Ways in which Machine Learning and AI can improve your ERP

| February 6, 2019

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Artificial Intelligence and machine learning have the ability to restructure the world. These two areas have witnessed exponential advancement due to which companies are able to benefit the most. Improvements to the ERP software has also been made with the help of artificial intelligence and machine learning. Furthermore, machine learning is beneficial because it quickly evaluates a problem which thus results in taking necessary measures on time. With such technological advancement, it is easier for companies to prevent shutdowns or waste their resources. Let’s dig in further and know how these two technologies can help in improving your existing ERP.

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Brillio

Brillio, a global technology consulting and business solutions company, enables the successful digital transformation of businesses by utilizing disruptive technologies to create new customer experiences, achieve cost efficiencies, and gain competitive advantage with speed and agility.

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The virtuous circle and the MetaQuant Approach

Article | June 29, 2021

Depicted as a natural predisposition to form groups of work, teamwork has been popularized through history as a central feature of organizational change programs that advocates empowerment and disruptiveness. The suasive force of discourse regarding the ineluctable essence of teamwork as a tradition and custom founded on some inclination for humans to work cooperatively, create a set of “rituals”, conventions and practices which invite to innovation, flexibility and creativity. Teamwork as “human nature” was a common thread all through history and management literature. The team-based nature of early human activities can be traced to hunter-gathering in societies where orality was the prime source of communication. The locus communis was the collective memory (facts, rules, code of conduct, religious beliefs and practical knowledge). The pneumonic function of the verse will fulfil a didactic function as a way of memorizing any content in order to systematize a conceptual theoretical primitive language. In preliteracy times, doctrines and their conservation were highly dependent of the spoken word and memory (Havelock, 1957, 1992). Thus, in an oral culture experience is “intellectualized” mnemonically (Ong, 1982). In a sociobiological perspective, aspects of teamwork behaviour allude to a biologically determined “natural history of species”. According to Katzenbach and Smith (1993) “teams- real teams and not just groups that management call “teams” should be the basic form of performance for most organizations, regardless the size”. This statement clearly sets the basis for the team as a natural building block of any organizational design. Buford (1972) in a comprehensive study of Ancient Greek and Roman craftmanship interpreted teamwork in a very familiar approach we understand it today: collaborative work, multiskilling, mutually interdependent tasks. There were technical divisions of labour based on skills, the relationship between mentor and apprentice and so on. The greatest craftsmen were expected to be versatile in different skills, but the coordination of work efforts was left to the so-called professional cadre of engineers, architects and masters. With the advent of Capitalism, the massive growth of the economic activity claimed for reorganization. A new form of discourse emerged, our prehuman origins and modes of communication becoming codified and formalized as the scientific disciplines of evolutionary biology, economics and linguistics respectively (Foucault, 1972). Within the economic discourse, there was a creation of a distinct managerial object, which opened new domains of knowledge and professional practice. The mythical traditions of teamwork replicated in today’s contexts and the “tribal” notion of team popularized by Codin (2008) paves the way to concrete changes in the form we perceived our working environment. The analogy of team as “family” so common in the corporate world which in its essence represents our first experiences as a community is not a happy term anymore, since in a manner it could go against the interests of today’s organizations. Therefore, in building a healthy sustainable workplace culture teams cannot be perceived as family. Teams have a commitment to a common goal, clear expectations and performance. The MetaQuant: From siloed work to interdisciplinary collaboration With the paradigm shift to automation, organizations are taking actions that promote scale in AI through the creation of a virtuous circle. The central overarching question is: Are traditional ML teams good enough to develop models able to achieve long lasting competitive advantage? “In a world spinning around AI, competition among institutions seems to be fierce while mayor obstacles appear on the way: recruiting top talents is not only time-consuming but also high-priced, or just trying to find a balanced approach to talent, meaning "reshaping" the old-school computer scientists into quants, is critical in terms of AI implementations. The big winners: those firms that integrate AI with human talent” (Litterio, 2020: 167). Successful machine learning (ML) projects require professionals beyond engineering expertise. AI has the biggest impact when it is developed by dynamic creative cross-functional teams. The move from functional to interdisciplinary teams initially brings together the diverse skills and perspectives to build effective tools. In order to bring theory into practice, and in the need of a novel conceptual framework design, I have coined the term MetaQuant. The MetaQuant is a new breed of market players, who “translates human language into signals” and "reads" the data from a holistic perspective identifying patterns within the linguistic and symbolic constructs. The MetaQuant is the linguist, the semiologist, the sociologist, the cognitive psychologist and the philosopher or rather a combination of these intertwined profiles which will fuel the potential for information advantage providing a unique core differentiator transforming data into knowledge. In this sense, the MetaQuant has emerged as a crucial component of any AI model paving the way for a novel insight where hybridization is critical. The formula for a successful organization in a discovery-driven environment is the MetaQuant + The ML team. And eventually the Quantum Computing Expert. Finding the needle in the haystack can be a competitive difference maker. Creative thinking, actionable insights, collaboration, proficiency, flexibility, shared vision and training are the ingredients for an elite team. It is vital for organizations to establish workflows that empower everyone to play a role in order to move projects from test to deployed AI/ML. Yet, knowing how to do ML is not the same as being proficient with it and knowing how to implement a ML model end-to-end is not the same as using ML creatively to build solutions to real-world problems, to explore and assess potential applications specific in competitive contexts. Ideally, when selecting members for your elite team, it is advisable to make a first distinction between those who wish to do research in ML from the ones who wish to apply ML to your business problems. Both are of major importance alike. The instreaming of new talent brings in novel ideas which can positively impact the work culture. Demonstrating flexibility is a significant asset. Since ML projects may encounter all kinds of roadblocks, being able to easily change tactics to overcome obstacles without getting frustrated or losing sight of the end goal is key to deliver projects. Mentoring and inspirational leaders is greatly valued when designing a ML team. An exceptional team leader is the one who shares a unique perspective and knowledge. Experience in the field is a substantial source of wisdom within the organization. Having a passion for diversity of input and fostering a healthy culture of support distinguishes average from excellent ML teamwork. Educating everyone is the dictum to become an AI-first institution. To ensure the adoption of AI, organizations need to educate everyone, from top leaders down. To this end most are launching in-house programs which typically incorporate workshops, on-the-job training to build in capabilities. Some others, and which reflects a common trend today, opt for partnerships with renowned academies or prefer the outsourced modality “training as a service” program or a bootcamp. For an A-team, it is critical to make a mark in the ecosystem through journal publications, book chapters, white papers or lecturing in conferences. Disseminating their work and findings through meetups, workshops, and seminars is a must for building a thriving culture that promotes exchange and cross-fertilization of new ideas and technologies in a substantial way. Systematicity and coding belong to the ritualistic change of conscience.

