The Client is the largest global manufacturer of Air Coolers. The Client is an India-based Multi-National Company with a presence in over sixty (60) countries. As the market leader, this enterprise enjoys a prime position in the residential, industrial and commercial market segments and its brand is considered synonymous with cooling products in the global market. The Client is a market disrupter in what is a diverse and poorly organized sector and it has set the market benchmark with 201 trademarks, 64 registered designs, 15 copyrights and 48 patents, thereby setting the gold standard for air cooling in the global market.
Tag: Advanced Analytics for Business User
Don’t Be Daunted by the Challenges of BI Tools. Self-Serve BI is the Answer!
Gartner research reveals that, ‘90% of corporate strategies will explicitly mention information as a critical enterprise asset and analytics as an essential competency.’ As business professionals, we all know that information is power and today, your business users are expected to know more and to keep pace with industry, market and customer changes that will negatively impact the business or have provide potential opportunities. But how do your team members achieve these goals when they are busier than ever, and the changes are coming more rapidly than ever!
‘Simple, self-serve BI tools can provide your business with the foundation to achieve your goals with features and tools like Social BI, Mobile BI, Embedded BI, etc.’
In this article, we will discuss the topic of modern business intelligence tools and solutions and the advantages of providing self-serve tools to your users for day-to-day analysis and intelligence gathering.
First, let’s look at some of the challenges you will need to consider when implementing self-serve BI tools:
Challenges of Self-Serve BI
- Technology Access and Infrastructure Readiness – Your IT, finance and management teams will need a comprehensive understanding of your current technology and infrastructure, the data hubs, data warehouses and software solutions (legacy, best-of-breed, ERP, etc.) that will provide the foundational data for your users. You will need a plan and a roadmap to integrate these into your business intelligence strategy. A modern, seamless BI solution can provide a simple solution for what might otherwise be a challenging situation. If you can easily integrate your data sources and make them available for data gathering and analytics, your users can leverage the data to report, share and collaborate.
- Team Member Adoption and Understanding – Your team will also need an understanding of the average technology skills of your business users and their willingness to adopt new tools and solutions. If your team members perceive that your BI tools are difficult to use, or if they are not educated on the need for and the benefits of self-serve business intelligence, they are unlikely to adopt the new tools. If, on the other hand, they see the value to their role and how it can make them more productive and streamline their work process; if they see that the solution is easy and intuitive to use, your business is less likely to face the challenges of team reluctance.
There are many other challenges and considerations that should inform your BI tools strategy, but these two are perhaps the most important.
Now, let’s consider some of the many benefits of self-serve business intelligence and how it can support your goals and simplify the lives of your business users:
Benefits of Self-Serve BI
- Social BI – Social BI allows users to champion the use of business intelligence. Power users and those who are curious by nature will create reports, share and collaborate, using easy-to-use tools and thereby encourage others to use the tools and to repurpose report formats etc. to achieve their own goals. Social BI allows business users to share, ‘like’ and perform tasks in a way that is similar to social networking and is therefore popular among business users.
- Mobile BI – Today’s team members often work remotely, or spend a lot of time on the road. By providing self-serve business intelligence that is intuitive to use and accessible on Android and iOS devices, the business can ensure that users will have seamless access and can accomplish tasks, search for information, share and collaborate, without missing a beat!
- Data Democratization and Data Literacy – If you want your team members to grow and add more value, you want to encourage data literacy and ensure data democratization. Move away from restricted data access and sole ownership of analytics by data scientists, IT and business analysts. Provide easy-to-use tools that allow for simple search analytics in a Google-type environment and will make it easier for reluctant business users to embrace your new BI solution and develop new data analytics skills they can use for fact-based decisions.
- User Adoption – There is nothing more frustrating than spending the time and money to implement a new solution, only to find that your users are resistant to using that solution. With true self-serve BI tools and intuitive data visualization, reporting, analytics and access, users will want to adopt the tools and share their discoveries with other team members.
