Conversational

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 ConverSight.ai’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 https://www.conversight.ai/supply-chain-optimization/

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 ConverSight.ai, which is empowering Supply Chain leaders, are emerging.

 

ConverSight.ai’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.

 

ConverSight.ai’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 info@conversight.ai or request a demo.

Is Your Business Data Rich and Information Poor?

You may be familiar with buzzwords commonly used in the tech arena like big data, data lakes and data warehouses but with all of the emphasis placed on gathering data, what does it mean to be data rich? Data richness qualifies as having a large stockpile of data in which there are hundreds of thousands of pieces of information. As we hear more about businesses working closely with data, it is important to realize that simply having a lot of data may not be enough to make a business successful.

 

It’s great to have data from every corner of your business, but if it’s not being used to make decisions, it can be more of a burden than an asset, not to mention incredibly overwhelming. Databases that hold massive amounts of information are extremely expensive, and often lack organization and tools to interpret the data — arguably making it all a big waste of time and effort to manage and maintain.

 

When large amounts of data is collected every day, every minute and every second — but there isn’t a clear way to sort through or analyze it, organizations are considered data rich and information poor.

 

Here are some strategies to deploy in an effort to achieve information richness that leads to better decision making and growth:

 

Conversational Analytics 

 

There are several types of analytics that can be employed to interpret mountains of data, but conversational analytics are convenient. Some say using conversational analytics are user-friendly because there is relatively no training required, allowing a wide range of employees to use it, leveraging the language and words they are already using on a daily basis.

 

Collaborative Analytics 

 

One thing to keep in mind is that these insights, however they’re being created, aren’t just for business executives and the C-Suite. When everyone in the organization has access to data insights, roles at all levels are empowered to make better decisions while performing the smallest to largest tasks. This triggers a cultural shift within organizations to stay informed and make accurate decisions — from all areas of the operation.

 

Proactive Insights 

 

Proactive insights can be considered the most important form of business statistics. Staying up to date on the direction of data trends (good or bad) is vital to business growth. Proactive insights are here to illustrate what is going on with your business in real-time so bad trends can be stopped before they make an ugly mess, and can even be course corrected to exponentially grow in the right direction.

 

In order to move in an information rich direction, organizations should prioritize putting a data management strategy in place. While data is collected, insights should be shared among teammates to encourage knowledge sharing that everyone can benefit from. Increased access to data will help your business grow in the right direction while paving a new path that encourages data-driven decision making and proactive insights.

 

Interested in learning how your business can gain proactive insights through conversations with your data? Request a demo with a ConverSight.ai expert today.

5 Ways Conversational AI Increases Productivity and Efficiency in Supply Chain

Conversational artificial intelligence (AI) is changing the way people interact with technology. It takes natural language processing and allows enterprises to create advanced dialogue systems that utilize memory, personal preferences and contextual understanding to deliver a realistic and engaging conversation with data sets.

 

The logistics world uses massive amounts of customer data that changes daily, requiring a great amount of inter-team coordination and organized workflows. The end-to-end process of inputting, tracking and completing orders is  time consuming, laborious and vulnerable to human error. As distributors continue to incorporate smart systems that leverage artificial intelligence and machine learning, they are depending more on automated assistants to get the job done.

 

Here are the top 5 ways conversational AI is transforming supply chain operation:

 

Automates Repetitive Tasks

 

Conversational AI removes the complex user interface to enable users to engage with technology in a human-like contextual conversation. As a result, the user gets personalized responses to their queries. Layered into this streamlined interaction with data is the added ability to uncover valuable insights within seconds. Automated reports and checklist take the laborious steps and research out of recurring report generation, saving minutes and hours for users on a daily basis.

 

Improves Workflows Between Users 

 

Conversational AI makes communication between teams and customers a seamless experience. The user simply asks a question and receives insights based on context and keywords. This automated interaction shaves significant time off of the order process from start to finish. By making data easily accessible to various roles within the supply chain hierarchy, data can easily be manipulated and analyzed at any given time.

 

Acts As A Data Watchdog 

 

AI does the back-end work for supply chain that historically requires several teams and a sharp eye on inventory tracking. The predictive element of conversational AI delivers alerts on errors or anomalies found in inventory. In cases of delay in delivery and incidents, teams receive alerts and act instantly, saving valuable time and resources before an error grows and begins to impact other areas of the supply chain.

 

Increases Visibility Into Inventory 

 

In logistics, visibility into all stages of an order are of utmost importance. AI is creating more visibility than ever into inventory on hand, turnover and velocity. Predictive monitoring on cycle time and age of inventory is also saving several steps and takes the guessing out of ordering. With the added conversational abilities, actions are completed through natural language or voice commands making real-time updates on products readily available.

