TCO), the business should include detailed requirements in its solution selection. When choosing a BI tool and augmented analytics solution for your business, one of the most crucial concerns is the features and functionality of the prospective solution and how this solution will meet user and organizational needs. When planning for deployment of BI tools and augmented analytics, the business should take the time to work through a process, ensuring that it has considered what users need and want to ensure user adoption and the ease-of-use and features the solution will provide.
To Achieve User Adoption, ROI and TCO Goals, Select the RIGHT BI Tools and Augmented Analytics
It is important to remember that there are also specific features a business should consider, like embedded BI and easy-to-employ Integration APIs, that will assure user adoption and appropriate ROI and TCO. These considerations will affect how well the solution is received, whether users will adopt it and be satisfied with the selection, and how the investment will perform when considering total cost of ownership (TCO) and return on investment (ROI) when compared to other possible uses of the same investment funding.

 

With this foundation of documented features, services, skills and capabilities, the business can implement, manage, upgrade and support Business Intelligence and Augmented Analytics capacity and growth within the organization.

 

‘When you are attempting to transition business users into Citizen Data Scientists, there is bound to be some pushback from users and that pushback, combined with senior management concerns can and WILL bring your project to its knees if you do not anticipate and address these concerns.’

 

To ensure user adoption and achieve the ROI and TCO the business deserves, take the time to do the work. Develop requirements, consider the features and functionality of a solution and compare those to your use cases and your user expectations. INVOLVE your users and middle managers in planning to understand how and when to deploy the tools and how to support your business users as you transition them into Citizen Data Scientists.

 

To find out more about how to ensure Return on Investment (ROI) and Total Cost of Ownership (TCO) results, and enable user adoption, read our free White Paper, ‘A Roadmap To ROI And User Adoption Of Augmented Analytics And BI.’ To find out more about our Augmented Analytics And BI ToolsContact Us. Keep pace with changing enterprise needs and support business agility. Let us help you realize your business goals and objectives with fact-based information, and flexible, scalable technology solutions that will support Citizen Data Scientist initiatives, and improved data literacy and data democratization.

 

Original Post : BI Tools and Augmented Analytics That Ensure User Adoption and ROI!

Is the Citizen Data Scientist Approach Right For My Business?

Find Out the How of the Citizen Data Scientist Approach

In 2016, the technology research firm, Gartner, coined the term ‘Citizen Data Scientist,’ and defined it as ‘a person who creates or generates models that leverage predictive or prescriptive analytics, but whose primary job function is outside of the field of statistics and analytics.’

‘When business users make the transition to Citizen Data Scientists with access to augmented analytics solutions, they can provide additional value to the team, to managers and executives and allow IT and data scientists to focus on strategic goals.’

In the ensuing years, the Citizen Data Scientist role has become more refined, and those businesses that embrace this approach have seen real benefits. But just who are Citizens Data Scientists, and how does a business recognize candidates and benefit from enabling this role?

What Does the Citizen Data Scientist Concept Entail, and Can My Business Capitalize On Its Potential?

How Do I Find Citizen Data Scientist Candidates Within My Business? You will find your Citizen Data Scientist candidates among your business users and team members. They are curious and eager to learn new skills to contribute to the organization and to hone their skills for career advancement. Team members who make great Citizen Data Scientists are often power users, and are acknowledged as leaders within their own team. They are NOT IT professionals, analysts or data scientists but they share a common characteristic for precision and wanting to get it right the first time.

What Does a Citizen Data Scientist Do? Within the context of their roles and responsibilities, every business user needs clear, meaningful information to make fact-based decisions and recommendations. Citizen Data Scientists use data to create reports on a daily basis. As the Citizen Data Scientist role evolved, team members have leveraged the advantages of this data to share reports, to create and format presentations for recommendations and suggested changes to support pricing decisions, hiring, production, new products and services, financial investments, marketing and advertising campaigns, and many other decisions. As the movement grows within your organizations, you can enable data democratization and improve data literacy. Citizen Data Scientists can also work with IT, data scientists and business analysts to share their research and analytics when the business feels it is necessary to take the analytics to another level to ensure credibility for strategic decisions.

