“Enabling clients reimagine their decision making & accentuate the business performance with AI strategy in a transformation, innovation and disruption driven world”

In today’s fast paced & volatile VUCA world, leaders face unprecedented challenges. They need to navigate through volatility while staying focused on strategy, business performance and culture.  Artificial Intelligence is fast becoming a game changing catalyst and a strategic differentiator and almost a panacea to solve large, complex and unresolved problems.  To be an AI powered organization, leaders not only need to have a broad understanding of AI strategy, they need to know how and where to use it.  AIQRATE advisory services and consulting offerings are designed to enable leaders and decision makers from Enterprises, GCCs, Cloud Providers, Technology players, Startups, SMBs, VC/PE firms, Public Institutions and Academic Institutions to become AI ready and reduce the risk associated with curating, deploying AI strategy and ensuing interventions and increase the predictability of a durable leader’s success.

In the age of the bionic enterprises, AI continues to dominate the technology & business landscape.  Under the aegis of transformation, disruption and innovation, AI has several applications and impact areas which usher a new change in how we make decisions in the enterprise and personal spheres.  Traditionally, human decisions are to a large extent based on intuition, gut and historical data.  In the age of AI, several of our decisions will be taken by algorithms.  Leveraging AI, the ability to mimic the human brain and the ensuing ability to sense, comprehend and act will significantly go up and will result in emergence of augmented intelligence in decision making. Enterprises, GCCs, SMBs, Startups and Government Institutions are attempting to harness the power of AI to change the way they do business.  All these industry segments are looking at AI becoming the secret sauce behind making them gain a competitive advantage.  If you have not started yet, you are already behind the competition, however large or pedigreed you might be.

So, where are you placed on your AI journey?  At AIQRATE, we can guide you on your journey of understanding what AI can do for you, embedding it within your business strategy, functional areas and augmenting the decision-making process.

At AIQRATE, we are here to help you with the art of the possible with AI.  Through our bespoke AI strategy frameworks, methodologies, toolkits, playbooks and assessments, we will bring seamless Transformation, Innovation and Disruption to your businesses.  Leveraging our proven repository of consulting templates and artifacts, we will curate your AI strategic approach roadmap. Our advisory offerings and consulting engagements are designed in alignment with your strategic growth, vision and competitive scenarios.

We are at an inflection point where AI will revolutionize the way we do business. The paradigms of customer, products, offerings, services and competition will change dramatically; and being AI-ready will become a true differentiator.  AIQRATE will be your strategic partner to help you to prepare for what’s next in order to stay relevant.

Enclosing here our journey walk through of 2020.

The Internet of Things(IoT) has profusely pertinent applications. The effectiveness can be realized through operation and integration of the IoT across applications from domestic use to large scale industrial usage.

In this blog write-up, I would like us to deeply examine dynamics of IoT for SME’s to discover a range of applications and advantages to potentially become a driving force by looking at some of the critical unsolved problems. IoT potential is looked through multiple lenses in this sector, particularly its implications and application across SME landscape.

It is imperative to understand that analytics and IoT are two sides of the same coin. Basically, the information gathered from sensors requires analytics applications. The duo combo will influence to make informed decisions based on the data and behaviors collected.

From this perspective, application and its use have been extended for large industries and organizations. One of the potential benefits that IoT offers is in saving of costs related to process automation and rebound in customer satisfaction.

Similar benefits of IoT can be translated and enabled for SMEs in a relevant scale. SME’s have started embracing IoT and its related technologies. Here we would try to demystify IoT for SMEs such as retailers and companies with more moderate capitals by examining the developing role that it could play in both the immediate and long-term future. Smart devices and sensors are vital for this Machine-to-Machine (M2M) link. By applying machine learning to exploring how IoT could be used to transform businesses, we will envision ways to apply and adopt to SME related challenges

IoT in Retail

Retail across business are a strategic fit for IoT characteristics and intelligent sensors that can measure them. Some areas gaining pace in the industry include Automated Checkouts, Personalized Discounts, Beacons, Smart Shelves, In-store Layout Optimization and Optimizing Supply Chain Management

Sensors acts as the gate way for the above-mentioned areas and are placed at strategic points to capture customers interests, popular and moving brands, kinds of customers etc.

