Reality Check: You’re Spending Too Much Time Searching for Information

The great Benjamin Franklin once said, “Time is money”. Even though he uttered these words in the 1700s, the sentence still rings true today. Timing is everything in business – how quickly a product can be manufactured, shipped and bought, all play vital roles in the direct success of a company. When that product is put out to the market and sold is crucial. 


The same principle applies to analytics – timing is integral to the efficient absorption and utilization of data. For example, if you are in a meeting and you are presented with interesting data/information but it is not relevant to the current topic or project at hand, then that data is simply a distraction in the moment; no matter the quality of that information. If it does not play an active role in pushing the needle forward, then it is inefficient analytics. 


What are personalized data stories? 


Personalized data storytelling is when data is transformed into an easily digestible message that anyone can understand, using advanced machine learning technology and augmented analytics. This message is usually presented in a customized manner using images, audio or any other creative AI means.


Personalized data stories are an up-and-coming technological advancement that has proven to help mitigate this inefficiency and according to many experts, will be the most used analytics method in future. With the speed of digital transformation, now more than ever, every employee should be empowered with some sort of personalized data to make confident data-driven decisions. 


Why are personalized data stories important?


Too often we are stuck sifting through data and other insufficient analytics platforms looking for what we need at any given time. According to recentresearch, “19.8% of business time – the equivalent of one day per working week – is wasted by employees searching for the relevant information they need to do their jobs”. 


Tools must be aware of users’ contexts – who they are, what they are asking, why they’re asking, and when they are engaging. Contextual understanding is crucial for delivering the most important information so leaders can decide and act at a particular moment. It also mitigates the possibility of integral information slipping through the crack.  


Advanced data analytics platforms and AI assistants, or data translators, have the ability to understand your goals, user roles, and specific challenges you are tackling at the moment in order to drastically improve your efficiency as an employee as well as the efficiency of the organization as a whole. 


To learn more about how your organization can employ personalized data storytelling to improve business outcomes, contact info@conversight.aior request a demo.

Augmented Analytics and Creative AI are Closing The Data Knowledge Gap

What is Augmented Analytics? 


Augmented analytics is an approach to data analytics that employs the use of enabling technologies such as machine learning, artificial intelligence and natural language processing to automate analysis processes such as data preparation, data processing, insight generation and insight explanation; all of which are tasks normally completed by an analyst or data scientist. Simply put, it is used to increase the depth in which people explore and analyze data in business intelligence and analytics platforms through automating data storytelling. Unfortunately, for many companies, especially small businesses, there is a shortage in data scientists that has created a growing skills gap required to employ data stories and use them in their decision making processes. Read on to learn how augmented analytics can bridge this knowledge gap and finally allow anyone within an organization to gain value from data insights. 


What is Creative AI? 


Recent Improvements in machine learning techniques, such as deep learning and neural networks, have enabled AI to generate imagery, video, text and audio content. Creative AI is when artificial intelligence uses past data to learn from an experience, allowing it to fine tune itself and generate new solutions and recommendations through audio and visual techniques. It ultimately helps in personalizing the output of data insights in a medium that makes the most sense for the end user, overall creating more value in the mass amounts of data businesses collect. 


How do they work together? 


Companies of all sizes and industries can use augmented analytics, combined with the power of Creative AI, to transform their organization at all roles to gain a deeper understanding of its data and analytics. According to recent research by Gartner, augmented analytics is a disruptive trend that will be a key component in the future of data, and that data and analytics leaders should plan for new Machine-Learning/Artificial-Intelligence based data storytelling capabilities that will automate tasks and drastically transform how analytics as a whole is done. In fact, according to another article, by 2025, 75% of data stories will be generated using augmented analytics and creative AI techniques.  


To learn more about how your organization can employ augmented analytics to automate tasks and improve decision-making process, contact info@conversight.aior request a demo.