What Tools and Training Does a Citizen Data Scientist Need? One of the primary reasons the Gartner predictions have come to fruition is he evolution of the business intelligence (BI) and augmented analytics market to support the concept of Citizen Data Scientists. Today’s analytics solutions are easy-to-use, self-serve tools driven by Natural Language Processing (NLP), and machine learning, as well as Artificial Intelligence (AI). All of these technologies come together to support the business user and provide tools that are sophisticated in their functionality, yet intuitive and easy for a business user. These tools do not require IT skills or data science knowledge. When the team uses these tools, they can adopt a common language and techniques to work with IT and data scientists to create use cases and refine and share reports, formats and outcomes. The more complete, and intuitive the solution, the less training and onboard time the user will require. There are simple, Free Training Courses available that can help your business and your team understand the uses and benefits of this approach and enable user adoption.

When business users make the transition to Citizen Data Scientists with access to augmented analytics solutions, they can provide additional value to the team, to managers and executives and allow IT and data scientists to focus on strategic goals. Using Augmented Analytics Tools like self-serve data preparation to gather and prepare data, and smart data visualization to receive suggestions and recommendations on how to best view data, users can combine predictive analytics to forecast and model, and sophisticated tools like anomaly monitoring, key influencers, and sentiment analysis to gain crucial insight into changes in customer buying behavior, supplier issues, product time-to-market, trends, patterns and opportunities with dependable metrics to make data-driven decisions.

‘The Citizen Data Scientist role has become more refined, and those businesses that embrace this approach have seen real benefits.’

If your business wishes to capitalize on the potential of the Citizen Data Scientist approach, it important to work with an IT Partner who can help you define your requirements and strategize for optimal success, providing the augmented analytics tools and knowledge of the industry that is required to position you for success.

Original Post : Is the Citizen Data Scientist Approach Right For My Business?

Why Choose Augmented Analytics with Low-Code, No-Code Development

Low Code No Code Development Supports Analytics Performance

Within the very near future, it is estimated that 70% of all software and application design will include a component of low-code or no-code development. So, it is no surprise that analytics software and tools are also affected by this trend. While advanced analytics and augmented analytics solutions provide a sophisticated, complicated underpinning of algorithms and analytical techniques, the average enterprise expects (and should look for) tools that are easy to use, so they can improve data literacy and data democratization and leverage analytics within the organization at the business user level, to improve results and efficiency.

It may be difficult to understand how such complex systems can benefit from the no code, low code approach, since the very concept of this approach seems at odds with the complexity of an analytical solution, but nothing could be further from the truth. When applied appropriately, these techniques can benefit the foundation of the augmented analytical solution and the users of those solutions.

  • Time and Expense – In a world where new features and functionality must keep pace with market demand, the emergence of no-code and low-code allows developers to add analytical functionality quickly, while controlling costs and time to market.
  • Business and Market Requirements – As organizations and business users embrace analytics, the need for new types of visualization, reporting and features changes quickly. In order to stay abreast of these changes and offer businesses the products they need, analytical vendors can quickly leverage, modify and develop new approaches to satisfy user requirements. Vendors can accommodate business-specific needs and data visualization requirements without time-consuming, expensive customization.
  • Integration of Third-Party Apps – Low-Code, No-Code capabilities support the easy integration of other enterprise applications and solutions and allow data analysis across the organization.
  • Performance and Scalability – Low-Code and No-Code solutions and platforms enable high-performance, scalable solutions and ensure that businesses can accommodate an expanding user base and data volume.
  • Compliance, Data Security and Industry Standards – No Code, Low-Code development includes data encryption features and user access security controls to mitigate risk, and protect data integrity and privacy.
Augmented Analytics with Low-Code, No-Code Development Provides Performance and Adaptability

If you are still wondering whether low-code and no-code approaches are appropriate for software and applications, consider these predictions and statistics from technology research organizations:

  • Gartner predicts that 75% of new software solutions will incorporate a low-code approach to development.
  • By some estimates, the use of low-code, no-code and artificial intelligence in analytics solutions has increased user access to analytics by as much as 56%.
  • Gartner predicts that organizations that lack a sustainable plan to operationalize and manage data and analytics will face a two-year setback in their data and technology efforts.

