Quick Wins in Enterprise Digital Transformation (yet often ignored) – Intelligent Automation

The modern workplace is seeing widespread usage of machines and automation. Enterprise digital transformation, Artificial intelligence (AI), and automation are changing the tide for businesses globally. This means a significant change in the work culture as employees will have to acquire new skills and adapt to the advanced capabilities of machines. 

As per a recent study1 involving over 600 business leaders from 13 countries, more than 50 percent of respondents confessed to having already invested over $10 Million in intelligent automation projects. The AI market globally is presently growing at a CAGR of 40%, all set to touch $26.4 Billion by 2023.

AI,  along with robotic process automation (RPA), voice recognition, natural language processing (NLP), and machine learning (ML), is allowing businesses to blend automation with human capabilities successfully to create intelligent working environments. 

Automation is driving agility for businesses giving them the much-needed competitive edge over others with quick decision-making powers. Clearly, decision velocity powered by AI-driven insights gives you data supremacy to lead in a highly volatile market.

Making a case for Intelligent Process Automation (IPA)

When automation meets artificial intelligence, you get intelligent process automation to scale up your business. While it allows you to off-load routine, repetitive tasks, it empowers better guardrails for all your automation initiatives. It takes the uncertainty out of the picture and enables more personalized execution and processes.

Intelligent automation enhances the overall customer experience. The speed of response has often been a critical consideration while evaluating the customer experience. Intelligent automation is helping organizations meet customer expectations with personalization. Through customized offers, services, and content, businesses are acquiring and retaining customers.

What do the right IPA endeavors ensure?

  • Agile services due to a significant reduction in processing time
  • Greater flexibility and scalability for being able to operate round the clock with capabilities to scale up and down as required
  • Improved quality control due to greater traceability of events and instances and checks at different levels
  • Increased savings and productivity due to a high level of automation
  • Clear, actionable insights to predict and improve drivers of performance

While there is unanimous agreement on the benefits of intelligent automation, not everyone has leveraged these benefits across the organization. What you need is an enterprise-wide approach that promotes a new way of working.

Adding intelligence to the digital mix

A highly automated world does not focus on reducing the headcount but increasing its potential to do more in an agile manner to solve the business challenges of tomorrow. It relies on structured and unstructured data the company collects from the public domain and other stakeholders rather than depending on traditional methods.

Intelligent automation compels you to rethink key business processes. The sales and marketing team gets deeper segmentation to target and sell through advanced analytics. Those working to strengthen the supply chain get to improve production and distribution by leveraging technologies like cloud and analytics across the value chain. Planning and development teams, on the other hand, rely on data-driven insights to integrate them into product performance and boost innovation.

Alibaba Group2 is a classic example of what you can achieve with intelligent automation.

After making significant strides in eCommerce and retail, it has further revolutionized its business processes with its ‘Industrial Vision AI‘ solution for manufacturing and production. It allows the company to inspect raw materials thoroughly to detect minute defects, resulting in a 5X increase in production efficiency. Its automated warehouse is managed entirely by robots taking precision and efficiency to a whole new level.

Regardless of your goal, you need to create a strategic roadmap to align it with your business priorities. This is not possible unless you assess your digital maturity.

What is the role of IT in successful IPA transformation?

Intelligent process automation (IPA) is a melting pot of technologies enabling significant gains for businesses worldwide. IPA should not be confused with robotic process automation (RPA) as unlike RPA that performs repetitive, automated tasks based on predefined rules and inputs, IPA can understand the context, learn, and iterate to support informed decision-making using unstructured and structured data.

Those who have been able to get the full value of IPA have been the ones who have put IT leaders at the helm of their IPA endeavors. CIOs need to strengthen their core with IPA programs to support automation.

Here’s what we recommend:

  1. Assess the high-level value potential

You may start with help-desk requests since that’s where a significant amount of incidents originate. While tickets with low difficulty levels are resolved immediately, those with more complexity are often escalated to specialized teams. Determine how many such requests were handled the previous year, and by multiplying them by the average handling time (AHT) required, you can evaluate the value of this whole exercise.

For instance, an organization with a significant number of requests for password reset or access can leverage RPA bots that work across multiple applications via the user interface to automate ticket resolution and free up employee capacity. Reducing resolution times and a drop in costs associated with outsourcing help-desk support will thus improve performance and profits.

The effort required for these activities often varies. Everything needs to be evaluated critically from backups and patching to security audits and upgrades to understand the effort involved and the value you can garner by planning activities for automation.

  1. Identify the use cases best suited for IPA

Let’s consider the same example mentioned above. In order to automate incidents, organizations need to first identify the ones ideal for automation. An organization may be effectively logging incidents in detail, but due to the large numbers and complexities, support teams may not respond quickly and effectively.

AI can make sense of the chaos and understand the reasons behind the alerts. It may be trained to make appropriate recommendations or even make better decisions to ensure suitable responses.

  1. Elevate customer experiences with better service

AI and automation are changing the customer service landscape for every industry, from retail to aviation. Boeing has a fleet of passenger service robots that operate via sensors installed in their bodies. They are doing their best to reduce the manual work of cabin crews. Though experts argue a human perspective is required for these robots to do what humans can.

The key is to understand the power of automation and integrate it seamlessly into processes and workflows to complement human efforts and endeavors perfectly, as we did in the case of one of our clients Surge Transportation.

The company links shippers and carriers and has an automated tracking and monitoring system to assign loads. But the pricing and quotation were being done manually. This drained their resources, led to a huge turnaround time, and left a long log of emails, calls, and paper trails.

Trigent critically evaluated the complexities in its pricing mechanism to bring down the turnaround time to less than a second. Apart from 100% pricing accuracy, the company improved profits by 25%, revenue by 40%, and reduced the load processing time by 91%. With seamless carrier integration, the company now processes 4000 more loads per day.

Other use cases where AI and Automation are driving value

Cashier-less stores

Amazon is popularizing the concept of cashier-less stores with Amazon Go and Just Walk Out. Robotization of stores helps save operational expenses and gives shoppers a smart shopping experience.

Automated medical appointment scheduling

No-shows have been the cause of losses of over $150 billion a year for the U.S. healthcare system with every unused time slot costing individual physicians $200 on an average. No-shows also impact the health of patients since continuity of care is interrupted. IPA challenges traditional scheduling methods by ensuring error-free appointment scheduling based on the nature of the illness, the convenience of patients, and the availability of doctors and healthcare facilities. While patients get to choose a date and time for different health issues, follow-up appointments can be scheduled automatically along with reminders.

Automated supply chains

The ideal supply chain is where there is neither wastage nor out-of-stock scenarios. In tandem with machine learning, AI predicts demand based on location, weather, trends, promotions, and other factors. Revenue losses of up to $4Trillion have been caused due to supply chain disruptions following the pandemic with 33% attributed to commodity pricing fluctuations as per a report.

The automobile giant Toyota is using AI in its manufacturing environment to address waste control with its ability to predict when excess parts, products, and practices threaten to impede work.

Intelligent Automation is clearly the Winner streak!

The potential value of AI and automation is immense for different sectors and will vary depending on the type of industry, availability of abundant and complex data, use cases, and other factors. To get the most out of your automation initiatives, it is however important to tide over organizational challenges with the right mindset and approach.

Create impact and value with Trigent

Trigent with its team of technology experts empowers you to stay relevant and competitive. It is equipped with insights and intelligent solutions to dramatically boost your bottom line and improve customer engagement.

Allow us to help you grow your business and increase revenue with strategies and solutions that are perfect for you.