- Embedded BI – If you want to leverage existing technology, improve your Return on Investment (ROI) and Total Cost of Ownership (TCO) for your current solutions and infrastructure, consider that self-serve BI tools can be embedded into existing solutions. With embedded BI with Integration APIs, users can leverage familiar, favorite software solutions in a single sign-on environment, and find information within those solutions without having to learn complicated new techniques or fighting with data silos and transferring data from one place to another.
There are many other advantages to Self-Serve Business Intelligence. This short list should give you some ideas of how you can leverage these tools in your own business landscape.
‘As business professionals, we all know that information is power and today, your business users are expected to know more and to keep pace with industry, market and customer changes that will negatively impact the business or have provide potential opportunities.’
Business Intelligence solutions should include tools and techniques that make it easier to achieve data literacy and provide data analytics access to all business users. Simple, self-serve BI tools can provide your business with the foundation to achieve your goals with features and tools like Social BI, Mobile BI, Embedded BI, etc. Let us help you achieve your vision and improve productivity and insight across the organization.
Original Post : Let’s Discuss: Benefits and Challenges of Self-Serve BI!
Listen to the Experts: Citizen Data Scientist Results are Real!
Gartner has predicted that, ‘a scarcity of data scientists will no longer hinder the adoption of data science and machine learning in organizations.’ As businesses embrace the concept of transforming business users to Citizen Data Scientists, the Gartner prediction takes on a very practical application and enterprises try to sort through the roles of data scientists, business analysts and Citizen Data Scientists.
‘You can be a subject matter expert, or a professional trained in a very specific business function or industry and you can combine this expertise with augmented analytics to achieve your goals.’
Those at the top of major corporations, with experience in managing the reality of the data science landscape, are now realizing that they can create a collaborative environment that includes those who have data science and statistical experience, as well as those who have professional experience that is brought to bear for operational and strategy decisions by combining industry and domain knowledge with intuitive data tools and solutions.
In a recent CDOTrends Article, experts describe a data analytical environment that includes economists, engineers, data scientists and others from varied disciplines. In another publication in Fortune Magazine, experts talk about the very real evolution of data science and the fact that professionals at all levels will need to use, and WILL be using, data and analytics.
These articles point out the fact that Gartner predictions are now a reality, and that data science is proliferating across organizations of all sizes in all industries. Foundational data science skills are important but, as Gartner has predicted, the sophisticated, professional data scientist training is not required for business users to participate in, and benefit from, data analytics. Augmented analytics, designed for use by business users, provide tools that are easy enough for all users, and allow for natural language processing (NLP) and search analytics in an environment where users only have to ask a question, and can then allow a system to provide the context-oriented response they need to gain insight into an issue.
You can be a subject matter expert, or a professional trained in a very specific business function or industry, and you can combine this expertise with augmented analytics to achieve your goals. Data Scientists can then focus on strategic initiatives where analytics must be 100% accurate. When a business provides support for business users to transition into Citizen Data Scientists, the tools allow business users to leverage sophisticated techniques and to become more data literate and comfortable with analytics as part of their day-to-day workflow and business processes.
All of this is a long way of saying that Citizen Data Scientists are a reality today, and that the evidence of efficacy and effectiveness exists in many organizations today.
‘Combining professional experience to make operational and strategy decisions, and a user’s industry and domain knowledge with intuitive data tools and solutions is a powerful benefit to the enterprise.’
As we gain experience with the new reality of distributed data science, we hear from senior executives and experts who have seen the good and the bad of the evolution. And, the experts tell us that the most important trait of successful data analysis is curiosity. Citizen Data Scientists can use their experience in their role to ask the right questions and allow the new generation of augmented analytics solutions to provide the answers, without coding or sophisticated data science skills. Business users can easily understand what the data is saying in layman’s terms and translate complex issues into insight that is easy to understand.
Transforming business users into Citizen Data Scientists, provides advantages to the organization, to the business users and to data scientists. Today, businesses can explore a FREE Online Citizen Data Scientist Course, and the right augmented analytics solution, and organizational planning, to build a solid foundation and business user confidence. 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.
Original Post : The Efficacy of Citizen Data Scientists is Proven!
Apply Predictive Analytics to Specific Business Use Cases for Real Results!
