As global competition continues to intensify, manufacturers are seeking new ways to meet the changing needs of the marketplace. Forward-thinking players are counting on shop-floor automation to drive operational efficiency and raise product quality. They know that the future of their enterprise lies in a future-ready factory.

Isn’t a good ERP solution good enough for managing manufacturing operations? Not really! Most traditional ERP systems have remained focused on official functions like accounting, human resources, customer service, basic plant scheduling, and supply chain operations. The demands of the production function are more
specific and technical in nature. The requirement in this case is a solution that helps improve real-time
workflow visibility and process efficiency within the factory floor. 

Manufacturing Execution System – Built for the Factory Floor

A manufacturing execution system (MES) is an information system that interconnects, monitors, and
controls disparate manufacturing systems, and data flows in the production environment. It works across multiple areas of manufacturing operations including resource scheduling, product tracking, quality control, production analysis, maintenance management, and order execution. The solution gathers real-time data from the entire production lifecycle. The insights gleaned from this data is used for streamlining factory operations.

The primary goal of an MES is to ensure effective execution of the manufacturing operations and improve production output. A layer in between the ERP and other process control systems, an MES system is an essential add-on and not another version of an existing system. It functions seamlessly with ERP, supply chain management, PLM, and other core enterprise systems. Truth be told that there are some areas where the
ERP and MES systems overlap. However, this issue can be addressed easily since the implementation is done only after defining the roles and goals beforehand.

What to Look for Before Choosing an MES Solution

When it comes to choosing an MES solution, a few factors need to be considered before proceeding –
cost, interoperability, ease of deployment, language support, scalability, customization, and support.
The search for a one-size-fits-all solution may not be fruitful, since the modules depend on the industry
and scope of operations. Nevertheless, recent advancements have helped technology providers roll out
plug-and-play solutions that require minimal customization. 

A good integrated manufacturing execution system provider should offer everything from concept to delivery. The ideal service suite consists of MES consulting, solution design & implementation, upgrade & roll out, integration, and maintenance.

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Loyalty in the Age of Hyper-Personalization

Price, attention, delivery speed, quality, service – the parameters for brands to compete are many and to say it’s a battle out there to gain customer loyalty is an understatement; it’s pure savagery! Customers today openly scrutinize and share unforgiving opinions influencing a huge number of people, thanks to social media channels that have given a voice to the masses. No organization can now afford to ignore customer demands. Understanding them is therefore important and data takes the front seat in this scenario. Let’s look at the various options and approaches before brands to leverage data to their advantage.

Loyalty and Customer Data Platform (CDP)

There are no linear paths to purchases anymore. Customers take the curvy path of research before zeroing in on a purchase and this includes e-commerce websites and apps, physical stores, web forms, search engines, social media and so on. Brands need to keep up with this zigzagging of customers and that’s what customer data platforms facilitate ¹. They gather relevant data and present it as a unified view, highly useful in hyper-personalization.

Data Science and Loyalty

While CDPs brings a wealth of data before brands, what to do with it is a question that data science answers. The power of data lies in being able to successfully use it to understand customer behavior at every step of the marketing funnel – from product awareness to activation. Data science brings forth quantifiable metrics that allow marketers to understand at which point a customer becomes disinterested in a product and drops off. It helps bring about personalization at this very point to enable sales conversion. Of course, when personalization is successful, loyalty naturally follows.

Understanding Customers Better through AI-Based Engagement Analysis

While data science brings customers the most effective stages to intervene, artificial intelligence aids in customizing and personalizing that engagement to bring about the desired results. Here’s how they help:

• Making highly relevant purchase recommendations
• Offering insights to make digital marketing efforts effective
• Predicting the likelihood of lead conversion
• Providing direction to sales agents
• Optimizing the lifetime value of customers through predictive analytics

Personalization through Machine Learning Models

According to McKinsey Digital, organizations that successfully personalize customer experiences enjoy the optimization of marketing spends by up to 30% ². Achieving this manually, however, is impossible and automation without intelligence can lead to ineffective personalization. Enter machine learning (ML) and the problem ceases to exist. ML algorithms allow for automatic identification of data (behavioral) patterns and suggest the best course of action without an explicit programming need for each scenario. The right mix of data and ML can help marketers build the perfect model for personalization.