Call us today for a business consultation

References
1. https://www.analyticsinsight.net/intelligent-automation-accelerating-speed-and-accuracy-in-business-operations/
2. https://datacentremagazine.com/technology-and-ai/alibaba-group-adopts-ai-and-automation-singles-day

AI Implementation Checklist – 5 Points to Evaluate Before Adopting AI in Your Organization

Artificial intelligence is now all around us in household gadgets as well as business workflows. AI adoption is rampant across sectors; the global artificial intelligence market is expected to reach $ 266.92 billion by 20271 at a CAGR of 33.2% during 2019-2027. Nearly half of the respondents who had participated in a survey confessed to being interested in AI implementation and machine learning to improve data quality.

No doubt, artificial intelligence is the proverbial genie that does everything we want it to do without even rubbing the magic lamp. But the lack of nuance and failure to spell out caveats can result in AI systems that will make us think twice before we wish for anything.

Believe it or not, misaligned AI can be a nightmare.

A classic case is YouTube2, with its AI-based content recommendation algorithms that led to users accusing it of radicalization. Its constant upping-the-ante approach led users to extreme content in a bid to maximize viewing time. So videos on vegetarianism led to veganism, and jogging searches resulted in ultramarathons. This unintentional polarizing and radicalizing highlights one significant challenge: we have yet to define the goals accurately for our AI systems!

The sad truth is that we don’t even know what we want, at least not from our autonomous systems and gadgets and other possessions. For instance, a self-driving car may be too slow and brake too often just the way it was designed to prevent itself from colliding with nearby objects. But the object could be as insignificant as a paper bag that was blown away by the wind.

What we need is goal-oriented AI born with a solid sense of purpose with excellent human-machine coordination. But only after you have answered the question- Do I really need AI?

Here’s is your ultimate AI implementation checklist

AI has ample scope in many sectors. AI can interact on your behalf with customers, as in the case of chatbots, or help healthcare providers diagnose cancer and other ailments. If leveraged well, it can help you turn a new leaf in critical interactions with your customers. Understanding the potential of AI and applying it to enhance critical business values can make a world of difference to your business. The key is to know where you stand and whether AI can help you attain your business goals.

Identify the purpose

Organizations with successful AI implementations are usually the ones that have assessed its financial impact or conducted a thorough risk analysis for AI projects. Having the right metrics in place gives you a sneak peek into the risks and benefits of AI implementation and how it would perform in those chosen areas. While it may not guarantee a positive ROI, it gives you a fair idea about what to expect. 

Accuracy, for instance, is an important metric, but it’s not enough to understand how well your AI systems are performing. You need to correlate  AI metrics to business outcomes to ensure you get the most out of your investments. 

The smart pricing tool created by Airbnb to eliminate pricing disparities between black hosts and white hosts presents a classic example. While the AI-based system performed the assigned tasks with precision, the business results fell short – widening the gap further by 20%. 

Appoint mixed-role teams for all AI initiatives

Those who have implemented AI successfully will tell you how crucial it is to build mixed-role teams comprising project managers, strategists, application designers, AI researchers, and data scientists to ensure a diversity of thought and skillsets. As per a Garnet Research Circle survey3, skills are the first barrier to AI adoption, and 56 percent of respondents believed new skills are required for new and existing jobs.

AI needs experts for it to evolve to its best version. TayTweets, a promising chatbot by Microsoft, was nothing but fun, and people loved talking to her. Until, of course, she became the nastiest chatbot ever in less than 24 hours, responding with offensive tweets. It demonstrates how horribly things can go wrong when AI and ML go awry when left unchecked.

Diversity in technical acumen enhances the value of AI to customers since the people working with AI know-how and where it should be used to have the most significant impact. Whether you want to hire new people or train existing ones for newer roles and responsibilities is something you will have to decide based on the business initiatives you have in mind.

Make a business case for AI

Businesses need AI for different reasons ranging from data security and fraud detection to supply chain management and customer support. You need to identify the use cases and applications to determine how AI can be effectively used. Organizations depend on AI to analyze contextual interaction data in real-time and compare it with historical data to get insights and recommendations.

Data plays a pivotal role in every aspect of a business. While a lot of emphases is placed on coding, math, and algorithms, many organizations are not able to apply the data acquired effectively in a business context. You will have to understand who you are building these solutions for and what technology framework you will require to do so.

As Moutusi Sau, principal research analyst at Gartner4, points out, “Business cases for AI projects are complex to develop as the costs and benefits are harder to predict than for most other IT projects. Challenges particular to AI projects include additional layers of complexity, opaqueness, and unpredictability that just aren’t found in other standard technology.”

Assess your AI maturity

It is impossible to arrive at a strategy without evaluating where you stand against the AI maturity model. Once you know it, you can decide the next steps. Typically, the AI maturity model has five levels:

Ø Level 1 – There is awareness in the organization, and AI implementation is being considered, but no concrete steps have been taken in that direction.

Ø Level 2 – AI is actively present in proofs of concept and pilot projects.

Ø Level 3 – AI is operational, and at least one AI project has made its way to production with a dedicated team and budget. 

Ø Level 4 – AI is part of new digital projects, and AI-powered applications are now an essential part of the business ecosystem.

Ø Level 5 – This should be the ultimate goal where AI is now ingrained in the organizational DNA and plays a transformative role for your business. 

Look beyond the hype

AI can cause ‘cultural anxiety’ as a significant shift in thought and behavior is necessary for successful AI adoption. A compelling story to help employees understand how AI would be beneficial to all is necessary to ease the resistance they might feel towards the change.  CIOs should recognize their fears and anxiety of the possibility of being replaced by machines and encourage an open dialogue with team members. This will build trust and help determine if the organization is ready for AI.

The hype around AI itself can sometimes be the biggest problem as organizations hurry to hop onto the AI bandwagon with insufficient understanding of its impact. Explains Whit Andrews, distinguished vice president analyst at Gartner, “AI projects face unique obstacles due to their scope and popularity, misperceptions about their value, the nature of the data they touch, and cultural concerns. To surmount these hurdles, CIOs should set realistic expectations, identify suitable use cases and create new organizational structures.” 

 AI to Impact

The biggest mistake organizations make when they invest in AI is that they have too many expectations and little understanding of AI capabilities. Rather than getting caught in the hype, you have to be realistic and evaluate its role critically in furthering your business objectives.

AI is an expensive investment that will give you good returns if you know how to use it. A lot of tools are good, but not every AI tool is suitable for your business. What you need is the right AI implementation strategy created with professional help from those who know AI like the back of their hand.

Adopt AI with Trigent

Artificial intelligence is a defining technology that can be successfully integrated into business workflows and applications. We at Trigent have been helping organizations from diverse sectors, including healthcare, retail, BFSI, and logistics, create AI operating models that are optimized for faster and effective outcomes. 

We can help you, too, with everything from strategy and implementation to maintenance and support.

Call us today to book a business consultation

References

  1. https://www.fortunebusinessinsights.com/industry-reports/artificial-intelligence-market-100114
  2. https://firstmonday.org/ojs/index.php/fm/article/view/10419/9404
  3. https://www.gartner.com/smarterwithgartner/3-barriers-to-ai-adoption/
  4. https://www.gartner.com/smarterwithgartner/how-to-build-a-business-case-for-artificial-intelligence/

Can Salesforce IoT Cloud Fill the Customer Experience Gap?

With the onset of the pandemic, organizations worldwide fast-tracked their digital transformation endeavors overhauling their internal tech stack and data capabilities. An immediate need to move physical operations online largely propelled the process. From closing sales deals over business dinners, we had quickly moved to engaging with clients in digital spaces. Among the many challenges the pandemic ushered in, the one that daunted every organization was ensuring a stellar customer experience against all odds.

Salesforce known for its cutting-edge solutions has been consistently deploying emerging innovative technologies like the Internet of Things (IoT) to empower them. IoT is driving business growth by enabling real-time management of critical systems across industries. It comes as no surprise that the global IoT cloud platform market is all set to cross USD 5262.7 million by 2025.

