Know My Company
How have you interacted with smart technologies like AI and Cloud-based analytics platforms?
The concepts of AI, Machine Learning and Cloud-based analytics (high-performance, distributed, big data) have been around for some time now. My co-founder, Sumi Duttaray, and I have been engaged in the analytics for a long time, as we have experienced the evolution of data analytics and advanced statistical modeling. The power of cloud-based computing along with the capabilities of processing a massive amount of data unlocked the potential for applications Machine Learning algorithms. Within mdrk Consulting, we bring our decades-long experiences in data analytics and fuse them with new modes of platform-oriented automated solutions, often working together with cloud-based AI partners to solve the client’s problem.
How did you start in this space? What galvanized you to co-start mdrk?
One of the primary reasons to start in the space is to help small to medium businesses in the marketing, consumer insights and advertising space to be able to stay analytically agile, adaptive, and use Data Intelligence, and be technologically up-to-date having to access the analytics tools, and empowering the internal resources to drive business results.
At the beginning of we had the opportunity to work with a few clients that needed support to organize data-driven insights and the process for co-starting mdrk Consulting took-off. We have had a foundation to start structuring the consulting offering.
What is the state of NLP technology in 2019? How much has it evolved since the time you first started here?
NLP technologies, platforms and algorithms have evolved into the fairly good state over the last five years or so. There are two strands of NLP powering the business growths – textual language processing, and voice recognition. Since we started our consulting business, adoption of NLP to harness customer success has become a priority for most mid to large businesses. The power of NLP is fuelling both internal resource management and external customer management systems.
What is your vision into Customer Experience (CX)?
Customer Experience (CX, in short) has been a key driver of growth for most customer-focused product and services businesses. Related metrics, such as NPS, Brand Indices – Awareness, Perception, etc. are all becoming major portfolio assets in CMOs functions. CX is closely related to customer journey from advertising and marketing exposure to purchase, to services or subscriptions. With the advent of more direct-to-consumer brands, and with the emergence of the subscription economy, CX is the major factor driving business value and growth.
How do you see the raging trend of including AI and Machine Learning in a modern CIO/ CMO’s stack budget?
The trend of adopting AI and ML is certainly growing. In a recent survey, at least 48% of C-suite decision makers are willing to adapt AI/ML for their respective departments. However, only 28% are actually doing something with ML, but a bit far from adopting a fully automated AI system. The reason is a lack of understanding of the AI capabilities in current business environments as well as the cost (both resources and platforms) aspect of developing AI capabilities. While the willingness among the C-suite is there, the actual adoptions of AI/ML are still in the early stages.
How do you differentiate between technologies for Customer Success vs. Customer Support? Who are you competing within this landscape?
The platform and technologies that help the business to grow by acquiring a customer, by gaining market and brand share are critical for customer success, but the technology systems that help sustain growth by retaining and providing good customer support are those that maintain the brand value and therefore, stakeholder confidence. These platforms operate in distinct paradigms and often requires technology solutions that are designed for acquisition (B2C, B2B) and retention (CRM).
What are the biggest challenges and opportunities for businesses in leveraging technology to optimize their Customer Support and Customer Success?
The biggest challenge is understanding the customer journey – from product awareness to brand perception to adoption to recurring usage. One of the key factor playing technical roadblock is the data silos and legacy data systems. The opportunity to leverage the new technologies that build on data lake infrastructure and cloud-based ML powered solutions to understand the customer decision-making process and life-time-value are of highest values.
How should young technology professionals train themselves to work better with automation and AI-based tools?
With increasing democratization of the open-source AI and ML tools, young professionals have the opportunity to train themselves on the skills to handle big and unstructured data and Cloud-based computing platforms using languages like Python and R. The use of ML and AI libraries with well-defined business problems can foster career growths.
What is the biggest challenge to Digital Transformation in 2019? How does mdrk contribute to a successful Digital Transformation?