This information will enable customer segmentation and create applications designed for each segment such as promotions or discounts especially during launch offers for new products. In conclusion, IoT for SMEs can enable businesses to design enhanced strategies based on captures information through sensors.

Managing warehouses and production lines

Another potential segment that offers a strong application in IoT for SMEs is warehouse management. Sensors enable to track movement of goods in the warehouse or production lines. They also calculate the count of inventory creating a automated systems to create flags when the merchandise/raw material are running short.  Stock replacement/ replenishment requirements can be triggered automatically with alarms.

IoT in supply chain management

Service delivery is another prodigious application of IoT for SMEs. Again, sensors play a critical role in enabling the status of shipment or delivery at every stage. Apart from the above, it is significantly used for calculating improved trajectories for final mile delivery times.

Optimal routes for the delivery to improve the overall customer experience at minimal cost is key application of IoT in this segment.

Predictive and precautionary maintenance

Another application where IoT for SMEs is gaining rapid pace and is highly attractive is predictive and preventive maintenance. Here it enables a system for alerts for early detection and timely replacement of parts or status updates of machines for remote management.

End to end (E2E) operational application of IoT

Intelligent operations begin with integration of data from manufacturing, distribution and sales & marketing divisions. The factual application and advancement of IoT is to integrate all this data in creating new e2e products and services based on preferences of customers in combination to the data collected and validated.

IoT enabled healthcare

Healthcare services and clinics offers personalized service to accompany patients beyond the visits. IoT for SMEs provides solutions for these clinic-based models that result in a competitive advantage.  This enables to redesign the dynamics with patients a simple example could be to prompt a trigger for the ophthalmologic patient to replace glasses or improvement tracking. Use of sensors and Big Data also can give the complete vision of an operation and relevant tracking.

Customer based business models

IoT also offers an opportunity for a personalized service for an SME dedicated to plumbing and its predictive maintenance of spare parts to predict pipe installation failure by reviewing its surrounding conditions via application from your cell phone

The above mentioned are some of the many applications and advantages of enabling IoT for SMEs. The principle remains the same exploiting cutting edge technology allows to improve business model through informed decisions based on the data that IoT provides.

Security is a very important part of the above implementation. All technology is vulnerable to attacks. It is critical for the SMEs to consider security as part of the implementation. Below section illustrates some of the guidelines.

Digital Security for SMEs

Security is an essential aspect for SMEs or large organizations. IoT are also highly vulnerable to such attacks. It is important to factor every aspect of your IT architecture with the right security programs. This is key for deployment and commissioning of your sensors and Big Data programs to secure data.

SMEs need to consider aspects of hardware and software associated with IoT implementation model. Emphasis need to be laid on the types of networks, communications and back-up etc. and take inventory of equipment’s, software’s for the type of security that will protect attacks from identified vulnerabilities.

In summary, SME’s are becoming more digital to deliver a connected and seamless experience, IoT will trend among the latest technologies. The emergence of this technologies give rise to newer job roles such as IoT Managers, IoT Business Designers, full stack developers etc. in this sector. The functional and technical areas of these roles span across the expertise of applying sensors, embedded devices, software and other electronics to businesses with front-end and back-end technologies.

The rise of exponential technologies such as IoT and the need to stay upbeat with it, allows scope for the changing landscape of SME’s through new opportunities and roles. IoT will continue to be in the fore front of this changing landscape for SMEs while it is imperative for them directly boost this digital frontier.

As is the case with investments in any other area of technology, AI needs to deliver demonstrable impact to business top line and bottom line. In today’s competitive landscape of business, enterprises are expected to measure the incremental ROI for every expense and every investment made – technology or otherwise. The case of Artificial Intelligence is no different. It is critical that technology and business leaders demand ROI impact for this technology in order to foster its growth and justify its proliferation in business.