The high demand for automation across sectors has contributed to the growth of the IoT-connected machines market. By 2027, the global IoT connected machines market is predicted to touch USD 1.3 trillion with North America holding a dominant position with its 2019 revenues standing at USD 91 billion.

Salesforce is helping enterprises combat modern challenges in a digital-first selling world with solutions that can help them soar and serve their customers better.

Explains Warren Wick, EVP AMER Commercial Sales and Chief Revenue Officer, Sales Cloud, “Over the past year, we held more than six million calls with customers to understand what they needed to be successful as they worked to transform their business with more urgency than ever before. We’ve reimagined Sales Cloud to guide every company as they rethink the digital sales experience, from leads to coaching to processing revenue.”

Enterprises are now generating 21% more sales leads every day in 2021 as compared to the previous year thanks to Salesforce. There are several success stories to tell when it comes to Salesforce and the many organizations it has been helping worldwide to drive growth and offer a better customer experience. With IoT Cloud, Salesforce is also helping them bridge the customer experience gap. We will tell you how.

The IoT edge from Salesforce

IoT is an ecosystem; one where physical objects are connected across geographies through an IP address that connects them via the Internet. The devices connect, communicate, and help users come up with real-time insights and analytics to improve business outcomes. Salesforce has been offering IoT services through Salesforce IoT Cloud, Salesforce IoT explorer, and Salesforce Einstein services, to facilitate data collection and analysis.

As per a survey conducted by Forbes Insights in collaboration with Intel involving 700 executives from diverse industries, it was observed that practically all the industries had witnessed significant improvements in several areas including customer experience.

Salesforce IoT Cloud connects devices, apps, sensors, software, etc. to collect contextual data and give a better understanding of the customer journey. This enables enterprises to engage with customers and help them better with proactive customer support. While many have been investing in IoT adoption, their success rate varies greatly. But those who have leveraged the Salesforce platform have been able to integrate the data obtained from IoT into their CRM systems to reimagine the way they serve, sell, and promote. Most importantly, it has helped them take a step further towards their customers closing the experience gap in the most meaningful manner.

Customer experience has always been looked upon as a critical factor for enhancing customer satisfaction, brand loyalty, and revenues. Salesforce understands this well and offers a world of benefits to its users. The top ones include:

Seamless connectivity between devices and users

The profiles of customers are linked to the devices they use and this creates seamless connectivity to streamline operations and respond to events in real time. Tesla’s self-driving cars are a classic case in point and set an example as to how much you can achieve with IoT.

General Motors with its crisis assistance services came as a savior during hurricane Dorian wherein it could help those trying to escape the hurricane with real-time direction, free calls, routing to shelter and basic amenities, an in-vehicle WiFi hotspot, and much more.

Real-time analysis based on context

Without customer context, it would be impossible to analyze past behaviors and take remedial action in real time. Machine learning plays a big role in providing it. Data collected from diverse locations and devices give a realistic picture of what’s happening and where taking into account customer history, service history, and location.

Opportunities to serve better

With so much information at hand, you get to know exactly how the products are performing, whether they are due for maintenance, are there any new updates, is the warranty about to expire, etc. Salesforce IoT Cloud helps you manage all of this with the help of predefined rules that are orchestrated based on performance metrics.

The Sales and Support teams are instantly notified if the product fails to perform as per the expected standard. This kind of data helps in predicting behaviors while providing opportunities to enhance customer retention.

Offers a low-code, user-friendly platform

The fact that Salesforce employs low-code ensures that enterprises don’t have to recruit dedicated staff or a data scientist to manage IoT-related processes. A few clicks and you get all the information you need.

With the right triggers and responses in place, IoT takes away the stress and sends data to relevant platforms. A simple act like generating a lead form for a customer whose product is about to fail can have a positive impact on the customer experience while ensuring a substantial reduction in costs.

A win-win for all

A proactive approach strengthened by the extraordinary capabilities of Salesforce IoT Cloud enables you to understand your customers and engage with them in more meaningful ways. Salesforce allows you to export your IoT data in whichever format you want. It is easy to integrate into diverse business environments and there are multiple use cases that are currently being powered by IoT.

Salesforce Einstein with the help of AI technologies helps teams across departments like sales, marketing, and IT become more predictive and proactive when it comes to offering a stellar customer experience. Salesforce IoT Cloud empowers enterprises with IoT-driven tools and data-driven solutions to build trust and fill the customer service gap efficiently.

As Victor Abelairas, GM of Tridium Innovation at Honeywell Connected Enterprise explains, “Our sellers were able to continue their sales process virtually without skipping a beat. But more importantly, we were able to empower the rest of the company to stay engaged with the sales team and know what was happening with customers at all times, without having the day-to-day interaction in the office that they were used to. At the end of the day, we want to provide a better customer experience by understanding our customers more holistically than we would have otherwise.”

Deliver a better customer experience with Trigent

Our team of Salesforce consultants can help you integrate Salesforce IoT Cloud within your business environment to help you respond faster and serve better.

They understand exactly what it takes to enhance productivity and improve revenues. They can help you understand the many nuances of Salesforce IoT Cloud right from IoT implementation to customization to create engaging customer experiences.

Call us today to book a consultation and discover infinite possibilities with Salesforce IoT Cloud adoption.

Enable Transparent Tracking with NextGen Technologies for Cold Chain Logistics

Even as globalization has made the world a smaller place, the physical separation of the different regions still remains an important reality, especially when it pertains to the movement of goods. The greater this physical separation, greater are the odds of the consignment getting damaged.

This is even more true when it relates to the transportation of perishable goods. Hence, efficient cold chains have become an essential part of the modern supply chain to transport vital, sensitive cargo over great distances and through diverse climatic conditions.

For the range of supplies labeled as perishables, particularly pharmaceuticals and food (produces), quality expires with time as they maintain chemical reactions, which can mostly be alleviated with lower temperatures. Cold chain logistics have evolved with the growing demand for temperature-controlled logistics to transport consumable goods over great distances safely.

It takes coordination and time to move a shipment efficiently. Every delay can have negative consequences. To ensure that the loads do not become compromised or damaged at any point during this process, businesses in the food, medical and pharmaceutical industries are increasingly banking on the cold chain.

The challenges of cold chain transportation

In addition to the usual risk elements that plague our regular supply chains, cold chain logistics has unique issues, such as rising freight costs, product sensitivity, and growing regulatory obstacles.

The recent reports of over 12,000 vaccine doses spoiling due to fluctuations in the truck temperature are evidence of some of the main challenges faced by the industry today. According to the Department of Health and Human Services, the majority of 21 shipments of the Moderna COVID-19 vaccine sent to Michigan were unusable as they got too cold during transit.

The incident has, however, brought clarity to the fact that fleet managers need a better way to access and manage real-time information. The need for real-time data to manage deliveries with efficiency and precision is ever increasing. The insights drawn from this data can help fleet managers, drivers, and businesses work together towards the best outcomes.

The numbers linked to food recalls and losses are also staggering. In 2008, a single recall cost the food companies over $500 mn in settlements. Also, over $161 billion worth of losses were reported in 2010 due to food waste. A precise process to track and trace processes with new technologies such as blockchain, IoT, big data and AI can reduce or potentially eliminate waste and recalls. This can be done by ensuring safe and well-prepared supply chain operations, advanced disposal mechanisms for contaminated food batches, and timely deliveries.

The need for supply chain visibility

Supply chain visibility is crucial to both companies and customers today. According to popular research, 94% of customers are more likely to be devoted to a freight company that offers complete supply-chain transparency. Also, about 39% of consumers say they would willingly switch to a more transparent company if offered the chance.

This trend has some big brands implementing technology such as Blockchain to trace and track every activity across their supply chain. Real-time tracking with RFID enables tracking of tagged objects, creates a system of connected devices that continuously transmit data about their location, product condition, and more.