3 Reasons Your Business Should Redefine its Relationship with Data

In today’s market, supply chain leaders use data and multiple different quantifiable methods to improve decision making processes across all sectors of their business. Insights and analytics have become an integral ingredient for any business to succeed in their industry. Whether they utilize spreadsheets, dashboards, augmented or predictive analytics, every company can benefit from observing their data through an analytical lense, however, the extent to which they understand that data and then put it to use will determine how accurate and agile their decision making is.


According to recent research, “82% of supply chain employees have used or use dashboards frequently in the workplace”. Why is this particular method used so often? How do dashboards enrich the decision making processes? Simply displaying data in charts or graphs just isn’t enough to get an advantage in today’s challenging supply chain ecosystem, especially since too often these dashboards are disregarded or revolve around stale or inaccurate data. 


Many data and analytics experts say, in the future, data storytelling will be the most utilized analytics method. Why? 

1. It enables users to absorb and understand data with more efficiency than ever before. By directing the user to the most important aspects of data, deeper analytics offers interpretations that may have missed or never seen previously. 


2. Data storytelling makes insights more accessible than ever.  Previously, this type of analysis was exclusively reserved for the massive or lucrative corporations that have the resources to employ data analysts that spend hours drafting up visuals and presentations in order to convey the important values that they see within the huge amounts of data that they sort through on a daily basis. Now, with the aid of advanced technologies like AI assistants, voice and visual storytelling relays only the most important data through bite-sized insights that are both personalized and contextualized to the user. 


3. Advanced artificial intelligence and natural language processing has transformed data storytelling into a more efficient analytical method. By combining these two technologies, people are able to talk to their systems directly and extract significant values from their data without the need of a data analyst nor the skills of one – bridging the gap in markets and giving even small businesses the chance to harness their data and make better business decisions from it. 


To learn more about how AI and data storytelling can transform your business’ insights and analytics, contact info@conversight.aior request a demo

Why Analytics is Making The Shift From Dashboards to Data Storytelling

When it comes to analytics, dashboards have historically been the simplest way to convey and absorb data. Everyday mass amounts of data is processed into reports and dashboards – but how much of this data translates into impactful insights or valuable outcomes? According to a recent report by Exasol “52% of business leaders and data professionals say dashboards are being disregarded because they’re not getting the message across”.


Dashboards and reports are helpful, but alone, they do not enable data-driven decisions at the speed and scale that are often required for business agility and growth. Therefore, business leaders are turning towards alternatives towards modes of data delivery that are more personalized, automated and contextualized. 


Data is the most valuable asset businesses possess, which is  why the critical shift away from stale dashboards toward methods of vivid data consumption is more important than ever –  So what is the best way to convey data’s valuable information if dashboards are ineffective? – Data Storytelling 


What is Data Storytelling?


Data storytelling is when a narrative is built around a set or sets of data and its accompanying visualizations in order to present the meaning of that data in the most effective, personalized and efficient form possible. As an upgrade from routine, high maintenance dashboards, data storytelling surfaces the need-to-know insights unique to the user to intricately display patterns and deliver information in the exact way the audience or user requires. According to a recent Gartnerreport,  “data stories will be the most widespread way of consuming analytics by 2025”.


Benefits of Data Storytelling 


  • Allows decision makers to make decisions faster with more direct and personalized insight than ever before
  • Delivers an intuitive understanding of  data, delivering depth  that dashboards can’t.
  • Communicate the value that is in your data in simplified and efficient ways (text, audio or visual- providing interpretations you may have never considered before. 
  • Creates a level of transparency and accountability to the key metrics and performance of an organization that may have previously been hidden or overlooked by layers of dashboards
  • Data is presented in a tactical, consistently moving manner compared to static never-changing charts or images 

To learn more about how your business can begin deriving insights and outcomes from data storytelling, contact info@conversight.aior request a demo

Augmented Experiences are Shaping the New Supply Chain

As supply chains become more complex, they create the need for more streamlined approaches for reporting and analyzing. As businesses react and evolve to the long-term effects of the COVID-19 pandemic, efficiencies in operations and analytics are brought into focus revealing an overwhelming lack of timeliness, cost-efficiency, and organization across supply chains. Gartner predicts that by 2023, “overall analytics adoption will increase from 35% to 50%, driven by vertical- and domain-specific augmented analytics solutions.” Read on to learn how augmentation, a performance of artificial intelligence, is a front running technology in aiding supply chains in their digital transformation.