To be sure, there are two key areas where Artificial Intelligence can contribute immense value; Increasing top line figures by unlocking new revenue streams and improving the bottom line through efficiencies in operations. Needless to say, top line gains eventually percolate their way into showcasing bottom line improvement – but for the purpose of this post, we’ll refer to bottom line impact as areas where AI brings in cost efficiencies by helping organizations reduce their overall cost of operations.

Artificial Intelligence driven applications can have a discernible impact on business top lines and bottom lines and help organizations unlock ROI from their implementation.

AI-Powered Topline Growth

Artificial Intelligence-led applications have huge potential to add to top line revenue growth for any organization. Typical AI interventions for this purpose range from improving the effectiveness of marketing and sales functions, improving customer loyalty through laser-guided customer experience initiatives and direct and indirect data monetization.

New Revenue Streams Enabled by Data Monetization:

Business leaders need to realize AI’s potential to unlock new sources of revenue in addition to improving customer targeting and loyalty. One of these ways is data monetization. What is data monetization? Simply put, data monetization refers to the act of generating measurable economic benefits from available data resources. According to Gartner, there are two distinct ways in which business leaders can monetize data. The most commonly seen method from the two is Direct Monetization. The way to realize value from this avenue involves directly adding AI as a feature to existing offerings. Companies like Nielsen, D&B, TransUnion, Equifax, Acxiom, Bloomberg and IMS run their business on licensing their data in a raw format or as part of their application infrastructure. With emerging Data-as-a-Service models and the application for direct insight delivery through intelligent application of AI, direct data monetization is simpler than ever. By wrapping insights alongside the data source, vendors can create a symbiotically powerful exchange of information for both the buyers and sellers of data. On the other hand, Indirect Monetization involves embedding AI into traditional business processes with a focus on driving increased revenue. A popular example of this is corporations who come out with branded, paid-for reports based on the data they own. For instance, professional services companies such as Aon, Deloitte, McKinsey, etc., regularly bring forward insightful industry and function-specific reports based on the data they collect as part of their consulting assignments.

Enabling Intelligent Marketing and Sales

Many of the most prominently cited successes of AI-enabled business transformation comes from the marketing and sales arena. Sales and marketing are constantly on the forefront for exciting inventions in AI since they contribute directly to top line growth. Use cases discovered in this arena span social media sentiment mining, programmatic selection of advertising properties, measuring effectiveness of marketing programs, ensuring customer loyalty and intelligent sales recommendations. AI also has huge potential to drive businesses to explore and exploit eCommerce platforms as a credible channel for sales and to help drive the digital agenda forward. Available tools are helping drive better customer conversions on eCommerce properties – by analysing the digital footprints (clickstream, etc.) of prospective customers, persuading them into making a purchase. In such use cases, AI helps improve personalization at the point-of-purchase, improve conversions and reduce cart abandonment. Marketing and sales use cases today are pretty much at the epicentre of an AI disruption and business leaders need to uncover more use cases that can help drive effective top line growth.

AI Redefining Customer Experience

Customers are the epicentre of every successful organization. Today, we live in times where customers have numerous competitor options to choose from while the switching costs for customers are increasingly lower. Given this scenario, for businesses to win with their customers they need to have a smarter approach to customer experience management.

We have progressed well beyond pre-programmed bots addressing frequently asked questions. AI-enabled systems today go further and provide customers with personalized guidance. The travel and hospitality industries, for instance, are ripe for such disruptive innovations. In many cases, we see chatbots that help customers identify and recommend interesting activities and events that tourists can avail. When applied with human creativity, AI can ensure this redefined understanding of customer experience, while maintaining a lower cost of delivering that experience.

AI for Improving Bottom Line Performance

At an operational level as well, AI can help organizations run a more efficient business. For instance, corporations across industries need to find innovative and fail-safe ways to reduce the cost of manufacturing as well as capping their outlay on the supply chain network. AI-centric solutions can drive down the turnaround time for talent acquisition and transform other facets of the Human Capital function too.