Given the highly dynamic and unique nature of the cold chain challenges, fleet managers require technologies that have fast information processing capabilities. It should also be able to digest streams of data from million sources at the moment and also be agile enough to acclimate to evolving situations.

Digital Twin is a new, powerful software technique built upon in-memory computing. It has recently emerged with the ability to meet real-time data requirements and is cost-effective to implement, thanks to the Internet of Things (IoT). It helps fleet managers boost their situational awareness by identifying and tackling delivery challenges.

A logistics management system with real-time dashboards, timely reports, and better contextual information can make cold chain management and monitoring easier. Leveraging cloud-based systems equipped with real-time predictive analytics would help identify risk and provide opportunities to improve logistics efficiency.

Reducing cost with real-time cold chain monitoring

A well-run supply chain enhances customer service, saves money, and reduces transit time. The savings don’t come easy, though. They can only be accomplished through some digital transformation in the existing system. It requires some incremental improvement in processes along with a proactive risk-management approach.

Real-time monitoring can help logistics companies eliminate one of the most significant pain points of cold chain logistics – spoilage. Monitoring shipments in real-time and instantly flagging issues such as temperature excursions, hardware/coolant malfunctions, or deviations from handling protocols can help prevent damage in transit. 

While reducing spoilage with a better refrigeration system and managing transportation costs with multi-modal shipments is an option, this involves many hidden costs. Compliance mandates, labor, spare parts, weight, and several other factors contribute to the intricacies of maintaining the cold chain shipping costs.

The use of real-time data enables real-time analytics and response. It provides the opportunity to not only prevent cold chain risk but to eliminate it outright. It helps run a reliable and leaner cold chain taking off the weight of process and quality management with automation. 

The hybrid combination of all accessible data, constant connectivity, robust monitoring devices, and analytics that support data-driven improvements in logistics operations embodies the pinnacle of cold chain management and monitoring systems. Though small, real-time shipment process intervention and monitoring will be vital to your overall logistics efficiency plan.

Although it is logical to think of cost reductions from the bottom-up, the effort to evolve needs to be top-down. A digital transformation of your legacy system will help support the more extensive landscape for your business if it is used right, as in any tool.

Automate your cold chain logistics with Trigent

With a highly experienced team of technology experts having over decades of experience in TMS solutions, Trigent helps revamp your legacy systems to drive revenue and efficiency. We combine the best disruptive technologies, analytics, and trade intelligence to create custom-made solutions to overcome your supply chain challenges. 

We help our customers increase their market value and visibility with seamless integration of the latest technology solutions. Our solutions help you cater to diverse load requirements, optimize routing, market best rates, gather real-time location data, weather forecast & utilization of space, among others.

Build your next-gen cold chain logistics solutions with us. Call us today to book a business consultation.

Effective Predictive Maintenance needs strategic automation and human insight

New-age technologies like Artificial Intelligence (AI), Machine Learning (ML), Internet of things (IoT), and predictive analytics are automating processes and augmenting human capabilities. Together, they set the stage for innovations in different sectors. Manufacturing is leveraging Predictive Maintenance (PdM) that takes preventive maintenance several notches higher.

PdM changes the approach from reactive to proactive maintenance, empowering enterprises to anticipate changes in the system and preemptively manage them. In other words, it helps enterprises predict and avoid machine failure and resultant downtimes. These analytics-led predictions optimize maintenance efforts and facilitate frictionless interdependence.

According to Deloitte, PdM increases equipment uptime by 10-20% and reduces overall maintenance costs and maintenance planning time by 5-10% and 20-50% respectively. With a CAGR of 25.2%, the global predictive maintenance market is set to grow from USD 4.0 billion in 2020 to 12.3 billion by 2025. The growth is fueled by the continued demand for reducing maintenance costs and downtime.

In the current Industry 5.0 environment, the role of maintenance has evolved from merely preventing downtimes of individual assets to predicting failures and creating synchrony between people, processes, and technologies. Predictive maintenance plays its part well, though it does bring along certain challenges that necessitate human intervention.

The PdM advantage

As mentioned earlier, predictive maintenance helps eliminate unplanned downtime and related costs. In an IoT-driven world where sensors, devices, systems, etc. are connected, McKinsey believes that the linking of physical and digital worlds could generate up to $11.1 trillion annually in economic value by 2025.

Maximized runtime also means better profits, happier customers, and greater trust. Predictive maintenance can ease logistics by choosing maintenance time slots outside of production hours or at a time when the maintenance personnel is available. It contributes to supply chain resilience, material costs savings, and increased machine lifespan.

However, PdM is only as good as the data it relies upon. Due to IoT technology, data comes from different sources and needs to be duly analyzed before it can be harnessed to make predictions.

The PdM limitations

We need to consider several elements to translate the information PdM provides into positive outcomes. For instance, depending on usage and maintenance history, it may advise you to replace a certain part or component. But this information can lead to further questions. You may need help in deciding which brand and vendor to consider, whether replacement of the component is a good option, or would it make better sense to replace the equipment entirely.

The forecast is often prescriptive and based on statistical models. While optimizing the operational efficiency of a particular line of business, PdM often fails to consider how it impacts other lines. For instance, when it suggests particular equipment is due for maintenance, it may not be able to offer advice as to where the production/processing needs to be shifted when it’s down. The value it offers will therefore be shaped by how decision-makers respond to predictive data.

Data quality and coverage are critical to make predictive maintenance work for the organization. For data to be suitably collected, integrated, interpreted, and transformed, we need dashboards, notification systems, and a bunch of other things to get started. This requires considerable research and planning to go into its implementation for it to start providing the insights we need.

The key lies in the way you respond

Decision-makers typically respond to predictive data with either hypothesis-driven or data-driven responses. The former stems from past business experiences and determines the plan based on a limited scope of response actions. Data-driven responses, on the other hand, aim to find solutions based on real-time business realities and consider several optimization scenarios to determine the way forward.

In contrast to hypothesis-driven decision-making, optimization ensures that all possible paths are explored and evaluated, relevant constraints are taken into consideration, and cross-functional interdependencies are looked into. A workable scenario based on business realities is thus created with no scope for purely intuitive responses.

Despite the analytics-driven insights, predictive maintenance is incomplete without human judgment. Smart decisions come from the ability to visualize the physical and financial outcomes before enforcing them. High-risk situations might arise, and thus they are best left to human discretion.

A predictive maintenance model for Industry 5.0

Manufacturers need clarity on several variables to understand the implications of failure. A false alarm triggered due to inaccurate predictions can result in a lot of unwarranted chaos and anxiety. However, a missed detection might often prove to be a costly error, sometimes resulting in loss of humans and property. Therefore, while understanding variables, they need to first know how often the variable behaviors occur on the factory floor. Strong domain knowledge along with solid data based on previous failures and scenarios is the key to understanding a machine.

Prediction accuracy will improve if we have adequate data on the behavior of machines when they are very close to failure. Only skilled personnel can determine this; some data sets, despite being important, are harder to collect and yet very critical for decision-making.

If we need data on a machine that breaks just once in a year or two, we need to work closely with machine makers who already possess a large pool of relevant data. Alternatively, we may choose to create a digital or a simulation model to create relevant data sets. The most expensive failures are usually the ones we never expect and hence relevant testing for different scenarios should also be considered.

Looking ahead

The way forward into Industry 5.0 is to create a predictive model that uses analytics, machine learning, and Artificial Intelligence (AI) in conjunction with human insights.

Manufacturers are now relying on predictive models to facilitate smart manufacturing as they struggle with quality issues more often than machine failures. Unusual temperatures, random vibrations, are all telltale signs that a machine may be in dire need of maintenance. Simple data sets can be a good starting point as we scale up with the right predictive maintenance solution. But, in the end, it’s the human insight that can give predictive maintenance its winning streak.

