Case Study : Augmented Analytics for a leading Pharmaceuticals Company in Gujarat, India

The client is a leading publicly listed Pharmaceuticals Company with a large shareholder base. The company manufactures all major dosage forms such as Tablets, Capsules, Injectables, Syrups, Ointments, etc.

Case Study : Augmented Analytics for a leading Construction & Infrastructure Development Company in India

Founded in 1982 as a construction company, client has successfully positioned itself amongst the top 10 construction & infrastructure management companies in India. Client has to its credit many prestigious projects in the Industrial, Power, Institutional & Infrastructure sectors across India.

Context-Driven Natural Language Processing (NLP) Beats ‘Dumb’ NLP Every Time!

If you are an avid reader of technical research or industry journals, you probably know about Natural Language Processing or NLP. If you don’t know about it, you certainly use it every day – whether you know it or not! When you search using Google, you are using natural language and that makes it easier for you to develop a question and get an answer. Ask a question and get an answer. It’s that simple!

But, when it comes to analytics, NLP is typically much more restrictive. Talk all you want about machine learning and natural language processing but the boundaries and restrictions placed on these concepts in a typical analytical solution do not make it as easy as business users might like.

Remember that your business team members are also consumers outside the walls of the office and they use and appreciate the ease of Google searches. Here, a consumer might ask, ‘how many ounces in a pound’, or ‘what is the tallest building in the world’, and they get an immediate answer. THAT is what they want in analytics as well and if you don’t give it to them, they are unlikely to adopt the analytical tools you invested in or to achieve the results you wanted for optimizing resources, improving productivity and, most importantly, engaging in fact-based decision making that will improve the business bottom line.

So, what, if anything can one do about the disconnect between the ease of use of analytics and the typical NLP solution? To answer this question, we first need to understand the difference between standard natural language processing in analytics (AKA Dumb NLP) and context-driven searching using natural language processing (AKA Intuitive NLP).

Context-Driven Natural Language Processing (NLP) Beats ‘Dumb’ NLP Every Time

Context-driven natural language processing allows people to think and communicate like people – not like machines! It is intuitive and ‘smart’ and goes far beyond ‘dumb’ NLP.

Dumb NLP: The use of NLP in analytics provides the basic foundation to get a user into the details of the data and allow them to choose and filter using columns and filters. It recognizes the data in the column or field but not the context. Much like a text to speech solution, it can read, translate and present the data but it has no real understanding of what the data means. Users often get frustrated when they try to use these tools because they have to wade through the choice of columns, click on menus and sift through scripts and when the NLP query results are presented, they may discover that they did not get what they wanted because they omitted or included some inappropriate data.

Intuitive NLP: Context-driven natural language processing allows the user to think of a question and ask that question in a way that supports human thought, and natural communication. Context-driven NLP ‘understands’ and interprets the question and the user intention so, for example, if a user wants to find sales results for a product sold during the ‘Thanksgiving’ season, they do not have to know the date for a particular year or years. They can simply ask the question. ‘How many donuts were sold in Scottsdale, Arizona during Thanksgiving 2019 and 2018? The system will understand the question and interpret it to provide the right information.

Much like your best friend can understand your intent and respond to a question without your being concise or detailed, context-driven NLP can handle the subtleties and the context without the need for excruciating detail and restrictive programming or scripting.

Ask, ‘What was the best day of bakery sales in Tucson Az last year?’, and the system will know that, a) the ‘best day’ means best day of sales for you, that b) bakery sales means all items that fall within the bakery category in your product portfolio, such as cake, brownies, croissants, cookies, bread etc., c) that Az means Arizona and that d) last year was 2019. Just ask the question…and you will get an answer. It’s that simple.

Context-driven, intuitive NLP provides many opportunities to ask questions and handles many concepts, including,

Synonyms, Phonetics and Abbreviations – Enter question and the system will recognize and process information correcting for spelling errors, abbreviations and related words.

Geography, Places and Persons – Enter a question and allow the system to identify a person or place automatically, and give the answer in context of person or geo location.

Time Series – Enter a question and receive results based on absolute time, or on a range or relative time period.

Rank and Polarity – Enter a question and receive results based on a determination of ‘higher’ or ‘lower’ results.

Aggregation – Enter a question to understand results for averages, minimum, maximum, first, last, sum, counts, etc.

Comparison – Explore how sales or other factors compare from one region, year or variable to another.

Context-driven natural language processing allows people to think and communicate like people – not like machines! It is intuitive and ‘smart’ and goes far beyond ‘dumb’ NLP by offering tools that users will want to leverage and interacting with users in a way that is meaningful to them. Your business users don’t need have to use or understand sophisticated skills to create a query or ask a question. They don’t have to wade through five or ten steps to create a query. With context-driven NLP, users just have to think of a question and type that question and they will get the answers they need.

Make your business more productive, optimize resources, empower your team members and allow them to make confident, fact-based decisions and to solve problems and get the information they need to do their job – without stress or time-consuming training or procedures! THAT is the difference between using ‘dumb’ NLP and using intuitive (context-driven) NLP in analytics.

BI Tools Provide Benefits and Challenges!

Understand the Benefits and the Challenges of a Business Intelligence Strategy!