Gartner has predicted that, ‘Overall analytics adoption will increase from 35% to 50%, driven by vertical and domain-specific augmented analytics solutions.’ Your business, like every other business in the world, has its own industry, domain and vertical concerns, and these concerns drive your competitive strategy, your products and your services.
Predictive analytics uses sophisticated analytical methodologies to predict future outcomes based on historical data. Using these techniques, the organization can predict future events, customer buying behaviors, and business outcomes. These techniques can help the business drive results, improve revenue, understand customer and client buying behavior, solve problems, plan for new locations and products, create accurate pricing strategies and plan for new resources and training, as well as for appropriate maintenance, supply chain services, etc.
‘Take the guesswork out of the planning process and analyze factors that influence business success. Plan and forecast accurately.’
Predictive Analytics utilizes various techniques including association, correlation, clustering, regression, classification, forecasting and other statistical techniques. These techniques can be targeted to specific business use cases to solve specific, unique business issues and to help the business plan, forecast and compete.
In order to understand how businesses might use assisted predictive modeling and predictive analytics, let’s look at some business use cases and how analytical techniques can help the enterprise derive concise, clear information to support decisions and strategies.
Customer Churn
The cost of acquiring and interacting with customers can be expensive and each time a business loses a customer, it must spend money to replace the customer.
Fraud Mitigation
Businesses must mitigate fraud and control business costs and must develop and sustain fraud detection processes to monitor operations.
Quality Control
Businesses must control quality or risk losing customers and market share and exposing the enterprise to legal risk and liability.
Demand Planning
Take the guesswork out of the planning process and analyze factors that influence business success. Plan and forecast accurately.
Product/Service Cross-Selling
Leverage customer satisfaction to cross-sell and upsell products and services and increase revenue and brand loyalty.
Maintenance Management
Focus on equipment maintenance to ensure that downtime is limited and equipment is up and running, anticipate resources, hours on the job and training needs.
Customer Targeting
Identify the reasons customers buy a product or service and use fact-based data to create products, marketing campaigns, ads and customer outreach. Target specific demographics and customers.
Human Resource Attrition
The enterprise must retain team members and to do so, it must understand what makes a team member stay or go, what makes them invest in the future of he business and what issues create issues and dissatisfaction.
Loan Approval
The enterprise must avoid bad loans, so as to enhance profitability and productivity and it must have a dependable process for identifying and attracting the right clients and for reviewing, approving and managing loans.
Marketing Optimization
Create attainable targets and goals with an understanding of what improves and affects sales and how customers choose a product or service, how to market and advertising to achieve objectives.
Predictive Analytics Using External Data
Integrate external data and analyze data to assess the affect on sales, marketing, finances, resources, productivity, etc.
Online Target Marketing
Optimize marketing funds and resources, understand what works and what does not work, and how, when and where to message and the ideal demographic and profile of the target customer.
Student Academic Performance
Predict academic performance of students to effectively manage student interaction and training and improve environment to assure student success.
Crime Type Prediction
Predict the type of crime that is likely to occur to plan for appropriate law enforcement resources, placement and strategies and ensure public safety and appropriate use of funds.
‘Predictive Analytical techniques can be targeted to specific business use cases to solve specific, unique business issues and to help the business plan, forecast and compete.’
Find out how Assisted Predictive Modeling and Augmented Analytics can help your business plan for success, and explore the potential of comprehensive Predictive Analytics here.
Original Post : Predictive Analytics Business Use Cases Ensure Results!
What Should My Business Consider When Selecting a Mobile BI Solution?
As a business considers the implementation of a BI Tool and access to augmented analytics for its business users, it must define its requirements carefully in order to satisfy its corporate goals and its user needs. In today’s on-the-go work environment, mobile BI and the concept of an augmented analytics app are necessary components of the analytics strategy.
‘Ensure that the Mobile BI solution does not require expensive, extensive customization of dashboards or of the app in order to satisfy your business and user requirements.’
Gartner predicts that, ‘data literacy will become an explicit and necessary driver of business value, demonstrated by its formal inclusion in over 80% of data and analytics strategies and change management programs.’
If the business wishes to encourage data literacy and increase business value, it must carefully select its analytical tools and solutions. In this article, we provide a short list of factors your business should consider when selecting a business intelligence and augmented analytics tool with mobile capabilities.
