Tag: Support for Data Literacy

Key Influencer Analytics Tells You How to Succeed!

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March 19, 2024

Use Key Influencer Analytics to Understand What Factors Impact Success!

Suppose you are trying to understand why a marketing campaign is failing, or what factors cause your customers to buy your services again. What if you need to know whether the color of a product affects the number of units sold in a particular country or area of a country? There are so many variables and components that can affect business success, and understanding the relationship among all the factors of success can seem like a guessing game.

When you are faced with this quandary, it is wise to use analytics to take the guesswork out of the equation. But how do you begin to analyze all the factors at play?

‘Can an augmented analytics tools tell you what algorithm or analytical technique to use? Can it help you understand the relationships of various factors and issues and determine what changes will help you improve the revenue for a product, or help you create a new service package?’

Statistical and analytical experts will tell you that there are three primary factors that can help you decide on the metrics to use for your analysis:

  • The type of data you want to analyze – Understanding the data type can help you decide whether you need to consider a binary approach or look at categories, etc.
  • The character of the data you want to analyze – Are you looking at product attributes, a specific threshold or data range, etc.
  • What you want to accomplish with your analysis – Do you want to identify trends or patterns or are you trying to understand the relationships among the various factors and which factors affect success?
Key Influencer Analytics Helps You Understand Success

…and there is one more critical issue you must consider. Namely, who is doing the analysis? If you want to democratize data and improve data literacy across your enterprise, you will want your business users to understand and use analytical tools. But your team members are not statisticians or data scientists. So, they will need easy-to-use augmented analytics tools.

But can an augmented analytics tools tell you what algorithm or analytical technique to use? Can it help you understand the relationships of various factors and issues and determine what changes will help you improve the revenue for a product, or help you create a new service package?

One of the most frustrating tasks a business user has in analytics is finding and gathering the right data for analysis and ensuring that all factors, variables and data that may affect the outcome of the analysis is included. Depending on the size of the dataset a user selects, there may be hundreds or thousands of variables, and business users often find it difficult to identify the rights ones. Yet without the ability to identify the right variables, the business is likely to measure and attend to the wrong things.

That’s where Key Influencer Analytics comes into play! This approach puts the power and clarity of targeted analytics in the hands of business users and support Citizen Data Scientist initiatives and the critical goals of Data Literacy across the organization.

The user can simply point to the dataset they want to analyze and the system will identify the target and the influencers or predictors that will affect the target, along with its impact and it provides crucial metrics such as mean, outliers, and others and identifies relationship and distribution among variables. The system will auto-suggest relationships and present distribution and impact using the most appropriate visualization.

Users enjoy interactive features that allow them to see and explore other combinations and impacts and can select target and predictors, and use them for models, reports or KPIs. Key Influencer Analytics empowers every business user and allows them quickly select and target data to achieve results without the assistance of a data scientist, IT professional or analyst.

Key Influencer Analytics will:

  • Identify feature importance based on machine learning algorithms
  • Interpret insights in simple language
  • Measure statistics
  • Reveal influencers with impact on the target
  • Auto recommend influencers
  • Identify data relationships with interactive visualization

With these tools, business users can identify what matters most within the data, and how the various factors and relationships impact success, and they can understand the interdependence of variables and leverage auto-suggestions and machine learning functionality to gain insight. Users can also leverage the features within the tool to consider various combinations and the impact of those combinations on the success of the project, product or plan.

‘There are so many variables and components that can affect business success, and understanding the relationship among all the factors of success can seem like a guessing game.’

Find out how Key Influencer Analytics can benefit your business users and support Citizen Data Scientists, and how it can provide an advantage to your data scientists, business analysts and IT team members.

Original Post: Key Influencer Analytics Tells You How to Succeed!

What Citizen Data Scientists DO NOT Need in Augmented Analytics

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March 13, 2024

If you are an IT professional, a business manager or an executive, you have probably been following the progress of the Citizen Data Scientist movement. For a number of years, Gartner and other technology research and analysis firms have predicted and monitored the growth of this phenomenon.

In fact, Gartner predicted that, ‘…40% of data science tasks will be automated, resulting in increased productivity and broader usage by citizen data scientists.’