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Create a Cloud Migration Strategy with IT Infrastructure Monitoring

Article | July 23, 2020

The rapid pivot towards a remote workforce is forcing organizations to adopt a cloud-first approach faster than ever. We recently surveyed 500 IT decision-makers around the globe to ascertain their views on IT automation, cloud migration, and business continuity in the face of unexpected crises. The survey found that 87% of IT professionals agree that the current COVID-19 pandemic will cause organizations to accelerate their migration to the cloud.

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ThoughtSpot, Google Cloud Double Down on AI-driven Analytics

Article | March 26, 2020

Search and AI-driven analytics provider ThoughtSpot recently announced a collaboration with Google Cloud to launch Embrace for Google Cloud Platform that will enable enterprises to perform search and AI-driven analytics directly in Google BigQuery. The launch of Embrace will help enterprises leverage the dual power of Google BigQuery and ThoughtSpot’s augmented analytics. The combined delivery will enable organizations to derive proper insights and help them in taking appropriate actions. “Enterprises have more data at their disposal than ever before. The problem arises, however, when they look to turn that data into insights that can transform how their business operates. The old analytics stack is too slow and cumbersome to deliver the value they need from their data,” said Seann Gardiner, SVP of Business Development & GM of Embrace, ThoughtSpot. “Embrace for Google Cloud exemplifies the new, cloud-native, AI-powered analytics stack required to rewrite this equation and drive true transformation for our customers.”