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The term Social Determinants of Health (SDOH) refers to the social, economic, environmental, and demographic factors that influence health outcomes. These are “the conditions in which people are born, grow, work, live, and age, and the wider set of forces and systems shaping the conditions of daily life.”¹ These are also the non-medical factors that could impact a person’s overall health.

SDOH Factors contribute to about 40% of variation in health status among individuals^2. Despite the impact of SDOH on a patient’s health outcomes and costs, providers and payers are not equipped to address the several social determinants including housing, education, food security, and economic stability.

UNDERSTANDING THE PROBLEM

It is important to understand the factors, other than medical, affecting the life of an individual. 
Factors like housing, food security, access to care, etc., are concerns that may affect the health of the population. An approach of SDOH-led quality initiatives lies beyond the four walls of the clinical setting. Data gathering, with screening tools, focus groups, community congregation, etc., is required to gain an understanding of key social factors that impact population health. In the process of data collection, consider factors that are vital to population health, significant for the care giver/provider and health insurers, since these factors might not be related and may belong to different datasets all together.

THINKING BEYOND THE WALLS

New interventions need to be developed for quality improvement activities to tackle issues attributable to SDOH. Also, an intervention that works with one population set may not work for another.  Minimal or no attention to SDOH factors can lead to failure of understanding of the problem for the given population set. Quality improvement programs that directly address SDOH will need to engage representatives from housing, transportation, education, public safety, school, social care, and beyond. Due to the varied spectrum of stakeholders, it might create new challenges for implementation because of separate priorities, funding streams, etc. Nevertheless, it is the only way to address interlocking influences on health. It is to be noted that this approach does not undermine the inclusion and efforts of nurses, caregivers, providers, administrators, etc., in quality improvement activities.

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The world today is flush with touch technology and IoT-enabled devices. The perception is that nothing is off limits when it comes to interactive experiences. Mobiles and laptops that were once considered enablers of experiences are today perceived as barriers for seamless and immersive interactions. Multisensory environments that allow for delightful customer interactions are going to lead in the future. Thanks to the advances in technologies such as IoT, analytics, machine learning and cloud, reaching out to customers today is a completely new ballgame.

The Use Cases

Airports are a case in point. With over half the population living in urban areas today ¹, public spaces like airports are obviously going to be crowded. This poses a challenge to offer great experiences to flyers. Enter face recognition technology – the security screening process can be simplified like never before. Put artificial intelligence into play for resource allocation and crowd management would never be an issue.

Now, let’s consider reaching out to customers in unique ways. Imagine a smart offering by an airline that leverages voice and gesture controls; mixed, virtual and augmented reality; and hologram projections to transport a customer into a virtual world where experiences are as realistic as they get. Picture being able to fly in a virtual airplane to some exotic place. The potential customer would be instantly sold to the idea of such an air travel.

First Adopters are Already Here

Steve Jobs once said, “You’ve got to start with the customer experience and work backwards to the technology. You can’t start with the technology and try to figure out where you’re going to sell it.” Amazon, with its IoT- and analytics-enabled smart stores, seems to have adopted this thought well. Amazon Go store’s system can recognize a customer entering the store. It realizes when a product has been taken off or put back in the shelf. It can move those products to a cart and charge the customer’s online wallet for all the purchases. What can be a more seamless customer experience? In essence, forward-looking companies have already begun exploring smart spaces but it’s not too late for the rest to catch up.

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As networks jumped several Gs and inched towards 4G connectivity and beyond, a world of new opportunities was thrown open. Connected Fleet Management is one such opportunity and it brings a competitive edge to businesses by transforming logistics. There is nothing new about use of technology such as GPS in connected fleets. The change? Ability to collect data from vehicles aiding real-time decision-making.