Predict business success with Trigent

At Trigent, we are helping organizations benefit from Industry 5.0 We help them build value with predictive analytics and rise above maintenance challenges. With the right guidance, we help them foster the man-machine symbiosis to harness new levels of operational efficiencies.

Call us today for a consultation. We’d be happy to help with insights, solutions, and the right approach to predict better business outcomes.

What do Brown M&Ms Have to do with Outsourcing?

It is a folklore that has been proven true. In the 80s, Van Halen had strict conditions to remove brown M&Ms from their dressing room at the tour venues, or the show promoter will forfeit their money. The 53 pages typewritten rider contained the condition that along with a wide selection of beverages and food, M&Ms must be provided, but absolutely no brown ones. Years later, David Lee Roth charmingly explains the truth behind this clause in his video – that it was not a silly rockstar misdemeanor excess, but an intelligent safety check measure. Simply put, if the band found brown M&Ms in the dressing room, they will assume the promoters have not taken care of all the electrical and mechanical safety conditions in the rider. Then the band would spend time checking everything with a fine-tooth comb to ensure a safe and flawless show.

In other words, it is a simple assumption that if someone has taken care of the small stuff, they certainly can be trusted to take care of the big things. Just like Van Halen, check if your outsourcing partner has done the small things right. If they did, you could rest assured that they will take care of the big things.

Access to everyone on the team

Did the outsourcing company set up a meeting early to introduce everyone on the team? Such meetings are impactful when done with video. You should have all the details to reach everyone on the team – their emails, phone, skype, etc. Easy access increases communication among the teams. Highly collaborative companies set up Slack channels to communicate instantly with team members. Do you have easy access to the provider’s senior management? The provider’s leadership must check in with you periodically. When needed, you also should be able to get their senior management’s attention.

Transparency in daily activities

You should know what your outsourced team does every day. Though they maybe thousands of miles away and separated by timezones, you should get brief but crisp updates each day – on Slack or via email. Your daily stand up may include them to provide the updates. The remote teams should be check-in code into your repository every day. Weekly timesheets with a judicious amount of details will provide better insight into the time spent on various activities throughout the week.

Empowered Client Partner/Project Manager

Your project manager must your trust to make decisions on their end – as well as demand changes on your side – to ensure mutual success. While you have access to all of your team – who are hyper-focused on coding, testing, etc., you need a client partner who has your perspective to make everyday tactical decisions. They do not lose sight of the forest for the trees. The project manager should make specific, concise, and realistic communication about what they need and expect from each other. Do they take the liberty to suggest process changes? To put is crude, while you may have many backs to pat, you need one throat to choke.

The flexibility of the engagement

Good partners make the engagement flexible for both. Does your outsourcer lock you down with long term commitments and penalties? An outsourcing provider should be agile in terms of process, contracts, and other demands. How easy is it for you to scale your team up or down with relatively short notice, say weeks and not months.

How well do they treat their employees

“Customers will never love a company until the employees love it first.” — Simon Sinek

Companies that treat their employees well, certainly will treat their clients well and value them. When employees are valued with trust, respect, and dignity, they perform at their best. High performing teams will produce results that matter to you. See if your outsourcing vendor provides their employees a good work/life balance, continued carrier training, rewards, and recognition.

In summary, little things make big things happen. See if your outsourcer takes care of some of these small things. If they do, then you can trust that they take care of more complex and critical things too.

Ten Blockchain Benefits for Supply Chain Management

Blockchain, as a distributed database that stores digital information securely is transforming supply chain management in the manufacturing space.

Even though blockchain was initially intended for financial transactions, smart factories are finding different usages for this technology, as it can hold, record, and verify anything of value.

Deloitte describes the potential of blockchain for the intelligent factory as, “Smart factories can operate within the four walls of the factory, but they can also connect to a global network of similar production systems and even to the digital supply network more broadly.”

I draw upon our recent experience with a leading manufacturer of food products in NA to write up this blog to list top ten benefits of blockchain for supply chain management in manufacturing.

1. Increase Automation

Blockchain reduces dependency on paperwork and manual processes. Manufacturing supply chains, if they have even one single bit of inaccurate data can result in disputes, and disrupt operations. This leads to operational inefficiencies and the delays can be costly. Blockchain provides `an automated method for storing information in a tamper-evident digital format. This ability of blockchain can benefit planning, compliance, deliveries and inter-department approvals.

2. Efficiency in Connectivity

Supply chains can benefit from high levels of transparency where data silos are reduced and document authenticity is not compromised. A single source of truth helps operations to move documents from one stakeholder to the next safe in the knowledge that the documents are secure and tamper proof. In addition, error-free document flow ensures the free flow of goods, which help to speed up deliveries. A recent survey by Deloitte states that over 90 percent of consumers’ surveyed list, food product transparency, as a critical factor affecting the purchase and they expect manufacturers to provide the necessary information.

3. Erasing Boundaries

Supply chains that are spread across geographies require the management of transportation, customs collaboration and other such dependencies. Accurate documentation ensures that there are no broken links that can cause delays to supply. Blockchain helps to digitize physical assets and create a decentralized record of transactions making it possible to trace and track.

4. Adding Authenticity

Blockchain ensures that authenticity can be added to products which are produced in one country but supplied to another. Especially in the case of luxury items or pharmaceutical products, blockchain provides the authenticity on its source and preservation through tamper-proof digital documentation.

5. Cooperation Between Man & Machines

Blockchain invokes digital trust between partners, customers and suppliers. Trust is the bedrock of supply chain management and blockchain enables this by enhancing communication between machines and humans. “Blockchains allow us to have a distributed peer-to-peer network where non-trusting members can interact with each other without a trusted intermediary, in a verifiable manner.”- Institute of Electrical and Electronics Engineers (IEEE)

6. Blanket RFQs

Blockchain enables the creation of tamper-proof smart contract that automatically includes multi-party agreements. Smart contracts self-verify terms and conditions and self-execute by releasing payments to concerned parties. Multiple contracts can be created across an entire supply chain where the value and terms are integrated. Though such agreements are tamper-proof, they are outwardly visible to stakeholders across each stage of the chain.

7. Origin Tracking for CRM

In a typical manufacturing supply chain, all stakeholders focus on moving products from one stage to the next. Sometimes the broad picture is ignored for the small, i.e. in this case the customer. Customer tracking from the first order is imperative for long-term relationship management and brand building. Blockchain helps with provenance tracking and ensures that all data is never lost or compromised.

8. Cost Control

A survey of supply chain works conducted by the Digital Supply Chain Institute (DSCI) states that more than one-third of people quoted reduction of costs as the highest benefit of blockchain in supply chain management. By hastening administrative processes, it controls extra costs without compromising transaction security

9. Fraud Management

Digital consumers are making conscious buying decisions and suppliers are searching for newer and better ways to invoke confidence and prove authenticity. Blockchain provides all the proof required by consumers to ensure that compliance has been maintained by the manufacturer. In the food industry, especially, it is estimated that there is a loss of $40 billion every year from food fraud. Food fraud refers to the deliberate and intentional substitutions of inference products for financial benefits. Blockchains can embed origination data and as the food travels down the chain, all other historical data is added and the customer gets the complete origination history.

10. Outsourced Contract Manufacturing

Businesses can maintain more control over their outsourced manufacturing by providing all parties in the supply chain with access to the same information. Less time is spent on data validation and focus remains on improving goods, reducing costs and delivering within stipulated time lines.

Blockchain opens up possibilities to expedite and streamline the everyday processes businesses run on. The beauty of blockchain for supply chain management, specifically, is that it not only simplifies the procurement or precision parts selling process, but it also makes the method safer, faster, and less expensive. Trigent has in-depth domain knowledge and technology expertise of manufacturing systems to help companies optimize their supply chains.