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How to Market Your AI-powered platform

Article | June 22, 2021

The world of AI-powered businesses is evolving like never before. It’s fast-moving, extremely competitive, and even ruthless at times. Currently, hundreds of artificial intelligence platforms are being introduced every day and they are reshaping the way businesses conduct different campaigns like social media campaigns, search marketing campaigns, digital marketing campaigns, etc. With intense competition in this field, only a few manage to reach the top. Some keep on struggling to impress their audience for years while others fail to find the right traction and eventually crumble shortly. Being a company owner, marketer, or founder, it is essential to keep one thing in mind — people want to buy great products. And, only the most creative, smartest, and strongest all will last. Whether it is a service or product, it must add more value to the day-to-day lives of your customers. That said, effective marketing for AI-powered platforms in this internet era may seem like finding a needle in a haystack for some. However, it can get an edge and rule this cynical market if you follow the below-mentioned actionable tips. We have discussed with some of the best brand communicators and marketers in the business who have used amazing tactics to survive in this already saturated industry. Focus More On ROI, Less On Technology Being an AI-based company or a platform, it's obvious that many tend to get wrapped up in a bunch of technical terms. But the customers don’t care much about it. Instead of knowing your artificial intelligence tool in and out, they want to know how it can boost their returns on investment. Yes, it’s good to let them know the technology you have used. But in the end, it’s the service you are selling and any customer would want to make sure if your product can satisfy the following needs: ● Enhance customer relationships ● Minimize business costs ● Simplify the processes ● Reduce the losses ● Get more sales Your marketing strategy for AI-powered platforms must focus on the major pain points of the customers. After all, knowing if your product is worth the money is the basic thing all businesses and individuals need. Go Visual To Effectively Market Your Service Nothing can catch someone’s attention better than the visuals. Humans are visual learners and nothing can beat great visuals when communicating a service or product. Let your customers take a peek at what’s under the hood of your service. You indeed can get help from gifs, videos, photos, and screenshots to clear some fog. But understanding how the software works is rarely achieved through them. Giving them an idea of how it really works is the key here. Demonstrating the functionality and interactivity of your platform helps clients understand its operations and ultimately, its potential benefits. Make sure your demo is clear, friendly, and able to help your customers visualize your AI-powered platform in action. This high-performing marketing strategy has the power to normalize your solution, no matter how complicated it is in reality. Have A BS-Free Approach Even though this is a pretty obvious thing to know, it’s worth mentioning here because it is, unfortunately, extremely widespread. You should market your product as an AI-powered one only if it truly revolves around AI. The concept of artificial intelligence is the new boom in the market and many businesses are tempted to introduce their platform as AI-powered even when it isn’t. This may look cool in the beginning but avoid doing this as it can cause serious consequences for both investors and customers down the road. Therefore, the marketing for AI-powered platforms should be very tech-specific and long away from even the slightest hint of misleading. Educate Your Customers On Alternate Options In general, Artificial Intelligence is an umbrella term that comprises several technical approaches. But sadly, only a few of them are mostly touted in the market. “Deep Learning” and “Machine Learning” are to name a few. How many are there who say they use Robotic Process Automation, AI Optimized Hardware, Decision Management, or Evolutionary Strategies? The numbers are surprisingly poor. Your marketing for AI-powered platforms should include demonstrations that educate customers on your unique approaches that can benefit their business in terms of finances, eCommerce, digital marketing, etc. For instance, if your platform is armed with Evolutionary Strategies (ES), let your customers know about it. ES uses a set of candidate solutions for problem-solving. It evaluates the answer depending on a ‘fitness’ function. The survival of the solutions is decided on their performance ratings which improve them generation by generation. The stand out feature of ES is that it does not require tons of clearly labelled data. Such kind of optimized marketing creates