What is Connected Fleet Management?

In a truly connected fleet, vehicles are fitted with tracking components, usually a combination of GPS and IoT sensors. These devices collect data pertaining to vehicles, traffic, driving conditions, etc., and transmit it via telecommunication-satellite network to the cloud. This data is then sent to a dashboard accessible to fleet managers.   

Why Connected Fleet Management?

Optimized operations and increased productivity are high on the priority list of every organization. Connected fleet management ensures faster delivery to customers at lower costs. Most importantly, it streamlines the entire system in which large fleets and multiple locations are involved, reducing transportation risks and cutting fuel consumption as well as time.

Use of Analytics

IoT devices generate a flood of data. If accessed unfiltered, the sheer amount can be quite overwhelming for the fleet manager, let alone making any business sense out of it. This is where analytics comes into picture. Filtering data and presenting it in the context of the users requirements through a convenient dashboard – that’s what analytics does.

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How to manage the fuel bill?

In the airline business, Air Turbine Fuel (ATF) costs constitute an average 25%-30% of overall Operation Costs. That makes it the single largest operating cost component that impacts the bottom line. The contribution of fuel cost varies largely subject to fluctuations in crude oil prices & US$-linked exchange rate. The chart below that covers data from FY2018 (source: Annual reports of respective airline) highlights that when average crude oil prices were sub US$60/bbl, fuel costs as a % of Ops Cost were largely on the lower side of the range.

A similar chart for FY12, 13 & 14 would have shown much higher contribution to Airline Ops Costs when the oil prices were in triple digits. Refer to below chart (source: IATA)

The crude oil prices (ATF is among the most refined variants of crude oil), as well as US$ linked rate of exchanges are beyond an airline’s control. This fact compels airlines to focus on other key elements within their control that can affect fuel costs, while an airline embarks on network expansion.

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Financial institutions and their customers have always been partners in each other’s progress. But customer experience is a crucial factor in the success of their business. A study revealed that 50% of customers are willing to remain loyal to their bank, albeit the choices many. This loyalty is dependent on banker’s ability to analyze and address the varying needs of customers. 

Changing Human Behavior – A Barrier in the Banking Landscape

Studies show that humans are not always rational in their decisions. Over a period, they have also started counting on shortcuts to resolve problems. This approach, also called heuristics, often results in various forms of biases that lead to judgment errors. This situation poses a challenge for banks whose primary focus has been on changing consumer behavior pertaining to investment discipline, insurance coverage, savings, and credit discipline. The needs and consumption patterns of today’s customers are unpredictable, thanks to the plenitude of choices they have. 

Less wonder that a study revealed that the average rate of application abandonment across a bank’s retail offerings is approximately 40–50%. Also, the non-performing loans have added to the bankers’ woes. 

Behavioral Science – Perfecting the Art of Knowing Customers

Behavioral science is that elusive answer to multiple questions bankers are asking. It is a field of study that deals with human behavior and decision-making. Experts in behavioral science apply the principles of psychology, sociology, economics, and neuroscience to analyze human relationships. 

Traditionally, banks have been leveraging the concept of behavioral sciences in the areas of strategy, product design, and marketing. Nowadays, they face the challenge of mitigating the new issues related to acquiring and assisting customers. Many banks and solution providers have realized that the application of behavioral science to banking technology has now become the need of the hour.

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It’s not uncommon to see employees sipping a cuppa to release their stress at work. But what happens if robots become co-workers? Is that a cause for concern? Not really! According to a Gartner study, by 2023, over 30% of operational warehouse workers will be supplemented, not replaced, by collaborative robots. 

Enterprises across verticals are battling to enter the right market with the right product at the right time. Though it looks more like a demand-supply synchronization task, there’s a lot more at stake. Achieving high performance at every stage of the supply chain is an arduous task. This calls for a heightened degree of efficiency in business operations across all key functions and stakeholders.