Four disruptive technologies for Banking in 2019

In the brave new world of banking and financial services, technology has become the key to a locker filled with goodies. As a result, it is not impossible to imagine a future where opening a bank or a financial company is as simple as connecting an appliance. In that world, a robot could guide an investor on the best possible options or you could walk into a bank manned by robot tellers. PWC’s report titled ‘Financial Services Technology 2020 and Beyond: Embracing disruption‘ envisages a future where the impossible will become reality. While this list may seem a little too futuristic, banks and financial services organizations are already feeling the tremors of new technology waves that are disrupting existing business models to pave the way for faster, smarter, cheaper operations.

Here are a few emerging technology disrupters:

Distributed ledger technology (DLT)

Algorithms are enabling the collaborative creation of digital distribution ledgers that are far smarter than their paper counterparts. Distributed ledgers are asset databases that can be shared across multiple devices, sites, and geographies where participants can own identical copies of the ledger. Used for various purposes, these ledgers are stored in cryptographic forms and accessed with electronic keys and signatures. Participants, based on rule-based permissions, can update these ledgers, whenever required.

Accelerating change in financial services through Digital Transformation

Distributed ledgers are beneficial to banks as they can reflect changes on a real-time basis. As they are extremely secure, they prevent unauthorized entries, making corruption virtually impossible. As a technology solution, distributed ledgers reside on top of existing applications. Within the field of distributed ledgers, block chain is one more method of distributed ledgers. However, block chain is restricted to a sequential model while DLs do not necessarily fit into a sequential pattern when distributing ledgers. Distributed ledgers may be a good first step forward with immediate benefits for the banking sector.

Artificial Intelligence

Robo-advisor – Fancy though the name sounds, robo-advisors have been around for over a decade. However, it is only in the recent past that this concept has gained popularity. Robo-advisor is an algorigthm-based AI for automated financial advice. This concept has become especially popular for small investors with limited investment options. However, even in cases of larger investments requiring complex decision-making, robo advisors help to automate activities such as tax losses and rebalancing. Robo advisors are useful for single investment goals, and are very good with automated portfolio rebalancing.

As an add-on service, banks can provide value-added services to customers using robo-advisors. Customers can, thus, benefit from customized financial plans and automated investing. One of the key advantages of robo-advisors is the ability to negate human-made calculation mistakes. Uncolored by human emotions, robo-advisors rely purely on algorithms and numbers, reducing chances of errors in investment decisions. In the competitive world of banking, robo-advisors can combine the derive intelligence on existing customers to offer customized investment plans that are beneficial to banks and customers.

e-KYC and identity

Know Your Customer (KYC) is a process adopted by businesses who offer products and services to traders, customers and agents. It is also a process followed by financial services organizations to adhere to regulatory requirements and also to target segment customers. Till recently KYC was a physical activity which required human intervention. While several organizations continue to rely on physical KYC, some forward thinking financial institutions are incorporating eKYC as a procedure for information and verification on customers. By minimizing paperwork and manual labor, eKYC presents a huge opportunity for banks to reduce operational costs without compromising security and information. eKYC reduces paper dependencies thereby helping to avoid identity thefts, and eliminating forgery. Banks can adopt eKYC as it is extremely secure. In the future, eKYC would be the first step forward in a world of secure, paperless transactions.

Cybersecurity

According to the 2017 True Cost of Fraud Study from LexisNexis® Risk Solutions, financial services companies earning at least half of their revenues through digital channels incur up to $3.04 in costs for every dollar lost to cyber-fraud. However, as per the same survey, banks that adopted a multi-layered approach to cybersecurity experience less than 50 percent of the average losses attributed to lapse in cyber security. To ensure cybersecurity, banks are leaning on digital identity intelligence, advanced behavioral analysis, clear-box machine learning technics and integrated risk based authentication. With over one billion new internet users entering the field on an annual basis, the fear of cyber threats can be extremely overwhelming. However, digital identity-based authentication is helping to control fears while providing a real boost to this industry.

To summarize, technology disruptors are providing opportunities and challenges to the banking sector. While challenges such as data breaches, cyber attacks and compromised data will be a fear factor, banks that want to meet the heightened needs of customers should plunge ahead and adapt digital technologies for competitive success.

Internet of Things – Three Popular Development Boards

The Internet of Things (IoT) is developing at a rapid pace, as a result of the availability of small, inexpensive computing hardware. IoT development boards combine micro-controllers, processors, wireless chips, and other components in a pre-built, ready-to-program package. Development boards come in various configurations and here are three popular ones.

Arduino Uno

The Arduino UNO is an open-source microcontroller development board based on the ATmega328P(datasheet) which has:

  • 14 digital input/output pins
  • 6 analog inputs
  • A 16 MHz quartz crystal,
  • A USB connection,
  • A power jack,
  • An ICSP header and
  • A reset button

The Arduino Software (IDE) runs on Windows, Macintosh OSX, and Linux operating systems. The Arduino IDE supports the languages C and C++ using special rules of code structuring.

Applications:

Few applications of the Arduino Uno boards are:

  • Robotics and Control Systems
  • Home and Industry Automation
  • Traffic Light Countdown Timer
  • Underground Cable Fault Recognition
  • Controlling of Electrical Appliances using IR
  • Parking Lot Counter
  • Weighing Machines
  • Medical Instrument
  • Emergency Light for Railways
  • Auto Intensity Control of Street Lights
  • Biotechnology
  • Agriculture

Pros:

  • Inexpensive
  • Cross-platform
  • Simple, clear programming environment
  • Open source and extensible software and hardware
  • Large support of community

Cons:

  • Memory limitations
  • Less powerful
  • Processing power is weaker than the microcontroller
  • Requires effort to accomplish some tasks such as scheduling and database storage

Transform your industry and disrupt the competition with IoT

Raspberry Pi 3

Raspberry Pi is a fully functioning credit card-sized computer, which runs on a customized Debian Linux called Raspbian. Like a computer, a Pi has a memory, processor, USB ports, audio output, a graphic driver for HDMI output.

Pi is a powerful platform based on a Broadcom BCM2837 SoC with a:

  • 2 GHz 64-bit quad-core ARM Cortex-A53 processor
  • 1GB RAM

Raspberry Pi 3 is equipped with:

  • 4 GHz WiFi 802.11n
  • Bluetooth 4.1
  • 10/100 Ethernet port

Advantages of Raspberry Pi over Arduino:

Raspberry Pi Arduino
Multitasking and suitable for complex projects Runs one program at a time, used for repetitive work
Suitable for software projects Suitable for hardware projects
No limiting to programming language Limited to Arduini, C/C++
Built-in Ethernet port for networking Need to connect external hardware and implement coding
Act as a server and communicate to other computers, connected devices. Excels in controlling small devices like sensors, motors, and lights

Applications of Raspberry Pi:

  • Media Streamer
  • Arcade machine
  • Tablet computer
  • Home automation
  • Carputer
  • Internet radio
  • Controlling robots
  • Cosmic Computer
  • Hunting for meteorites and Coffee
  • Raspberry based projects

Pros:

  • Super powerful with lots of memory and processing capabilities. Expandable memory.
  • Linux based OS and now even Windows 10 can be run on top of it to make processing more user-friendly.
  • A lot of GPIOs available, and the more the GPIOs, the more sensors you can interface.
  • If you have experience with Linux, it’s very easy to get started with it, otherwise it will take some time to get the hang of it.
  • Python, C, C++, Ruby, Go and many more can be used to program the Pi exactly the way you can code any computer.
  • People have successfully used Pi to run Open CV , data mining algorithms etc. and connected the results to various applications.
  • In terms of cost, better than an Arduino with Ethernet shield.
  • Great on-line community and endless possibilities of what can be done using it.

Cons:

  • You need good knowledge of Linux systems to get things moving
  • The processing power will be an overkill processing-wise for most of the applications since we will use it only to send data across.
  • Closed source.
  • Power hungry.