wonders. It cares more about the outcomes customers will get and less about the tech. Develop A Remarkable Demo To earn the trust, attention, and eventually the budget of your customer, you need to make the best first impression of your AI-powered platform. Your product should speak for itself and you can get help from a crisp, condensed and engaging demo for this task. Build a great demonstration of your product to explain how it operates. This will make customers realize how it can be beneficial for their specific needs. A highly practical and visual demo gives extra information about the product so your customers can understand a broader picture of it. It helps them to draw conclusions about certain facts, functionalities, and potential benefits. Include Case Studies In Your Demo Case studies play a vital role when it is about marketing for AI-powered platforms. The fact is, most of your customers are not tech-savvy. And, all those jargon, technical words related to your product are kind of an enigma to them. Of course, you can use visuals, bulleted points, and other forms to demonstrate the unique features of your product. However, it’s not enough for them until they see how your product helped other customers. You can count on some of your compelling customer stories to showcase the power of your tool. It not only demonstrates how your platform works in the real world but also helps clients know the tangible value creation. Arrange Free Consulting Sessions And Webinars For Customers Marketing for AI-powered platforms should be all about expressing your unique approach and best ideas to the right audience in such a way that they find it valuable, interesting, and game-changing. Talking directly can make this job a lot easier. Yes, we mean literally talking to your prospective clients. But how can you do that? It’s simple — through consulting sessions and webinars. Both of these options are highly beneficial as they can ● Answer all the questions customers have ● Create excitement among customers ● Build communities Such a consultative approach is an integral part of any high-performing marketing strategy because it allows you to serve and not just sell. And on top of everything, it creates a ‘tone of helpfulness’ that promotes trust. No matter if you have the most unique and powerful ideal in the world, that’s not enough for the success of your company. The right marketing is what you need to make your idea reach the mass. As the artificial intelligence industry is constantly growing and the cutthroat competition is making it harder to reach the top, what roadmap you follow in marketing for AI-powered platforms is the ticket to your success. FAQs What is AI-powered marketing? AI-powered marketing, in layman’s terms, is a marketing strategy that uses artificial intelligence. It revolves around the facts related to data analysis, data collection, and customer & economic trends that can make or break your marketing efforts. When speed is what you want, nothing is better than AI-powered marketing. With the effective use of customer profiles and data, AI initiates communication and serves the customers in the best way. What are the top benefits of AI-powered platforms? The following are the benefits that can make your job of marketing for AI-powered platforms easy: ● Improved personalised experience ● Automated customer interactions ● Improved outcome predictions ● Enhanced recruitment process ● Improves information security ● Operational automation ● Real-time assistance ● Data mining What is an AI-powered platform? Traditional platforms involve human beings to complete specific tasks. On the other hand, AI-powered platforms use machines to do the same. Artificial intelligence platforms use cognitive function stimulation that humans normally use for general intelligence, social intelligence, logical reasoning, learning and problem-solving. With such a great ability to reduce human efforts and deliver excellent benefits, effective marketing for AI-powered platforms is the need of the hour. { "@context": "https://schema.org", "@type": "FAQPage", "mainEntity": [{ "@type": "Question", "name": "What is AI-powered marketing?", "acceptedAnswer": { "@type": "Answer", "text": "AI-powered marketing, in layman’s terms, is a marketing strategy that uses artificial intelligence. It revolves around the facts related to data analysis, data collection, and customer & economic trends that can make or break your marketing efforts. When speed is what you want, nothing is better than AI-powered marketing. 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Spotlight

Brillio

Brillio, a global technology consulting and business solutions company, enables the successful digital transformation of businesses by utilizing disruptive technologies to create new customer experiences, achieve cost efficiencies, and gain competitive advantage with speed and agility.

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