If you follow industry and business publications, you know that analytics are taking the lead in business strategy. Gartner states that, ‘90% of corporate strategies will explicitly mention information as a critical enterprise asset and analytics as an essential competency.’ If your enterprise is implementing a business intelligence and analytics strategy, it is important to plan carefully and to understand the real benefits as well as the challenges of choosing the right BI tools and deploying these tools to users in a way that will ensure optimal user adoption and leverage of analytics to achieve the results you need.

‘Your business should carefully assess requirements and plan for expected user adoption by selecting a BI tool that will offer the features, ease-of-use and functionality your team members need.’

In this article, we provide examples of the various benefits of BI tools for specific business functions and some of the technology and user challenges you will face as you consider your options and plan for implementation.

Address the Challenges and Achieve the Benefits of BI Tools

No matter the business function, there are benefits to implementing a business intelligence strategy that will deploy these tools to your team members. Here are some examples:

Benefits

Finance – Your organization will be more efficient and profitable, with Ready-to-Use Dashboards, Analysis, and KPIs designed especially for the Finance domain. This business intelligence solution includes interactive Dashboards that allow users to perform intuitive, easy analysis of key metrics including Profitability, Accounts Receivable, Accounts Payables, Cash Flow Analysis, Past Due Invoices, Balance Sheets, Income Statements and more!

Inventory – Inventory business function allows users to accurately plan and optimize inventory. Interactive Dashboards track item movement, compare sales to closing stock, and monitor warehouse stock and value, and answer critical questions regarding stock turnover ratio, seasonal buying, back-order assessment and safety stock to prevent lost sales. Users can analyze inventory levels to effectively manage stock based on the buying behavior of customers.

Purchasing and Procurement – Allows users to view and analyze spending details, analyze procurement data, drill through data to analyze issues, measure performance, identify savings opportunities, and track supplier performance. Identify reliable trading partners, analyze supplier cost, perform purchase rate comparisons, reveal trends, identify top/bottom vendors, and achieve timely insight into spending patterns and trends across all departments.

Production – Quantify and visualize data at the operational level to make fact-based decisions. Analyze Output, Reduce Labor Costs, Maintain Inventory Levels, Optimize Equipment Performance, Monitor Rejection Ratios and Downtime, and take action before problems arise to mitigate risk, and capitalize on opportunities. Publish automated reports to monitor and manage plant performance and provide management with quality metrics and relevant data.

These are just a few examples of how business intelligence can be used within a business function, department or business unit to benefit business users and to help the organization make fact-based decisions, spot trends and patterns and opportunities, and identify the root cause of problems.

If you want to take advantage of all of these benefits and ensure success of your business intelligence initiative, your business should carefully assess requirements and plan for expected user adoption by selecting a BI tool that will offer the features, ease-of-use and functionality your team members need.

Technology and User Challenges

Social BI

Your team members are also consumers and outside of the office they are used to a collaborate and social experience. By engaging in Social BI, your team can champion data sharing, collaborate on creative ways to analyze data and make quick work of data analytics, with tools that allow the user to ‘like’, ‘share’ and leverage other social tools and networking techniques.

Mobile BI

Not every BI tool provides real mobile business intelligence to accommodate every type of device, screen size and resolution. Choose a solution that has a Responsive and Adaptive UI engine, so you can roll out BI tools on any Desktop, Tablet or Smartphone without any device specific development. ‘Design once, Use anywhere’ concept in true sense.

Personalized Dashboards

Business users will not adopt a solution that limits them to predefined dashboards. Each user has a need to see and use data in a different way. Be sure to select a solution that allows your users to work in a way that is meaningful to them.

Interactive, NOT Restrictive

Choose a solution that will allow users to leverage deep dive analytics. There is no way an organization can anticipate every question or type of analytics a business user will need to incorporate into decision-making. Provide truly interactive tools that will assure user adoption and make your organization more agile.

Ease-of-Use

Advanced Data Discovery allows business users to perform early prototyping and to test hypothesis without the skills of a data scientist. Advanced Data Discovery ensures data democratization with Self-Serve Data Preparation, Smart Data Visualization and Plug n’ Play Predictive analysis that can drastically reduce the time and cost of analysis and experimentation.

‘No matter the business function, there are benefits to implementing a business intelligence strategy that will deploy these tools to your team members.’

Ready-To-Use Business Intelligence tools can support data democratization and improve your business results. If your business understands the challenges of implementing a business intelligence solution and adequately plans for implementation and user adoption, it can leverage the benefits of these tools and solutions and ensure success. Let us help you achieve your vision and improve productivity and insight across the organization.

Original Post : Address the Challenges and Achieve the Benefits of BI Tools!

Smarten Augmented Analytics Now Available on Mobile App!

Smarten is pleased to announce the launch of its Mobile Application for Smarten Augmented Analytics. This native app has a seamless user interface for a great user experience (UX). Smarten Mobile app is available for iOS and Android. Installation is easy.

Smarten Augmented Analytics Receives CERT-IN Certification for Its Products and Services!

Smarten announces the recent certification of its Smarten Augmented Analytics Software product by CERT-IN. CERT-IN, or the Indian Computer Emergency Response Team, is an India government-approved organization for upholding information technology (IT) security, and is a well-renowned application security standard, respected within the technology community. It was initiated in 2004 by the Department of Information Technology for implementing the provisions of the 2008 Information Technology Amendment Act. CERT-IN certification is provided by a CERT Empaneled Security Auditor following a detailed security audit to review all components of the organization network including websites, systems, applications, etc. After completion of the testing procedure, the certificate is provided to show that all requirements were met.