Today’s traditional reporting software is unable to keep up with the demands of fast-paced operations. Most reporting tools require a developer to configure reports, which leads to added costs and unnecessary time in waiting for clear and succinct results. With the introduction of augmentation in these processes, supply chains are able to automate the supply chain to develop reports, automate time consuming, repetitive tasks and eliminate countless hours and costly resources.


Supply chain planners typically analyze business’ inventory, as well as supply and demand lead times, to make more informed, educated decisions. Artificial intelligence agents, like’s Athena, augments this analysis to provide recommendations on purchase orders, inventory levels and more.


Once reports are developed, decision makers are able to easily and quickly to gather insights and summarized information on their supply chain to answer user questions such as:

  • “Did my price increase?”
  • “How many orders did my customers purchase?”
  • “What are our daily sales?”


Additionally, the augmentation of business user’s analytics allows for proactive monitoring of specific inquiries and data. Issues or anomalies are caught early on before turning into costly, long-tail errors.


Human reporting is becoming a tool of the past, as the automation and augmentation of the supply chain through artificial intelligence creates more efficient, smoother transitions for the process of reporting, analyzing, and recommending. Additional research by Gartner, states “organizations that seize the opportunities presented by the newly catalyzed market will be able to dramatically hasten their analytics-related maturation, which could potentially enable them to make competitive breakthroughs, in comparison with slower-maturing rivals.” How does your supply chain shape up to the defined status quo?


To learn more about ways your business can improve reporting times and optimize operations, visit

Conversational Intelligence | What You Need To Know

Last week, Microsoft took on a $16 billion dollar acquisition of Nuance, a speech recognition company. Conversational AI has the ability to transform the way people interact with technology, as the adoption of this speech-recognition software encourages the streamlining of data management.


Strategic acquisitions such as these are especially significant in the world of speech and language recognition software and its impact on the businesses across verticals and industries. As larger-scale companies, such as Microsoft, begin to implement speech recognition software into their own companies, it points to greater growth and development within the industry. Not only will the use of AI continue to increase in big-name businesses, but attention will continue to be drawn to the exponential power of conversational AI and its applicability to the everyday user across businesses of all sizes.


Conversational AI interfaces understand the context and intent of business questions by leveraging machine learning, data science, knowledge graphs and cognitive techniques. Enterprises are then able to create advanced dialogue systems that utilize memory, personal preferences and contextual understanding to deliver a realistic and engaging conversation with data sets.


Success in deploying conversational AI in the business needs key skills, not just technical, but mostly business domain & subject matter knowledge. Conversational AI bots need to understand the domain and speak the domain, not just English. That’s where the domain-focused business platforms like, which is empowering Supply Chain leaders, are emerging.’s powered intelligent business companion, Athena, understands user behavior, context and intent of the conversation to deliver personalized insights and action. There are two primary technology components to the Athena platform 1) the data ingestion and knowledge creation and 2) the process by which end-user queries are answered.’s characteristics includes:

  • Connect to multiple data sources, both structured and unstructured
  • Integrate with online applications through web services and APIs
  • Access to insights through narratives and questions (e.g., supply chain metrics)
  • Uncover data anomalies through data science
  • Provide personalized proactive-insights
  • Retrieve information (e.g., product searches)


To discover how your supply chain business can improve productivity and efficiency through the use of speech and language recognition, contact or request a demo.