Digital Transformation is a buzzword from leading consulting institutions. The biggest challenge is that a Digital Transformation roadmap is often least understood under most business functionalities, difficult to correlate with future return on investment. At mdrk Consulting, we try to couple the digital initiative with a singular business problem at hand and help clients to build modular step-by-step approach by connecting the data silos to broader business problems. It helps clients to see the clear roadmap to robust Digital Transformation, from data to solutions.
How potent is the Human-Machine intelligence for businesses and society? Who owns Machine Learning results?
Humans are not going to be replaced anytime soon. However, Machine Intelligence would take over a lot of the repetitive data-driven analytics, including but not limited to understanding common human interactions and usage. Who owns the Machine Learning intelligence is philosophical questions, at least for now, but the critical part of the Machine Learning output, say, for example, ownership of self-driving car would become a major legal and social issue.
Where do you see AI/Machine Learning and other smart technologies heading beyond 2020?
Improving the services that provide a seamless and faster experience for the customer would evolve on after 2020 – examples include, experiencing augmented and virtual reality, ordering, delivering, recommending, sharing, consuming content, and connecting with real and virtual entities.
What is the Good, Bad and Ugly about AI that you have heard or predict –
The good side of AI is automation with precision. The bad part is the resource, energy, and cost of implementing even a simple AI system. However, the ugliest part of an AI system is the black-box nature and inherent bias of the learning system, and when an AI system goes wary, we may not have an answer to fix it immediately before causing the havoc in the chain is systems.
What is your opinion on “Weaponization of AI and Automation”? How do you promote your ideas?
This is a highly controversial issue, particularly, concerning privacy and surveillance Intelligence. Drawing the boundary on the good (beneficial, say health, epidemic, weather, etc.) vis-à-vis unfair use (towards common people and ordinary citizens) would be a major concern.
What Cloud Analytics and SaaS start-ups and labs are you keenly following?
Open AI/ML frameworks and start-ups using voice, images and those fairly competing on cognitive algorithms (and any variations of Neural Nets) are my major focus
What technologies within AI/NLP and Cloud Analytics are you interested in?
Deep, recursive, and collaborative neural network frameworks
As a tech leader, what industries you think would be fastest to adopting Analytics and AI/ML with smooth efficiency? What are the new emerging markets for these technology markets?
Any CRM and Customer Intelligence based businesses would have greater success in adopting AI/ML. Markets like India and middle-east would be the best places for these technologies to be successful.
What’s your smartest work related shortcut or productivity hack?
Smart, prioritized calendar reminders (across all communication applications) and conference auto-dialler when needed by a virtual assistant.
Tag the one person in the industry whose answers to these questions you would love to read:
It is difficult to point one person in this field, but I follow Avinash Kaushik who maintains several blogs on these topics and provides simple to understand thought leadership.
Thank you, Kajal! That was fun and hope to see you back on AiThority soon.
Kajal Mukhopadhyay, often known as Dr. K, is the Co-Founder & Principal of mdrk Consulting, an independent boutique data and design consulting firm based in New York City. mdrk Consulting helps clients with data intelligence, data science, analytic solutions and data-driven products and designs. As a Co-founder, Kajal brings 15+ years of experience in media and digital analytics.
Most recently he was part of the Mindshare team from GroupM, where he had been a Managing Partner and Director of Live Audience, responsible for Audience Product Developments using big-data intelligence and machine learning algorithms.
Founded by experienced analytics and design professionals Sumi (Mousumi) Duttaray (mdr) and Kajal Mukhopadhyay (Dr. K) in 2003, the mdrk Consulting (formerly, iKolkata) is a data analytics and design consulting partnership with a combined experience of 30+ years. mdrk Consulting brings decades of academic research in economics, social sciences, political sciences and related fields of consumer behavior. Our collective expertise helps companies in retail, finance, marketing, consumer insights, media, ad-tech and industry researches to navigate, design and build data-driven intelligence