AI Driving Operational Efficiencies

Traditional manufacturing processes are now increasingly augmented by robotics and AI. These technologies are bringing increasing sophistication to the manufacturing process. The successes combine human and machine intelligence making AI-augmented manufacturing a pervasive phenomenon. Today, business leaders in the Industry 4.0 generation need to seriously consider planning a hybrid labour force powered by human and artificial intelligence – and ensure that the two coexist by implementing the right policies and plans in place.

Smarter Supply Chains Powered by AI

Orchestrating a leaner, more predictable supply chain is ripe for an AI-led disruption. We are witnessing not just new products and categories but also new formats of retailers proliferating the industry. This varied portfolio of offerings and channels requires corporations to manage their outlay efficiently on the overall network responsible for the network that manages the entire process from procurement and assembly to stocking and last mile delivery. Multiple use cases exist that leverage multi-source data from internal and external repositories, combining them with information from IOT sensors. AI algorithms are then applied over this combined data infrastructure with the objective of helping business users quickly identify possible weaknesses/flaws in the process such as delays and possible shortages. Business leaders are constantly on the lookout for solutions that can directly lift their bottom line by bringing in more intelligence and automation to their supply chain networks – thus unlocking savings for their businesses.

An Artificial Facelift for the Human Resources Function

The human resources function has historically been considered a cost-center in organizations. In addition to bringing down the costs associated with talent acquisition and management – AI would also help HR teams become leaner, more organized and reduce the turnaround time for talent acquisition. AI interventions are being seen in the areas of employee engagement and attrition management, but some of the most exciting use cases come from the talent acquisition area within the HR function. Multiple organizations are already working on solutions that can eliminate the need for HR staff to scan through each job application individually. By using AI intelligently, talent acquisition teams can determine the framework conditions for a job on offer and leave the creation of assessment tasks to Artificial Intelligence-powered systems. The AI-empowered system can then communicate the evaluation results and recommend the most suitable candidates for further interview rounds.

One of the key reasons why AI is in vogue today is the demonstrable ROI impact that it promises to bring to business processes. With greater computational power and more data, AI has become more practicable than before, but what will sustain its growth is how much incremental value it can eventually unlock for businesses across the globe and power new revenue models for businesses to tap into. It is critical that business and technology leaders earnestly kick off discussions around how to justify the impact of AI and mark down the key metrics that will be used to measure it. Partners and service providers too need to stay on top of finding ways to showcase measurable improvements that their software or services can bring to technology buyers. This will enable the entire AI ecosystem to flourish. 

A robust ecosystem for small and medium enterprises is one of the key indicators of economic vibrancy and entrepreneurial energy in a nation. India’s entrepreneurial spirit was given a massive boost after liberalisation in the early 90s. These norms ended the draconian ‘Licence Raj’ that kept the lid on the business aspirations of the average Indian. With improving access to capital, heightened ease of doing business and a galvanised ecosystem that provides mentorship and guidance to fledgling startup founders, the small and medium enterprise (SME) sector has been riding high over the past couple of decades. Now with Artificial Intelligence (AI) in the mix, SMEs will be given another boost – through reduced cost and improved efficiencies in how they run, operate and succeed.

There is no doubt that AI will be an important gamechanger for the SME sector. Startups today are much more data-rich than before and understand the value that can be unlocked through intelligent deployment of advanced analytics. They understand that a data-driven understanding of their business landscape will far outweigh heuristic methods in the dynamic environment in which their enterprises operate. Further, with lowering cost of adoption, increased focus on the SME industry by incumbent analytics/AI vendors and partners, we have a perfect storm of sorts for the sector to derive the exponential benefits of this technology. Let us look at the areas where AI can deliver a strong, demonstrable impact on the sector and how such businesses can get started on their AI journey.

