Smarten Support Portal Updates – April – 2025!

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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!

Case Study : Augmented Analytics Solution for India Powertrain and Sustainable Solutions Engineering Company!

Augmented Analytics Solution for India Powertrain and Sustainable Solutions Engineering Company

The Client is a prominent engineering company in India, renowned for its extensive history. For over 160 years the Client has delivered bespoke design engineering and precision manufacturing solutions, specializing in enabling seamless motion across industries that include automotive, agriculture, marine, light construction, firefighting, and railways. The Client provides cutting-edge power solutions for critical installations and diverse applications, with expertise in fuel-agnostic engines and precision manufacturing of key engine components. It has expanded offerings in electric power train for mobility and other industrial power applications and a strengthening position in the motion control solutions space with strategic acquisitions, empowering progress across multiple sectors. The Client business is publicly traded on the National Stock Exchange of India (NSE) and the Bombay Stock Exchange (BSE) and a robust distribution network including 200 distributors, 8000 retail stores and 20,000 mechanics across India.

Enable User Adoption of BI Tools with Embedded BI

Embedded BI Assures User Adoption of Analytics

When a business sets out to initiate data democratization and improve data literacy, it must choose the right approach to business intelligence and select an augmented analytics product that is self-serve, intuitive, easy to implement and easy for business users to embrace. Transitioning business users into the role of a Citizen Data Scientist can be challenging.

 

‘If the organization wishes to convince its business users of the importance of data analytics and fact-based decision-making, it must provide tools that are intuitive, easy-to-use and can be established within the parameters of the user’s day-to-day tasks as an integrated part of their workflow.’

 

To ensure user adoption of BI tools, optimize return on investment (ROI) and total cost of ownership (TCO) and successfully deploy business intelligence and augmented analytics, businesses often choose Embedded BI.

 

Gartner defines embedded analytics in this way: ‘Embedded analytics is a digital workplace capability where data analysis occurs within a user’s natural workflow, without the need to toggle to another application.’

If Your Business is Considering BI and Augmented Analytics, Embedded BI Will Enable User Adoption

Embedded BI solutions differ from the typical business intelligence solution in a number of ways. Here are just a few examples:

User Experience (Ux) – In the traditional BI environment, business users must learn a new solution and interface and may be required to among other solutions and software products to use that data within the BI tool. Users with average or poor technical skills are not likely to adopt a solution that requires additional training and multiple steps to accomplish a task. In the Embedded BI environment, analytics is accessible from within a familiar enterprise solution using a single sign-on and tools that are intuitive, so the user can quickly find information and analyze it all in one place.

User Adoption – In a traditional BI environment, users must invest time to learn a new BI tool and work within data silos to try to analyze information and share that information with others. Embedded BI allows users to leverage analytics within the natural flow of their daily tasks and easily share that data with other users, so the team and the individual user adoption is supported.

Integrated Workflow – Business team members are busy, and they are often scrambling to complete tasks on time and to make decisions, create presentations and move on to the next thing. Traditional BI tools require users to interrupt their workflow, and use multiple enterprise solutions to gather and analyze data within the BI environment, so the analytics process is cumbersome and inefficient. Embedded BI allows users to work in an integrated environment, gain data insight and make relevant data-driven decisions without delay or frustration.

 

‘Embedded analytics is a digital workplace capability where data analysis occurs within a user’s natural workflow, without the need to toggle to another application.’

 

In a business environment that is more competitive than ever before, team members must have the tools they need to perform tasks and complete activities dependably, and to have a firm grasp on the solutions and tools they use without spending a lot of time in training, or in gathering and preparing data to gain insight into challenges, issues, opportunities or trends that affect business success. If the organization wishes to convince its business users of the importance of data analytics and fact-based decision-making, it must provide tools that are intuitive, easy-to-use and can be established within the parameters of the user’s day-to-day tasks as an integrated part of their workflow. This approach to BI and analytics will ensure user adoption.

You can find out more about the Smarten Embedded BI And Integration APIs solution and add powerful functionality and access to existing ERP, SCM, HRMS, CRM or any other products. Provide analytics capabilities within existing products without major Investment. Your business users and your customers will appreciate the ease-of-use and access and you will gain a competitive advantage. Read our White Paper: ‘Making the Case for Embedded BI and Analytics.’

 

Original Post : Enable User Adoption of BI Tools with Embedded BI!

Smarten Support Portal Updates – March – 2025!

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?

Case Study : Augmented Analytics for Global Telecommunications Infrastructure Solutions Provider!