Choosing the right self-serve, augmented analytics solution can help the enterprise build a crucial foundation for analytics, for transition of business users into a Citizen Data Scientist role and for improved time-to-market, decision-making and collaboration. The use of new and cutting edge technologies and the seamless incorporation of these technologies is critical to the success of the analytical application implementation and to return on investment (ROI) and total cost of ownership (TCO) metrics.

Select and implement an Augmented Analytics Solution with business intelligence (BI) and advanced capabilities and enjoy the benefits of advanced technologies like Artificial Intelligence (AI) And Low-Code, No-Code (LCNC) techniques to ensure affordable, flexible solutions that every user can leverage, no matter their skillset or technical capabilities. Read our free article, ‘The Benefits Of Low-Code No-Code in Augmented Analytics.’

Original Post : Why Choose Augmented Analytics with Low-Code, No-Code Development!

Predictive Analytics Supports Citizen Data Scientists!

Use Predictive Analytics for Fact-Based Decisions

Like every other business, your organization must plan for success. In order to do this, the team must have a dependable plan and be able to forecast results and create reasonable objectives, goals and competitive strategies. These plans and forecasts will support investment in technology, appropriate resources and hiring strategies, additional locations, products, services and marketing strategies, partnerships and other components of business management to ensure success.

Forecasting and planning cannot be based on opinions or guesswork. It must be based on historical data, facts and clear insight into trends and patterns in the market, the competition and customer buying behavior. To accomplish these goals, businesses are using predictive modeling and predictive analytics software and solutions to ensure dependable, confident decisions by leveraging data within and outside the walls of the organization and analyzing that data to predict outcomes in the future.

‘Every industry, business function and business users can benefit from predictive analytics.’

According to CIO publications, the predictive analytics market was estimated at $12.5 billion USD in 2022 and is expected to reach $38 billion USD by 2028.

Predictive Analytics is Beneficial for Every Industry and Business Function

Predictive analytics encompasses techniques like data mining, machine learning (ML) and predictive modeling techniques like time series forecasting, classification, association, correlation, clustering, hypothesis testing and descriptive statistics to analyze current and historical data and predict future events, results and business direction.

When a business selects predictive analytics tools that are suitable for business users and team members, it can leverage sophisticated algorithms and analytical techniques in an easy-to-use environment to enable every team member to contribute to the bottom line by allowing them to gain insight into data and use that insight to make confident, fact-based decisions.

With these tools, users can explore patterns in data and receive suggestions to help them gain insight on their own without dependence on IT or data scientists. The enterprise can provide the tools needed at every level of the organization with tools and data science for business users that are sophisticated in functionality and easy-to-use for users at every skill level.

The benefits of augmented analytics and self-serve predictive modeling include:

  • No complex algorithms or data manipulation
  • Auto-recommendations for algorithms to explore underlying data
  • No advanced data science skills required
  • Analyze, share, collaborate and optimize business potential
  • Business users can prototype and hypothesize without professional assistance
  • Recommend optimal actions to achieve specific goals

Every industry, business function and business users can benefit from predictive analytics. Here are some examples of the use of predictive modeling:

Retail – Predictive Analytics tools can be used to understand customer buying behavior and to suggest products and product bundling based on previous purchases, buying patterns, and demographics. This creates a more personalized and targeted shopping experience that is unique to each customer.

Supply Chain – The organization can forecast demand and manage the supply chain to optimize inventory using machine learning to predict customer demand, seasonality, product trends etc., to that the enterprise can mitigate stock shortages and avoid warehouse and inventory overstock.

Healthcare – By using historical data regarding specific diseases, conditions and treatment plans, providers can forecast treatment outcomes, limit risk and improve overall care, thereby reducing complications, readmission and provider resource, medication and hospital bed shortages.