 

Reduces Quality Issues and Increases Customer Satisfaction

 

With increased visibility comes the ability to prevent small errors or quality issues from turning into large problems that impact customer satisfaction. Product managers can leverage AI for end-to-end inventory management and demand schedules can be proactively predicted to make sure that resources are allocated efficiently. Teams can manage sales orders from start to finish while seeing accurate and correct quantities to meet quality and compliance expectations.

 

As conversational AI and other emerging technologies are integrated into supply chain and distribution operations, all aspects of the supply chain will evolve to users interacting with technology like they would with a human. The result is an added ability to find answers from multiple complex data sets in real-time, allowing valuable resources to be spent in higher revenue generating functions of the enterprise.

 

To discover how your supply chain business can improve productivity and efficiency through automation, watch this video or contact info@conversight.ai for a free trial today!

Top Tech Trends to Watch in 2020

With digital transformation, 5G implementation, automation, and data accessibility top of mind for the modern day business, 2020 won’t disappoint as existing technologies evolve and new emerge. Here is a hot take on the top trends to watch as we gear up for the new year that is sure to be filled with innovation and the digital transformation of enterprises.

 

Hyperautomation

 

According to a study by Gartner, by the year 2020, over 40% of data-based tasks will be automated with no sign of adoption slowing. This top trend ecompasses the use of technology to automate tasks that once required humans, with the goal of incorporating AI-driven decision making across an organization. This includes analytical components that accomplish things like data discovery, analysis, design, automation, measurement, monitorization, and reassessments.

 

Data Democratization

 

Democratization of technology and data, also referred to as “citizen access,” gives the average user easy access to technical and/or business insights. Organizations that implement a democratization strategy save significantly on extensive and expensive training of their workforce.

 

AI-Powered Voice Commands

 

The rise of the AI voice assistant within organizations continues to grow in adoption as businesses strive to make more informed and intelligent decisions that have significant impact on operations, customer service, and sales. In fact, comScore predicts 50% of all searches will be done by voice in the new year.

 

Predictive Modeling

 

With the help of predictive modeling, any organization can use past and current data to accurately forecast trends and behaviors second, days, or years into the future. As a result, organizations can reach their goals faster and more efficiently and attract, retain and nurture their most valued customers.

 

Conversational Analytics and Natural Language Processing (NLP) 

 

Another Gartner study predicts that by the year 2021 over 50% of analytical queries will either be generated via search, natural language processing, or will be automatically generated. This trending technology gives business people an easier way to ask questions about data and in turn, receive an explanation of the insights. Check out our use case video on the impact conversational AI has in a warehouse setting to see it in action!

 

Are you a company looking for ways to empower your users with real-time insights and actions through conversational AI? Contact us here to learn how we may be able to help. 

How To Empower Your Sales Team Through Data

Data. Everyone’s talking about it, and everyone – even small businesses – gather inordinate amounts of it every day. For many companies the data just sits there – likely in their POS, CRM, ERP or WMS systems.

 

Sad thing is, most people know there is a lot of valuable information in that data. For this discussion, let’s focus on CRM platforms.

 

Ask a group of sales-related folks how many like their current CRM, and you’ll see few hands raised. Then ask how many realize the value of the information within their CRM, and you’ll see most, if not all, hands go up. So what’s the problem?

 

Specifically, CRM data entry and retrieval in some companies takes upward of 25 percent of the sales team’s time. Conversely, a recent Forbes study shows salespeople spend only 22 percent of each day actively selling, defined as time spent on the phone, emailing or face-to-face with a customer or prospect.

 

Apparently, the remaining 53 percent of time is spent in meetings, other administrative tasks or on personal distractions (social media, calls, etc.). Since those items are under each company’s control, there’s not much we can do about that as a group.

 

But what if we could take that 25 percent spent on the CRM and cut it down by even five percent, giving salespeople more time with customers and prospects? In a full-time work year, that’s an extra 104 hours with clients and potential clients for each sales team member. Multiply that across a sales team, and that’s a lot of potential revenue lost due to menial, administrative tasks.

 

So how do we shift that five percent? In our company, we empower each member of our sales team with a business companion, but not the kind that sits at a desk and answers phones. Our companion’s name is Athena, and she is the virtual voice behind the ConverSight.ai platform.

 

Athena helps each member of our sales team use their mobile device or desktop to retrieve information from our CRM including sales goals, customer notes, deal opportunities, upcoming meetings and any other information available in the data – simply through a voice request or typed chat.

 

What’s more, Athena allows our SDRs, sales managers and directors instant access to this data in the form of reports, pinboards and so much more. No more added expense for outsourcing report creation, and no more lag time waiting for someone in the IT department to extract this information and build a report.

 

And the best part – Athena does this for about half the cost of an FTE. While she helps in sales, she also assists in the manufacturing facility, warehouse, logistics and transportation. And she never takes a break.

 

If you aren’t yet using a business companion on your team, you should look into one.