Support for Devices
Be sure your solution provides mobile support for iOS and Android, with a seamless user experience that accommodates all screen sizes and resolutions.
Out-of-the Box Functionality
Ensure that the Mobile BI solution does not require expensive, extensive customization of dashboards or of the app in order to satisfy your business and user requirements. Features and functionality should be out-of-the-box so you can get started right away.
Access to Crucial Features
Some mobile analytics solutions provide restrictive access and provide read-only limitations, or only display pieces of the information from the data sources. Be sure your Mobile BI App provides intuitive dashboards, graphs, key performance indicators (KPIs), PDF reports and natural language processing (NLP) searching all within the mobile app. Users should be able to login, browse and search objects and perform interactive analytics, with access to ‘favorites’ and recently used objects.
Integration with File Formats
Your Augmented Analytics App should allow users to access objects via PDF and XLS and share data via WhatsApp, email or other sharing apps on their device.
Appropriate Security and Access
The Mobile BI solution should provide access rights and security, defined on a server to ensure security and privacy and access at the correct level, given the user credentials.
Mobile Hosting
Your Augmented Analytics App should be flexible and agile enough to host from anywhere within the IT infrastructure – on premises, or via public or private cloud.
Licensing
Be sure the augmented analytics provider is not charging expensive add-ons for the mobile app. If you currently have a license for augmented analytics, the mobile BI app should be an easy add-on, without expensive fees, and should be easy to download and implement and easy for users to adopt and use right away.
‘In today’s on-the-go work environment, mobile BI and the concept of an augmented analytics app are necessary components of the analytics strategy.’
Explore Smarten Mobile Augmented Analytics And Mobile BI and add powerful functionality and access for your business users with out-of-the-box Mobile BI and advanced analytics for every team member in your enterprise. For more information on Mobile BI and Augmented Analytics, read our articles, ‘Considering A Mobile BI App? Understand The WHAT Of Mobile Augmented Analytics Before You Choose’, and ‘The Importance Of Adding A Mobile BI App To An Augmented Analytics Strategy.’
Original Post : What to Know to Choose the Right Mobile BI Solution!
Imagining the Impact of Citizen Data Scientists!
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.
Power Users and Champions
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.
Business Process Streamlining
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.
Collaboration
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.
Goals and Objectives
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.
Original Post : Imagine How Citizen Data Scientists Can Help Your Business!
The Importance of Adding a Mobile BI App to an Augmented Analytics Strategy!
Many businesses are considering, or have implemented, business intelligence and augmented analytics solutions. According to renowned technology research firm, Gartner, ‘80% of organizations seeking to scale digital business will fail because they do not take a modern approach to data and analytics governance.’ With this prediction in mind, the addition of business intelligence and augmented analytics to the organization workflow, business processes and technology infrastructure is a wise decision.
‘The addition of mobile capability will improve user adoption, support culture changes and extend the office environment for a more productive business and team foundation.’
In order to address the ‘modern approach’ Gartner describes, the business must include a mobile BI and augmented analytics app strategy. In this article, we discuss the importance of including a Mobile BI App in the organizational approach to business intelligence and advanced analytics.
Changing the Culture and Business Processes
With any data literacy and data democratization effort, the business MUST look at culture change. If it intends to encourage business users to transform to Citizen Data Scientist, it must look at all aspects of its culture, business processes and workflow, and to integrate data sources and make that information available at appropriate levels so that users can access and analyze data and IT and senior management can be assured of appropriate data governance. When the business implements a business intelligence and/or augmented analytics solution, it must consider the importance of adding the capabilities of a Mobile BI App so that users can access data from anywhere. By providing mobile augmented analytics, the business can enforce and enable the culture change and modernize its approach to data access and data sharing. Providing restrictive business intelligence or analytics solutions without mobile capability will further inhibit user adoption and act as a barrier to the culture change within teams.