Energy Infrastructure – Using predictive analytics allows these businesses to monitor and analyze data and performance and to detect patterns and trends that may indicate downtime, breakdowns and maintenance issues.

Financial Services, Banks and Loan Businesses – Predictive analytics provides support for credit risk and fraud mitigation and allows businesses to create scoring models for loan approval, etc. based on credit history, and other financial considerations. Predictive modeling allows the organization to identify transactions that are outside the norm, and alert the business and its customers of hacks, fraud, etc.

‘When a business selects predictive analytics tools that are suitable for business users and team members, it can leverage sophisticated algorithms and analytical techniques in an easy-to-use environment to enable every team member to contribute to the bottom line by allowing them to gain insight into data and use that insight to make confident, fact-based decisions.’

These are just some of the benefits and use cases your business can consider to decide on how best to implement predictive analytics and integrate the use of these tools into day-to-day use for business users to improve data-driven decisions and results.

To find out more about AI And Predictive AnalyticsContact Us. Keep pace with changing enterprise needs and support business agility. Let us help you realize your business goals and objectives with fact-based information, and flexible, scalable technology solutions that will support Citizen Data Scientist initiatives, and improved data literacy and data democratization.

Original Post : Predictive Analytics Supports Citizen Data Scientists!

Low-Code/No-Code Analytics Design Engenders Solution Agility!

Look for Analytics with Low-Code/No-Code Technology!

The advent of low-code, no-code app and software development has enabled rapid, innovative changes to all types of development projects and that new environment is evident in Modern Business Intelligence (BI) and Augmented Analytics products and solutions.

Why Should Business Users WANT to be a Citizen Data Scientist?

Making the Case for Citizen Data Scientists!

When a business decides to undertake a data democratization initiative, improve data literacy and create a role for Citizen Data Scientists, the management team often assumes that business users will be eager to participate, and that assumption can cause these initiatives to fail.

How Can Mobile BI Help Your Business?

Mobile BI Can Benefit Your Business in Numerous Ways

Gartner defines the field of analytics and business intelligence technology as, ‘an umbrella term that includes the applications, infrastructure and tools, and best practices that enable access to and analysis of information to improve and optimize decisions and performance.’

In order to understand the evolution and importance of Mobile Business Intelligence, we must go beyond the technically specific definition, to talk about the concepts and the purpose of Mobile Business Intelligence Solutions, and how mobile business intelligence tools can help your business become more productive and support success.

‘Providing the right Mobile BI tools to business users, takes the guesswork and frustration out of data analytics and ensures user adoption and improved data literacy.’

While many businesses today have recognized the value of self-serve analytics, they may a) not yet have implemented augmented analytics within the organization, b) have implemented business intelligence (BI) and analytics within the walls of the office environment, or c) be planning to expand self-service analytics to include mobile business intelligence mobile apps that will provide access for business users working in any environment.

Mobile Business Intelligence (BI) Has Many Benefits to Business and Business Users

Here we will discuss the benefits of self service analytics as they relate to the Mobile Business Intelligence environment. Here are just some of the benefits of mobile business intelligence:

Accessibility – When business users have access to real-time data, and insights into results, challenges and opportunities, they can mitigate risk, adapt to change and answer questions from customers, team members, managers and others. Desktop and enterprise BI tools require users to be in the office, which limits access to tools and information for remote users or those who are often on the road, working at home or visiting customers.

Adaptability – If the recent global pandemic taught businesses anything, it highlighted the need to adapt to change, and to establish and sustain tools, business processes and an environment that can support users and the business no matter the situation. The evolution of Mobile BI tools has allowed businesses and their team members to work from anywhere, to remain connected with access to valuable data insights and to keep the business moving with timely approvals, decisions and completion of tasks and activities.

Productivity – If there is one thing business users and their managers hate more than anything, it is the inability to complete tasks or the fear that a task will be completed without all the required information. Team members who are out of touch can hold up the completion of a task or make the wrong decision, because they do not have access to the right information and/or they lack the tools to share information with other users.