NodeMCU

The NodeMCU is an open source firmware, built around a System-on-a-Chip (SoC) called the ESP8266, and features:

  • Wi-Fi capability
  • Analog pin
  • Digital pins
  • Serial communication protocols

Applications of NodeMCU:

  • Geolocation using ESP8266
  • ESP8266 based wireless server
  • Pressure Sensors on Railway Tracks
  • Air Pollution Meter
  • Humidity and temperature monitoring
  • Wi-Fi controlled robot
  • Temperature logging system
  • M2M using ESP8266
  • Make your personal assistant

Pros:

  • Provided inbuilt WiFi functionality
  • Cost-effective
  • Integrated support for WIFI network
  • Low energy consumption

Cons:

  • It is a 3.3V device, so it may not be compatible with some peripherals
  • Lack of official documentation
  • WiFi code takes a lot of CPU power

Trigent helps global companies to apply IoT Command Control and Coordination systems to solve real-world business problems. To know more visit: Disruptive Technologies.

Glossary:

ATmega328P – Single-chip microcontroller created by Atmel in the megaAVR family

BCM2837– Broadcom chip

ESP8266 – A low-cost Wi-Fi microchip capable of either hosting an application or offloading all Wi-Fi networking functions from another application processor.

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References:

Can Small Businesses Benefit from Big Data?

All organizations irrespective of their size generate volumes of data. However, for SMBs, the question is, does the cost and effort justify the value to be derived from data? Data analytics provides deep insights that complement human judgement. Forrester describes the power of big data for small business as “A major disruption in the business intelligence and data management landscape.”

There are several success stories of small businesses benefiting from data analytics. One interesting story is of a zoo in Washington State that was unable to plan daily staffing commensurate with attendance. The zoo’s major source of income was through attendance, which was highly dependent on weather.

By parsing historical data, and analyzing it against decades of local weather data, they found some predictable intelligence. This helped them to fine-tune their plans regarding staffing and promotional activities.

The fear of big data is probably related to the word `big,’ and small companies wonder if they have enough data to qualify for big data. It does not matter. Any data, including visitor logs from a website, is enough to provide vital information on customer behavior.

Another reason why SMBs shy away from big data could be the lack of streamlined processes and information silos. A lease-management company in North Carolina, that manages nearly 1,000 rental properties in the Outer Banks, was unable to accurately predict profitability for homeowners through tourist rentals. With data stored in spreadsheets, the management found it impossible to analyze the data that they had amassed over the years. The company opted for a business analytics tool, which distilled the data and simplified the available information.

Based on the analytics, the company could share vital information with its guests. They could now make rental-pricing recommendations to owners based on seasonal trends and so forth. The business has grown by over 10 percent and costs reduced by 15 percent in the last three years. Big data analytics for small business also helped this company to identify invoice-processing errors, and overall it saved $50,000, annually.

Leverage our Big Data Services to get insights from your Structured and Unstructured Data Repositories

Smaller organizations focused on business needs may not have the time, or even not see the need for streamlined processes. Big data makes allows us to think about the current strategy, economic environment, and competitive landscape. To move from small to medium and from there to large requires processes. Incorporating them now can help to mine data, which will be useful in the short and long term.

To summarize, big data for small business helps small organizations to watch and learn about their customers and their preferences. Even if it is just from their website, it is still intelligence. For retaining customers and acquiring new ones, for up selling and cross-selling, for streamlined processes, which lead to operational efficiency, big data has a hoard of benefits that simply cannot be ignored!

  1. https://www.inc.com/magazine/201407/kevin-kelleher/how-small-businesses-can-mine-big-data.html

To Opt or Not? Can Traditional Industries Use Machine Learning to Garner Business Insights?

Machine learning is a scientific discipline that uses algorithms to learn from data instead of relying on rules-based programming. It works in three stages, i.e. data processing, model building & deployment, and monitoring, with machine learning binding the three together. The power of machine or deep learning cannot be underestimated and as Alexander Linden, Research Vice President of Gartner says, ‘Deep learning can give promising results when interpreting medical images in order to diagnose cancer early. It can also help improve the sight of visually impaired people, control self-driving vehicles, or recognize and understand a specific person’s speech’.

To Opt or Not

Traditional industries have many processes which are governed by rules-based software. This approach is limited in its ability to tackle complex processes. If the rules-based learning can be substituted with self-learning algorithms, then valuable patterns and solutions would emerge.

As a result of digital data and Internet of Things there is a proliferation of data. If you believe this data will help you make intelligent decisions based on patterns, add machine learning. There is no need to add it otherwise as it can make an existing business complicated. Starting with the smaller pieces of the puzzle is better than jumping into it head on. For example, one can collate information from regular reports, apply machine learning to forward-looking predictions.

Machine learning can be useful to detect anomalies, enhance customer services and recommend new products. Manufacturing companies, for example, can benefit from machine learning by self-examining videos where defects can be spotted and automatically rerouted.

Recent developments in machine learning suggest a future in which robots, machines, and devices will be able to operate more independently if they run on self-learning algorithms. This would have far reaching effect in terms of improved efficiency, and cost savings.

Related: Reshaping your business with AI

Machine learning works best on specific tasks where input and output can be clearly stated. If an organization has a sufficient amount of data, with enough variation, machine learning can produce meaningful approximations.

Finally, it is the technical barriers that become the biggest hurdle in the transition process. To address the actual challenges and the perceived ones, companies need to identify expert data analysts who are capable of developing the intricate algorithms that machine learning requires. It will also require a team of engineers who can provide strategic direction, manage quality, and train internal resources on the tool.

Strategize your Business Around The Internet of Things

The Internet of Things (IoT) is here and now. It is the first step to make your business truly digital. And it starts with your things – your line – of – business assets and the data they produce, your cloud services, and your business intelligence tools. By implementing a strategy to take advantage of the opportunity that Internet of Things offers, you can go beyond sustaining your business and make it a disruptor that shakes up the entire field.

Start with Your Things but Avoid “Big Bang” Approach

The IoT can be overwhelming because of the hype and confusion around it. Instead of being panicked by the huge universe of things made up of billions of assets, think about it as the Internet of Your Things. Focus on the right areas of your business that provide quick and tangible return. If you have operations, you can start with it – connecting systems and line-of-business assets to deliver better performance visibility – driving toward predictive maintenance and helping reduce downtime.

Related: Embrace digital transformation, remaster your business, stay ahead of the curve.

IoT starts with identifying the one process, product line, or location that matters the most to you, then making small and incremental changes for a big impact. For example, connect robots on the factory floor with back-end systems and create a production line with more continuous up-time. Add expiration dates to the data set for pharmacy inventory and save thousands of dollars in wasted medications. Connect one handheld device to your inventory system and suddenly you’ve got real-time customer service on the sales floor.

Build on Your Existing IT Assets

Start with your existing IT assets and build upon them. Add a few new assets, connect them using IoT services – Microsoft Azure Internet of Things (IoT) – and the cloud, and enable them to talk to each other, to employees, and to customers. The rapid proliferation of connected assets and devices raises challenges due to the variety of platforms and protocols. Connect your current and diverse line-of-business assets using Azure IoT services which also enables you to pull in data from very large numbers of devices and other business systems.

Use Cloud Computing To Manage Data Deluge and Derive Insights

Cloud computing offers scalable data collection, processing, and analysis capabilities that are flexible to the needs of your business. Cloud solutions give businesses the ability to store and process significant amounts of data, whether it’s latent or in real time; store that data; and apply rules and structure to it for consumption. Cloud computing technology and a flexible consumption-based price structure associated with off-premises hybrid, private, or public cloud compute models have created the ability to deliver new offerings to market, which were simply not achievable in the past.