Extending the Office Environment
Over the past decade, businesses have changed drastically and one of the greatest changes is the concept of a ‘team’ or ‘group’ working on a project, or toward a goal. In recent years, the idea of remote workers has grown exponentially, and teams spread across the country (or across countries) and geographic locations are now using software and technology to collaborate and share data. Users want to access data on the road, in a hotel room, while working at a client office or in an airport, and when it comes to analytics, that need is just as great. It is important to provide a solution that accommodates all types of devices from desktops and tablets to iOS and Android devices, so that the user can access data and analytics from anywhere on any device.
Improving User Adoption
When senior management teams announce a new initiative like the adoption of analytics, it is easy for team members to discount the commitment and to believe the new ‘flavor of the month’ will simply disappear and they will go back to the old way of doing things. The culture change we discussed in this article is a necessary component and the availability of the tools, and easy-to-use solutions that require little training is crucial. A mobile BI and augmented analytics app meets the expectations of users for intuitive tools – tools that are accessible as and when they need them, and with simple, powerful reporting and collaborative tools, the users will be encouraged and enabled and user adoption will improve.
There are many other important aspects of mobile BI and augmented analytics. Here, we have provided a few of the crucial considerations a business must include when it reviews its requirements and builds a strategy to implement business intelligence and analytics for business users. The addition of mobile capability will improve user adoption, support culture changes and extend the office environment for a more productive business and team foundation.
‘In order to take a ‘modern approach to BI and analytics, the business must include a mobile BI and augmented analytics app strategy.’
Explore Smarten Mobile Augmented Analytics And Mobile BI and add powerful functionality and access for your business users with out-of-the-box Mobile BI and advanced analytics for every team member in your enterprise. For more information on Mobile BI and Augmented Analytics, read our articles, ‘Considering a Mobile BI App? Understand the WHAT of Mobile Augmented Analytics Before You Choose’, and ‘What Should My Business Consider When Selecting a Mobile BI Solution?’
Original Post : Improve Analytics User Adoption with Mobile BI App!
Can Predictive Analytics Provide Accurate Results for My Business Without Burdening My Users?
If your business is struggling to forecast and predict outcomes and results, your management team is probably considering predictive analytics. The technology research firm, Gartner, states that, ‘50% of data scientist activities will be automated by artificial intelligence, easing the acute talent shortage.’
For the average team member, the concept of predictive analytics may seem daunting and, if you are a business user whose management team has asked you to embrace and participate in analytics, the addition of predictive analytics to your day-to-day business processes may seem irrelevant or it may seem to mean you will be expected to work harder or produce more output. But don’t be too quick to assume the worst.
‘By providing this type of expanded functionality to the team, the business can enable both data scientists and business users with predictive analytics that will benefit the organization.’
Let’s take a look at Predictive Analytics, the benefits of Assisted Predictive Modeling and its importance in the organization and how intuitive augmented analytics can help business users achieve their goals without requiring advanced training or additional workload.
What is Predictive Analytics?
Predictive analytics is comprised of sophisticated analytical methodologies that allow businesses to predict future outcomes based on historical data. Using these techniques, the organization can predict future events, customer buying behaviors, and business outcomes. Predictive Analytics utilizes various techniques including association, correlation, clustering, regression, classification, forecasting and other statistical techniques.
Understanding Assisted Predictive Modeling
When a business provides augmented analytics tools for business users, it allows the team to perform predictive analytics on a daily basis without the assistance or skills of a Data Scientist or an IT professional. Assisted Predictive Modeling provides auto-suggestions and recommendations to guide business users with recommended techniques, selecting the most appropriate techniques for the type and volume of data the user wishes to analyze. If the business chooses an augmented analytics tool with intuitive predictive modeling features, it allows users to work quickly and receive clear, concise results for decision-making so user adoption of the tools is more likely and forecasting and predictions are accurate and timely. All popular predictive modeling techniques are incorporated into the solution, so users have access to the most sophisticated predictive analytics and tools and can use these tools to model and review business use cases and issues.