So, how is it going? It’s actually going quite well.

However, it is worth noting that some businesses have not had the success they expected when implementing a Citizen Data Scientist approach. One of the primary reasons for falling short of results is to set inappropriate expectations regarding the role of Citizen Data Scientists vs. Data Scientists within the organization.

As the Citizen Data Scientist approach gained momentum, businesses seemed to develop an expectation that Citizen Data Scientists could replace Data Scientists. Nothing could be further from the truth. Augmented Analytics and Citizen Data Scientists are not meant to replace refined data modeling or the role of Data Scientists, but rather can supplement and support analytics across the enterprise. The enterprise should not discount the value of strategic data analytics and its place in the organization but rather should see augmented analytics and Citizen Data Scientists as a way to drive fact-based decisions and provide clarity and data-driven actions across the enterprise.

The fact is that there is a place for Citizen Data Scientists within your business, AND a place for Data Scientists and the strategic use of their skills.

What Citizen Data Scientists DO NOT Need in Augmented Analytics

If you want your Citizen Data Scientist initiative to succeed, and you wish to achieve data democratization and data literacy, you must understand how augmented analytics should be used to support business users and organizational objectives. So, let’s dive in and explore this issue further.

AUGMENTED ANALYTICS SOLUTIONS

When selecting an augmented analytics solution, your enterprise must choose tools that are designed specifically for business users with average technology and analytical skills. Easy-to-use, intuitive tools will ensure user adoption. If you choose business intelligence or advanced analytics tools that are meant to data scientists, IT professionals or business analysts, you are setting your team up to fail. These tools are focused on the needs of Data Scientists. The tools are powerful and can produce undeniable value in the right hands, but they are not designed for your business professionals. To use these tools, users must manually gather and prepare data, scrubbing, cleaning, etc., and then write complex queries and use complicated algorithms and analytical techniques. Users must be expert in R programming or in Python or other scripting and programming languages. In short, this kind of software, app or solution is not for the feint of heart, and it’s certainly not suitable for a Citizen Data Scientist.

The right business user solution is an augmented analytics should be designed with all the tools a business user needs to get swift, dependable results.

  • Self-Serve Data Preparation
  • Assisted Predictive Modeling
  • Smart Data Visualization
  • Machine Learning and Natural Language Processing (NLP)
  • Clickless Search Analytics

EXPECTATIONS AND RESULTS

Once you have chosen the right augmented analytics solution, you must establish appropriate expectations.

Optimize Citizen Data Scientists And Data Scientists

MANAGERS AND EXECUTIVES SHOULD NOT EXPECT CITIZEN DATA SCIENTISTS TO BE DATA SCIENTISTS

That is not the purpose of this strategy. The purpose of a Citizen Data Scientist approach is to give your team members tools that will allow them to discover trends and patterns, and to gain insight into what is working and what is not working in their current process, workflow and in their day-to-day activities. If and when an issue is identified that will require adapting a strategy or a major goal or objective, the enterprise must have a process in place that will allow a team member to refer her/his research to a Data Scientist, IT team member or other analytical professional, where the initial analysis will be refined and studied for use in strategic goals. When a Citizen Data Scientist uses augmented analytics, they should not be expected to perform complex modeling or to establish predictive models that will be rolled out in production mode or dictate a new strategy.

CITIZEN DATA SCIENTISTS SHOULD FOCUS ON HYPOTHESIS AND PROTOTYPING

If a business user/Citizen Data Scientist discovers an issue or an opportunity, that user can explore the issue, look for relationships among the variables and factors that affect success and failure, develop an understanding of the challenge or the possibilities for product bundling, changing a marketing campaign, etc., and then share and collaborate with the team to further analyze and discuss the issues. It is this day-to-day access to analytics and clear data that will allow business users to make fact-based decisions and to build an understanding of data and analytics and how the information contained in data repositories and software systems can be integrated and analyzed to gain more clarity and to provide real metrics and measurements, so decisions are based on facts, rather than guesswork and opinion.

Role – Day-to-day business decisions, team collaboration and data sharing.