Collaboration – When a business user is working in a silo, or when business users do not all have access to the same information, they cannot collaborate. Creative, innovative solutions and insightful decisions only happen when a business team, management team or other department, entity or group has access to tools that allow them to share, report, create reports, and present information in a way that enables collaboration.

Data Democratization – The trend toward Citizen Data Scientists has gained in popularity. As business users transition from isolated team members into Citizen Data Scientists, they need access to sophisticated BI tools that offer clear, concise results in an easy-to-use interface, with features that enable team members to quickly gather and analyze data and share that data with the team. The days of complex BI tools managed by IT teams and Data Scientists are over! While Data Scientists work with crucial data to provide strategic direction, business users with access to self-serve BI tools can perform day-to-day analytics and find the information that will help them complete tasks and make better decisions.

Data Literacy – Today’s businesses must do more with less. That means that every resource, every skill, and every piece of knowledge must be leveraged to produce results. When business users gain literacy in data analytics, they can combine career knowledge, industry skills and business experience with data insights to produce better results. Providing the right Mobile BI tools to business users, takes the guesswork and frustration out of data analytics and ensures user adoption and improved data literacy

Time to Market – Your business must quickly adapt to change, understand competitive initiatives, shifting customer buying behavior, supply and demand challenges and more. With the right mobile business intelligence tools, users can discover the hidden nuggets of information that will help the business move forward quickly. They can answer prospective customer questions to close an order, and explore product bundling opportunities, and new product possibilities, or analyze and suggest changes to supply chain flow or production to ensure swift, reliable time to market.

Fact-Based Decision-Making – Mobile Business Intelligence solutions provide dashboards, reporting, analytical tools and other features on-the-go, so users can explore data, drill-down to find the root cause of a problem, perform searches using natural language processing (NLP) search analytics, visualize data, share data and make confident, data-driven decisions from any location.

‘When business users have access to real-time data, and insights into results, challenges and opportunities, they can mitigate risk, adapt to change and answer questions from customers, team members, managers and others.’

For a comprehensive discussion of Mobile BI and related topics, read our article: ‘What Is Mobile Business Intelligence (BI), How Can It Help Your Business, And What You Should Know Before You Decide.’

In this article, we have defined mobile business intelligence (BI), and discussed the benefits of this type of solution, Contact Us to find out how Mobile Business Intelligence solutions can help your business achieve objectives, and explore the potential of Augmented Analytics Products. Discover the features of Business Intelligence And Reporting, and Download A Free Trial Of Smarten Analytics Software.

Explore our complementary articles on Mobile BI: ‘Choose The Right Mobile BI Vendor To Ensure Success,’ ‘Ensure User Adoption Of Mobile BI,’ ‘Include Mobile BI Tools In Business Workflow,’ and ‘What Is Mobile Business Intelligence (BI), How Can It Help Your Business, And What You Should Know Before You Decide.’

Citizen Data Scientists Can Partner With Data Scientists!

A Citizen Data Scientist Initiative Can Optimize Data Scientists and Encourage a Data-Driven Culture!

According to some estimates, the average salary of a Data Scientist in the United States is over $150,000 per year. If your business wishes to accommodate a ‘data-first’ strategy to improve metrics and measurable success and avoid guesswork and strategies that are based on opinion rather than fact, it can either employ a team of expensive professionals, or it can take a different approach.

‘Citizen Data Scientists can use their knowledge of a business sector, industry, function or market to drive questions and develop reports and presentations to illustrate issues, identify problems and find opportunities for growth and competitive positioning, and share this data (and the search and analytical techniques) with other users.’

Citizen Data Scientists are business users who have a place on your team and are hired because of their professional and career experience in a particular industry, business function or discipline. When they are given access to data analytics, they can merge their knowledge of an industry, e.g., research, healthcare, law, finance, sales, supply chain, production, construction etc., with data integrated from databases, best-of-breed software programs, ERP, SCM, HRM and other systems and use sophisticated analytical tools in an easy-to-use, intuitive environment to gather and analyze data and produce insightful, concise results that are meaningful to their role.