The Benefits and Importance of Assisted Predictive Modeling
These tools allow the organization to apply predictive analytics to real use cases to analyze customer churn, to target customers, to identify cross-selling and product bundling, to find and set appropriate price points, to forecast where and when to open new locations, when the business will need new suppliers, when equipment will require maintenance, etc. A comprehensive augmented analytics solution also includes the benefit of integration with R Script, so that data scientists can capitalize on expertise and leverage enterprise investments in R open-source platforms, to perform statistical and predictive algorithms, and complex analysis to provide the depth of detail and advanced analytics and reporting the organization needs for strategic decision-making. By providing this type of expanded functionality to the team, the business can enable both data scientists and business users with predictive analytics that will benefit the organization, encourage collaboration and data sharing, and improve data literacy – all without increasing workload or frustrating users and team members.
‘Intuitive assisted predictive modeling and augmented analytics can help business users achieve their goals without requiring advanced training or additional workload.’
Find out more about Assisted Predictive Modeling and Augmented Analytics and explore the potential of comprehensive Predictive Analytics here. Find out how it can improve user adoption of analytics and increase accuracy of forecasting and results.
Original Post : Get the Right Predictive Analytics Tools for Users!
Enable Citizen Data Scientist User Adoption of Augmented Analytics with Business Use Cases!
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.
Customer Churn
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.
Product and Service Cross-Selling
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.
Human Resource Attrition
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.
Original Post : Augmented Analytics Use Cases for Citizen Data Scientists!
Considering a Mobile BI App? Understand the WHAT of Mobile Augmented Analytics Before You Choose!
If your business is considering a Business Intelligence or BI tool or an augmented analytics tool for its business users, the addition of this type of tool can and will improve user adoption of analytics, data democratization and data literacy. As you consider your requirements, your user and technology needs and other factors, do not forget to add mobile BI tools and augmented analytics to your list of requirements. A BI Mobile App will further improve user adoption and fact-based decisions.
By some estimates the Mobile Business Intelligence Market is expected to achieve a Compound Annual Growth Rate (CAGR) of 22.43%
‘If a vendor or solution provides only SOME of the features and functionality business users require, the solution cannot truly be considered a Mobile BI app.’
In this article, we define Mobile BI and the concept of a Mobile Augmented Analytics App, so that your business can achieve a more complete picture of these tools.
Perhaps the best place to start this discussion is to define what Mobile BI is NOT.
What Mobile BI and Mobile Analytics is NOT
A true Mobile BI and Augmented Analytics App should not be restrictive. Limited views and access will only frustrate users.
Real Mobile BI is not just a series of static reports or limited access to data that would otherwise be available from within the walls of the enterprise.
What IS Mobile BI and Augmented Analytics?
Mobile Augmented Analytics is based on a comprehensive advanced analytics solution with sophisticated features, analytical algorithms and functionality designed for business users with average technical skills.
Mobile BI is designed to extend the augmented analytics environment beyond the walls of the enterprise and support remote work, team members who travel and those who wish to work while on the road.
A Mobile BI and Augmented Analytics App accommodates both Android and iOS devices so that users can access features, reporting, data sharing etc., on the device of their choice.
Mobile BI for Business Users is easy to implement and license and does not require extensive training.
Mobile Augmented Analytics provides a functional environment for analytics, extending the features the user leverages within the office on a desktop so that the user can analyze data with full access into datasets, dashboards and reports.
Mobile BI apps must present data appropriately, no matter the size of the screen or the resolution. Navigation must be easy and intuitive.
If a vendor or solution provides only SOME of the features and functionality business users require, the solution cannot truly be considered a Mobile BI app. Implementing data democracy initiatives to support the transition from business user to Citizen Data Scientist requires tools that can be used in a real work environment and that must include true mobile access to a comprehensive set of features.
Remember, your team members are also consumers who are used to access to all their favorite apps no matter where they are, and no matter which type of device they choose to use.
‘A BI Mobile App will further improve user adoption and fact-based decisions.’
Explore Smarten Mobile Augmented Analytics And Mobile BI and add powerful functionality and access for your business users with out-of-the-box Mobile BI and advanced analytics for every team member in your enterprise. For more information on Mobile BI and Augmented Analytics, read our articles, ‘The Importance of Adding a Mobile BI App to an Augmented Analytics Strategy’, and ‘What Should My Business Consider When Selecting a Mobile BI Solution?’
Original Post : What is True Mobile BI?