Benefits – Improved team collaboration, improved data literacy and perspective, improved business agility, timely decisions.

DATA SCIENTISTS SHOULD FOCUS ON STRATEGIC GOALS AND DATA REFINEMENT

Most organizations cannot afford a team of Data Scientists and, even if they could, they do not want those professionals pulled away from crucial, strategic focus by day-to-day requests and projects that have short-term outcomes and importance. Rather than trying to replace Data Scientists within the business, the enterprise can optimize their time and reduce the need to hire more resources, by improving focus and enabling a workflow that allows them to concentrate on those areas that will reap the most benefit to the organization.

Role – Analyze and refine data for 100% accuracy and strategic use, act as expert, statistical expert.

Benefits – Focus on strategic issues with fewer day-to-day requests, collaborate on projects that require data refinement for 100% accuracy, focus on mature modeling requirements.

When an organization sets out to leverage the Citizen Data Scientist approach, it can ensure success by taking the time to plan appropriately AND by establishing appropriate expectations for how and when business users will engage in analytics and the results they can and should produce. When an organization understands the true meaning and purpose of the Citizen Data Scientist role, it can incorporate this strategy and align business users and Data Scientists to achieve greater collaboration and synergy.

Be sure you choose a vendor with comprehensive augmented analytics features and functionality designed specifically for business users, to support the transition of your business users to Citizen Data Scientists and ensure that your project will succeed. Contact Us to find out how we can help you plan and achieve your goals. It really IS possible!

Original Post: What Citizen Data Scientists DO NOT Need in Augmented Analytics!

Yes! Digital Transformation DOES Improve Results

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July 19, 2023

Digital Transformation Improves Results…As Reported By Businesses!

According to a survey of businesses regarding Digital Transformation (Dx), 40% of respondents reported improved operational efficiency, 35% reported that it was easier to meet changing customer expectations, 26% said Dx improved product quality, and 24% said Dx reduced product development costs.

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Yes! Business Users Can Love Digital Transformation (Dx)

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July 3, 2023

Some Reasons Your Business Users Should Love Digital Transformation (Dx)!

When it comes to implementing a Digital Transformation (Dx) initiative, your IT team and senior executives probably don’t need convincing! Consider the recent IDC survey results about Dx:

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Achieve Digital Transformation Without Missteps!

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May 26, 2023

To Succeed with Digital Transformation, Understand the Obstacles and Engage a Partner!

When a business makes the decision to take on a Digital Transformation (Dx) initiative, there is a lot of planning involved. The enterprise cannot simply declare its intention and leave the rest to fate. It must plan carefully and include all crucial components if it hopes to succeed and to launch this initiative in a timely manner.

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Digital Transformation is Not a Short-Term Strategy!

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April 21, 2023

Digital Transformation Provides Long-Term Growth and Support Benefits!

The term ‘Digital Transformation, or Dx, is everywhere today. If you have heard the term, but you’re not clear on its meaning, Digital transformation is a business initiative that adopts a customer focus by taking a digital or technology-driven approach to business. This approach includes business processes, software and solutions used to create concepts or products, complete tasks, work through approvals, manage projects, monitor, and manage suppliers, equipment, teams, etc. In short, every aspect of the business from business structure and models to customer interaction and operations. Digital Transformation technologies may include artificial intelligence (AI), ERP systems and solutions, private or public cloud environs, and digital solutions for augmented analytics, BI tools, workflow management, HR, product design, etc.

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Digital Transformation Must Include Current and Future Staff!

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March 29, 2023

In recent studies, 49% of the organizations surveyed about Digital Transformation (Dx) initiatives reported that Dx gave the business the ability to better manage business performance through data availability. When it comes to Digital Transformation strategies, the wise enterprise knows to involve its team members in the requirements planning and in planning for execution and transition.

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Should My Business Focus On Digital Transformation?

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March 28, 2023

Just Some (of the Many) Reasons to Undertake Digital Transformation (Dx)!

According to an Accenture study, ‘30% of companies are still considered laggards in technology adoption and innovation.’ Hopefully, your organization is not among those laggard companies! Digital Transformation (Dx) is important for many reasons, not the least of which is competitive positioning. If your business is not actively working on improving its digital response, work processes, approval procedures and customer interaction, you are already behind the competition!