Leverage Citizen Data Scientists to Augmented Data Scientist Teams

Depending on the size, market and industry of your business, you may choose to augment your staff with one or more data scientists to refine results produced by Citizen Data Scientists on a day-to-day basis. So, if a power user or business users discovers a challenge or an opportunity and your management team wishes to further explore the issue to understand its strategic or operational value, a Data Scientist can take the predictive model or other analytical report produced by a Citizen Data Scientist and refine the results for executive review.

Whether you choose to employ the services of a Data Scientist, provide business analysts or IT professionals to support your business users, you can create a comprehensive foundation for analytics across your organization.

By democratizing data analytics you can achieve many benefits, including:

  • Improved Data Literacy Across the Enterprise
  • Improved Productivity of Data Scientists, IT and Business Analysts (who can spend time on strategic initiatives rather than producing daily reports)
  • Optimized Return on Investment (ROI) and Total Cost of Ownership (TCO) for all software and systems
  • Fact-Based Decisions and Metrics-Driven Strategies, Goals and Objectives
  • Team Member Career Advancement
  • Optimization of Resources and Improved Team Productivity

A comprehensive self-serve augmented analytics solution will include Modern Business Intelligence (BI) and Reporting with Key Performance Indicators (KPIs), Self-Serve Data PreparationAssisted Predictive Modeling, and Smart Data Visualization with auto-suggestions to drive the analytical techniques and illustration of data based on data type, volume, etc., and other tools like Embedded BIMobile BIKey Influencer AnalyticsSentiment Analysis, and Anomaly Alerts and Monitoring.

With these tools, the Citizen Data Scientist can leverage Natural Language Processing (NLP) and search analytics with machine learning to ask questions using simple human queries and receive insightful answers. They can use their knowledge of a business sector, industry, function or market to drive questions and develop reports and presentations to illustrate issues, identify problems and find opportunities for growth and competitive positioning, and share this data (and the search and analytical techniques) with other users.

Citizen Data Scientists can predict customer responses to new product features, and to new marketing campaigns, analyze the likelihood of fraud or risk, identify supply chain issues, etc. These tools can also help the organization to foster collaboration and data sharing and encourage business users to innovate, create and explore opportunities using data-driven, factual information.

‘When Citizen Data Scientists are given access to data analytics, they can merge their knowledge of an industry, e.g., research, healthcare, law, finance, sales, supply chain, production, construction etc., with data integrated from databases, best-of-breed software programs, ERP, SCM, HRM and other systems and use sophisticated analytical tools in an easy-to-use, intuitive environment to gather and analyze data and produce insightful, concise results that are meaningful to their role.’

These are just a few of the factors you must consider when implementing a Citizen Data Scientist approach. Business users who are interested in becoming a Citizen Data Scientist must be willing to embrace new technology and tools and working at the leading edge of a new approach to collaboration and decision-making. initiative. Consider engaging an expert for your Citizen Data Scientist. IT consultants with experience and skill in this area can provide crucial support to help you succeed with your Citizen Data Scientist initiative and can provide simple Training Programs to bring your team on board and help them see the value to themselves and to the organization.

Original Post : Leverage Citizen Data Scientists to Augmented Data Scientist Teams!

Understanding and Addressing Data Anomalies in Business!

How Can My Business Understand and Handle Those Pesky Data Anomalies?

Why guess at the cause of your business results? Whether you are seeing positive or negative results, it is still important to understand the ‘why.’ Without this information, you cannot adapt and adjust to improve declining results, OR repeat and improve those great results you are experiencing.

Augmented Analytics Provides Benefits to Data Scientists!

When an enterprise undertakes an Augmented Analytics project, it is typically doing so because it wishes to initiate data democratization, improve data literacy among its team members and create Citizen Data Scientists. The organization looks for a solution that is easy enough for its business users and intuitive enough to produce clear results; one that also provides sophisticated functionality and features and will produce a suitable Return on Investment (ROI) and Total Cost of Ownership (TCO).