Plus, it demands the expertise to adapt quickly to the changes in the market place that’s now being increasingly influenced by new business models and newer technologies.

Intelligent Supply Chains Maximize Throughput
Businesses are expecting more from their supply chains, and doing their bit to maximize its possibilities. Changing customer expectations and competitive pressure creates the need to be more flexible, innovative and cost effective. It’s also obvious that the number of products being rolled out is increasing by the day, and the time to market is shrinking. So, these businesses expect their supply chain to deliver the best possible results, while being aligned to their customer service and business expansion plans. 

Essentials of an Intelligent Supply Chain Strategy

The task of every supply chain is to deliver transformative results to the business, while exceeding expectations of its customers. This can be done only by responding positively to the digital disruptions that are happening in the market place. From an operational standpoint, it’s about optimizing assets, reducing lead times, streamlining processes and collaborating with suppliers.

The choice of the right technology partner definitely plays a critical role in making the transformation happen. Vertical experience, domain knowledge and the standard of alliances form the basis for choosing a partner, but the portfolio of services offered by them is equally important.  Furnished below are some of the essentials to consider.   

• Design and optimization of network, inventory and transport plus post-merger SC asset rationalization. This also helps businesses validate the strategic, tactical and operational plans of the supply chain.
• Planning of demand, supply and production aimed at achieving source-to-pay and manufacturing excellence. This is done by analyzing of existing processes, gauging business-IT alignment and benchmarking KPIs for process improvement.
• Execution for effective management of transport, warehouse, dealers and global trade. This minimizes complexities resulting from high inventory and operational/compliance costs.
• Advanced analytics for data-driven decision making; spans logistics and robotics, aside from spend, factory and predictive analytics. The insights are drawn from multiple sources.

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The retail landscape has changed considerably in the last few years, forcing businesses to transform their sales strategy to stay afloat. Organizations are compelled to lean on newer technologies to increase sales. The change is also a result of consumers preferring online shopping to offline. Here are a few trends:

Faster Shipping

According to Forbes, the current shipping wait time has gone down by a day, when compared to 2018. What does this suggest? Retail businesses are in a race to improve delivery times. People want their deliveries in the shortest possible time and they will prefer a business that will make this happen. Smart supply chains that leverage the power of IoT and analytics will lead the way.

Subscription e-Commerce

Subscription commerce is another technology-led trend that has been growing exponentially. Here, customers, rather than purchasing a single product, subscribe to a constant supply of it. The best example is Dollar Shaving Club, which delivers shaving essentials to it members on a monthly basis. Founded in 2011 with a seed investment of $1 million, it was recently acquired by an FMCG biggie for a whopping 1 billion. The trend indicates that people are willing to fork out money to get the experience they prefer.

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This might sound farfetched but it’s true: A gifting company opted to return 70% of its profits to its customers in the form of rewards. The result: It went on to become one of the fastest growing ecommerce businesses in the region, with a massive base of loyal customers. It’s true that reward points make customers happy. But happy customers need not be loyal. Here’s where a next gen loyalty solution can make a difference by dovetailing both and creating winning experiences. In other words, a win-win situation for both the business and the customer.

Creating an Evolving Customer Engagement Ecosystem

As the customer journey evolves continually, marketers are counting on ways to provide enriched experiences through meaningful engagements. Invariably, most businesses deploy a loyalty program irrespective of its impact on business growth. Many choose to add a new lease of life to their existing programs, while others resolve to reimagine and reinvent their customer engagement strategy.

Cost-conscious businesses might maintain that loyalty programs are losing their relevance in today’s cluttered marketplace. But that’s nowhere close to the truth. The workaround is to upgrade the legacy loyalty platforms, but the effect may not meet expectations. This is ascribed to the fact that these obsolete solutions are usually loaded with a clutch of limitations – clunky architecture, complexity in customization, high level of maintenance, legacy data structures and more. So, the solution lies in total, but gradual, transformation. A next gen loyalty solution addresses most of the issues and paves a path to better customer engagement and understanding.

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