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Data Democratization is Important. So Are the Right BI Tools!

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March 16, 2023

Select the Right BI Tools and Succeed with Data Democratization!

Do you know what Data Democratization is? It’s simple, really. Data Democratization is the purposeful approach to cascading and integrating data into the daily workflow of business users to provide access to crucial information and the tools to analyze and understand that data and use it to make confident decisions. Instead of holding data in silos that are only accessible to IT, business analysts, data scientists and management, the enterprise recognizes the value of providing team members with the right information to do their job and contribute to the bottom line.

‘To succeed in data democratization, you need BI tools that provide data analytics access for all business users.’

Gartner predicts that, ‘75% of organizations will…deploy…multiple data hubs to drive mission-critical data and analytics sharing and governance.’ The key here is the ‘analytics sharing’ piece of the statement!

In order to fulfill the promise of this approach, your enterprise must employ business intelligence solutions that are easy-to-use and designed for business users, without advanced technical skills or advanced analytical skills. These tools allow your team members to engage in analytics and enjoy data democratization without the frustration of leveraging solutions designed for data scientists or IT staff.

Data Democratization Can Succeed with the Right BI Tools

Here are a few considerations to give you an idea of the kinds of things you will need to support your data democratization initiative. These factors are crucial to success, as they ensure that your users can and will adopt the BI tools you select to enjoy the new data access you have given them. Without these, you run the risk of spending the time and money to provide access and achieving poor return on investment (ROI) because of poor user adoption.

Embedded BI – By embedding business intelligence into the enterprise apps your users love, you can encourage data democratization and analytics in a single sign-on environment. Users do not have to sign in to multiple systems or move data around. They can start with the data within the ERP, HR, Finance or other system and perform analysis from within that system. Make it as easy as you can, and users will be happy!

Mobile BI – Don’t make your users sit at their desk in an office to use the BI tools. Make these tools accessible from the office and on the road, at home and in a client location or hotel. If you want your users to see the value in data democratization and you want to achieve your goals for this initiative, you must give your users the tools they need WHEN THEY NEED those tools.

Business Intelligence with Seamless User Access and Security – Data democratization does NOT mean throwing caution to the wind. Data must still be secured and accessible to users for the things they need to see, but not for the things they are not eligible to see and not in an environment where data security and privacy are at risk. To democratize your data, you must also ensure data governance, security and access standards and requirements are met.

Natural Language Processing – Make the augmented analytics and BI tools intuitive. Democratized data is no good if the users need an advanced degree to access the data. Natural Language Processing (NLP) allows your users to access data in a familiar way, with a Google-type search interface where they can ask questions using regular language and receive answers in a way that is easy to understand. If they can search, query and find information easily, they are more likely to a) use the system and b) understand the information they produce and make the right decisions.

Tools Designed Specifically for Business Users – The solution you select should be designed for business users, not for data scientists, business analysts, IT or statisticians. While you want the data democratization initiative to expand the skills and knowledge of your team, you do not want them to need advanced skills or training. Select a system that can be adopted and used within minutes – not months. Users want sophisticated functionality in an easy-to-use environment. That is important!

‘If you want your data democratization initiative to succeed, select tools that allow your team members to engage in analytics without the frustration of leveraging solutions designed for data scientists or IT staff.’

There are other considerations but, if you address the ones we have highlighted in this article, you will be well on your way to achieving your data democratization goals and ensuring that your users adopt the solution you select.

BI Tools should provide data analytics access for all business users. Simple, Self-Serve BI Tools can provide your business with the foundation to achieve your data democratization and user adoption goals. Let us help you achieve your vision and improve productivity and insight across the organization.

Original Post : Data Democratization Can Succeed with the Right BI Tools!

Digital Transformation Includes a Thorough Technology Review!

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March 2, 2023

What Technologies Should I Include in My Digital Transformation (Dx) Strategy?

Deloitte reports that ‘The implementation of digital technologies can help accelerate progress towards enterprise goals such as financial returns, workforce diversity, and environmental targets by 22%.’

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