Augmented Analytics for Global Telecommunications Infrastructure Solutions Provider

This Client is a global telecommunications infrastructure provider, offering comprehensive end-to-end solutions for wireless network planning, optimization, and performance management. It offers services to over thirty (30) Tier 1 and Tier 2 telecom operators and Original Equipment Manufacturers (OEMs) worldwide, and excels in advanced 5G NR and LTE-A technologies as well as legacy networks. Business services include RF Planning, Optimization, Quality of Service (QoS) Benchmarking, In-Building Solutions, and skilled Manpower Deployment to provide seamless execution across diverse environments. The Client operates in more than fifteen (15) countries and spans five (5) continents.

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!

White Paper – The Practical Use of GenAI in Business Intelligence and Analytics Tools

White Paper – The Practical Use of GenAI in Business Intelligence and Analytics Tools

In this white paper, we focus on the practical use of Generative Artificial Intelligence (GenAI) in Business Intelligence (BI) and Analytics tools and present several business use cases to illustrate how this approach to analytics can support business goals and help the enterprise to achieve goals. We also discuss some of the challenges a business may wish to consider in order to ensure that its analytics solution effectively incorporates GenAI so the enterprise can confidently depend on results and improve user adoption and ROI.

Mobile BI Tools Solve Many Enterprise Issues!

Incorporate Data Into User Roles with Mobile BI

If you are a business executive or an IT professional, you have probably seen a number of articles about the importance of Business Intelligence in industry publications and trade journals. If you are still unconvinced or uncertain about the critical importance of business intelligence (BI) and analytics for businesses like yours, here are some sobering, surprising and impressive statistics to ponder.

  • The global business intelligence adoption rate is 26%.
  • Organizations use 4 or more different business intelligence tools on average.
  • Organizations leave 97% of gathered data unused.
  • 74% of employees feel unhappy or overwhelmed when working with data.
  • Businesses using business intelligence are 5 times more likely to reach faster decisions than those that do not.
  • Bad data costs the US economy $3.1 trillion each year.

When you review these statistics, you will notice that some of the issues described can be resolved by the careful selection of the right software and solutions to satisfy your business, your team needs and your data infrastructure.

Why Mobile BI? Because it Solves Common Business Analytics Complaints!

If you are planning to acquire or upgrade a business intelligence or analytics app or solution to provide self-serve augmented analytics for your business users and improve productivity, access and data sharing, you will want to include the review of mobile business intelligence solutions in your requirements.

‘Mobile business intelligence (BI) solutions improve user adoption, ensure access to data from anywhere and encourage the use of data-driven information across the enterprise.’

The right mobile BI tools can address the issues and statistics listed above in the following ways:

  • The global business intelligence adoption rate is 26% – Mobile BI tools will increase the user adoption rate by providing intuitive data analytics that users can access from anywhere at any time, making these tools an important part of each team member’s tool box.
  • Organizations use 4 or more different business intelligence tools on average – The right mobile BI solution can integrate data from disparate data sources, and allow users to visualize in a way that is meaningful to each team member. It can optimize technology infrastructure and mitigate the issue of data silos and complex data mining and data gathering.
  • Organizations leave 97% of gathered data unused – Data is often misunderstood, misused or unused simply because team members and the enterprise do not know how to leverage, gather and analyze the data, or because the IT and/or data science team is short on resources and does not have the time to produce reports. Mobile BI tools are designed to be used by business professionals on a daily basis and to encourage data literacy and data democratization across the enterprise.
  • 74% of employees feel unhappy or overwhelmed when working with data – Understand and address your business user concerns and make data more accessible, easier to understand and use, concise and clear, so that every user can optimize data, make confident decisions and share and collaborate without data science skills or sophisticated data analytical experience.
  • Businesses using business intelligence are 5 times more likely to reach faster decisions than those that do not – Improve productivity, time to market and return on investment (ROI) and total cost of ownership (TCO) to gain a competitive advantage with mobile tools and easy-to-use techniques that will enable fact-based decisions.
  • Bad data costs the US economy $3.1 trillion each year – Banish bad data by integrating your data sources and analyzing and presenting data in a mobile environment to gain insight into trends, opportunities, issues and problems and reveal clear, concise soluti

‘If you are planning to acquire or upgrade a business intelligence or analytics app or solution to provide self-serve augmented analytics for your business users and improve productivity, access and data sharing, you will want to include the review of mobile business intelligence solutions in your requirements.’

Mobile business intelligence (BI) solutions improve user adoption, ensure access to data from anywhere and encourage the use of data-driven information across the enterprise.

If you want to support your business user team and provide a foundation for BI tools that will better serve your team and your customers, explore Smarten Mobile BI benefits and features, with powerful functionality and access for your business users including out-of-the-box Mobile BI and advanced analytics for every team member. For more information on Mobile BI and Augmented Analytics, read our article, ‘Mobile BI Business Use Provides Real Advantages.’

Original Post : Mobile BI Tools Solve Many Enterprise Issues!