Galvanising SME Operations

When run on the right data set, AI can work its magic in providing untold operational benefits to SMEs. The case for AI in the startup sector is much stronger than it is for their larger corporate counterparts. The reasons for that are two-fold. First, startups typically operate on smaller budgets – which means that they need to automate as much as they can to reduce costs associated with a higher headcount.

Secondly, startups by their very nature are extremely nimble, allowing them to experiment rapidly with new, innovative technologies. This twofold advantage means that AI vendors as SMEs need to have a robust strategy in place to work together and uncover the latent advantages offered by this technology. Here are a few areas where AI can specifically help startups galvanise their operations.

• Predictive maintenance: SMEs, especially in the manufacturing segment, can unlock huge benefits in the production process using AI. With sophisticated algorithms monitoring machine health, AI can help reduce the downtime in production schedules by accurately modelling when a critical machine is likely to go down, allowing businesses to better plan demand fulfilment.

• Supply chain and logistics: A major drain on the revenue of nascent businesses is the cost associated with procurement of raw materials and delivery of finished products. By using AI and third-party location data, SMEs can plug this drain by powering faster and leaner delivery schedules. Similarly, demand planning and order fulfilment will get a big boost as SMEs learn how to forecast accurately through machine learning models, thus reducing the waste that entails unused, unsold and unutilised inventory.

• Marketing and sales: Multiple SMEs tend to go under because they take on much large corporations with massive sales and marketing budgets. AI can help these startups level the playing field. By using data from each prospect interactions as well as leveraging emerging breakthroughs in the field of programmatic advertising, AI can help fine-tune the marketing programs of startups and help deliver better ROI on their spend. Similarly, through an improved understanding of their territory, AI can provide laser-guided focus to sales people on which prospects to focus on and what approaches can deliver the best results.

• Customer service: Where large enterprises can afford to outsource customer service operations or even bring them in-house, SMEs do not have these advantages. In today’s environment, customers are shown to be more loyal when provided with a superior customer experience. AI can bridge the gap between customer expectations and the constrained budgets available to provide those. With intelligent assistants, SMEs can navigate common questions and complaints put forth by customers and provide a superior customer service at much lowered costs of delivery.

• Talent acquisition: SMEs often have vastly varying needs for talent. For instance, those that are on a strong growth trajectory need to staff their companies rapidly before the competitive advantage they offer slips. Those that are on a slower curve also need to make sure that they hire candidates with the right mix of experience and attitudinal attributes to ensure the smooth functioning of their business.

AI can help reduce the time taken to identify the right candidates by rapidly screening resumes to identify the best fit for the needs of the business. Further, with the right data and training, AI can also administer relevant tests to candidates and grade their performance, thus reducing the requirement of human intervention and time taken to screen good candidates.

Getting Started

Let us look at some of the key factors that business leaders need to keep in mind as they get started on their AI journey.

• AI starts with data: The first consideration before planning an AI intervention is to understand whether high quality data is available for AI to work its magic. Without the right data sets, even the best algorithms can go awry. It is essential that business leaders ensure that their data repositories are sufficiently rich to get started on the AI journey.

• Identify the right problems: SMEs tend to be inundated with multiple issues of burning importance. It can be very enticing for business leaders to assume that AI is the panacea for all problems. That is not the case. Business leaders need to identify the right problem statements where AI can make a demonstrable impact and prioritise use cases that can be solved through AI. Scan the market for best practices and learn from peers to better understand what AI can do and what measurable benefit you can derive from AI-led interventions

• Set success benchmarks: For AI leaders, it is important to set a marker for the right expectations with business leaders. Hence, for the business to see continuous improvement in the results delivered by AI, it is critical to identify the right set of business metrics and expected performance against each of those.

Artificial Intelligence today has gone well beyond experimentation to now becoming a real game-changer in how businesses operate. AI can bring significant benefits to startups with improved efficiencies and faster operations. SME leaders looking for strong competitive advantages with respect to their peers would do well to harness the power of this technology and infuse it into their key business process to accelerate outcomes and grow their businesses.