The cloud also enables more data to be unlocked by enabling you to pull data in, from different sources, and across different line-of-business assets and devices. This data may arrive structured, unstructured or somewhere in between. It may arrive regularly or intermittently. Despite this variability, by providing a framework for the data, it can be automated—through filters, rules, triggers or other means—the intelligent processing of that data.

Partner with a IoT Service Provider For IoT Talent and Skills

To fill the IoT knowledge gap, companies are taking the most common steps – up-skilling existing staff through training on IoT-related skills, recruiting talent with IoT aptitudes, and partnering with IoT service or solution providers.

Companies moving from research to the planning stage need employees who understand the technology underlying the IoT, such as wireless systems, networks and sensors. Once products are in development, sales and marketing employees will need to be able to sell the benefits of the IoT in terms that consumers can understand, and companies will require armies of “data scientists” to analyze all the sensor-generated information.

So, How Do I Accelerate My IoT Journey?

Successful IoT requires significant expertise both from a solution delivery and business advice perspective. You need an IoT partner who can empower you to transform the raw data from your line-of-business assets into actionable insights and business results.

With unique expertise across Cloud, Digital Transformation, Analytics, and Big Data, Trigent can partner with you from ideation to implementation and provide your team the tools and frameworks to help arrive at the perfect business solution

Big Data Analytics Can Play an Important Role in Healthcare

Before you dive into the importance of big data analytics in healthcare, you can learn about the importance of small data vs big data in healthcare.

Global healthcare is in a state of flux with big data analytics emerging as a powerful tool to transform clinical, operational, and administrative functions among others.  The healthcare IT market has grown from basic EMR solutions to specialized hospital information management solutions and healthcare information exchange systems and the Healthcare IT Solutions Market Report predicts growth at a CAGR of 13.57 percent till 2022.  This growth is being fuelled by the increasing role played by big data to manage patient care, reduce costs, and improve quality while keeping one eye steadily focused on operational efficiency.

Related: Innovative Healthcare solutions for ISV’s & Providers

Realizing the potential of big data

Probably realizing the value of big data, The Health Information Technology for Economic and Clinical Health (HITECH) Act created a $30 billion federal grant as an incentive to adopt EHRs, which has helped to generate tons of structured and unstructured data.  This data is finding its uses across functions and services.

Value-Added Services

Insurance companies, for example, are changing their models from a fee-for-service to value-based data-driven payments by using electronic health records that enable high-quality patient care. In the value-based model, doctors, hospitals, and insurance work together to deliver care that is measured by patient satisfaction and this model relies on data from EHRs.

Cost Savings

The same data from EHRs have also helped in mitigating fraud thereby increasing cost savings.  For example, the Centers for Medicare and Medicaid Services prevented more than $210.7 million in healthcare fraud in one year alone.  Insurance companies have also experienced a higher return on investment.  United HealthCare generated a 2200% return on investment in a single year.  Big data analytics has helped these companies to take large unstructured information with regard to historical claims and by using machine learning to detect patterns and anomalies.  This has helped to control overutilization of services, patients receiving the same services from multiple hospitals, and filling out identical prescriptions in various locations.

Predictive Patient Care

By analyzing structured and unstructured data, and using predictive modeling on EHR data, it is now possible to diagnose various illnesses which is helping to reduce mortality rates.  To elaborate, devices are helping to monitor patients’ glucose levels, blood pressure etc.  When combined with machine learning IoT, proactive care for patients is a reality.  Advanced big data analytics is able to work with the unstructured data generated by these sensors.

To summarize, evidence-based medicine relies on patient data which is now growing more in availability.  Capturing data is, however, only the first step.  The next one requires analytics which will not only result in better patient care and engagement but also eliminate redundant testing, reduce expensive errors, and help save lives.

Why Blockchain Technology is Disrupting the Healthcare Industry

Healthcare records, as of now, remain disjointed because of the lack of common architectures and regulations that permit the safe transfer of data between stakeholders.  For example, an updated patient’s clinical data is stored in a database within the hospital or within a defined network of stakeholders.

As a paradigm shift in information distribution, Blockchain technology’s potential in healthcare can be groundbreaking.  Imagine a limitless database, with centralized ownership, where all members cryptographically add, manage and access data. When new data is added all the members on the network are notified.  For patients, this can be their latest medical diagnosis.

To drill down to the specific case of a hospital, Blockchain technology offers an easy way to manage patients’ records where multiple entities are involved.  If a patient, for example, decides to continue his treatment in a different place, the original hospital records need to be electronically transferred or carried as physical documents by the patient and this could be cumbersome and data could be outdated. However, Blockchain, behaving as a single source of truth, would allow the healthcare provider anywhere to have an immediate and accurate view of the patient’s current medications.

The above is only a small example of where Blockchain can benefit the healthcare industry.  There are several areas where it can make a positive impact such as clinical data sharing, public health information, clinical trials, administration and finance departments and patients’ personal data.  To elaborate, Blockchain-enabled IT systems can make a huge difference to clinical data exchange, but on a more transactional level, it can help with claims and billing management.  Research indicates that nearly 5 to 10 percent of healthcare costs are fraudulent and in the year 2016 this resulted in a loss of $30 million in the United States.  By automating the claims and payment processing activities, healthcare companies can reduce administrative expenses.

While the healthcare industry is beginning to acknowledge Blockchain’s power, many fear that the technology’s strength could itself be its Achilles’s heal, i.e. its decentralized approach places it in a position of security vulnerability.  Secondly, Blockchain works on the principal of unique identifier links. If the same person has multiple IDs then this duplication needs to be managed before it can be added to the blockchain.

Related: What you need to know about leveraging Blockchain technology for the healthcare industry

But these transactional challenges can be tackled and technology companies are already working on coming up with solutions.  The believers, for example, say that Blockchain actually helps to enhance security and reliability.  As per the Protenus Breach Barometer report, there were nearly 450 health data breaches in 2016 affecting over 27 million patients.   It is also estimated that 27% of the breaches were caused by hacking and ransomware.  The believers say that with the growth in IoMT (Internet of Medical Things) ecosystems, Blockchain-enabled solutions will not only bridge the gap of device data interoperability, it will also be more secure. For example, hacking one block in the chain is impossible without hacking every other block in the chain’s chronology.

Summary

The blockchain is based on open source software, commodity hardware, and Open APIs.  These components ensure faster and smarter interoperability and help to reduce the burden of handling large volumes of data.  By using industry standard data encryption and cryptography technologies, health care companies can ensure compliance and security. Blockchain data structures can support a wide variety of data sources including patients’ mobile devices, wearable sensors, EMR’s and so forth.  With built-in fault tolerance and disaster recovery, data remains protected.

To summarize, Blockchain technology has carved a niche place for itself in the healthcare IT ecosystem and in the future, Blockchain could remove all blocks in the way of advanced precision healthcare.

The Impact of Artificial Intelligence on the Healthcare Industry

Artificial Intelligence (AI) is predicted to play a game-changing role in patient care. Let’s take a small example of its help in medical diagnosis. Imagine a scenario where a patient walks into a doctor’s office with symptoms indicative of several possible illnesses.  The doctor, to be sure, consults a digital assistant which scans a global database and comes up with a solution based on deep data analysis. The doctor goes on to prescribe further tests to confirm the prediction,  and here too, machine learning helps with comparing the images to the database and confirms the most likely cause of illness.  The doctor has just hastened patient care and with the help of accumulated intelligence has diagnosed the case. Not stopping there, the doctor introduces the patient to a chat-bot that explains the disease and its treatment. It schedules follow-up visits as well as any further investigations, if required. AI has just proved how invaluable it can be in patient care, by shortening the diagnosis to treatment curve.  Where time is of the essence, AI has proved how invaluable it can be.

Machine learning has brought AI to the forefront of healthcare and it is likely that its impact on diagnosing and treating diseases will be unsurpassed.  Recognizing this trend, a 2016 study by Frost & Sullivan, projects AI in healthcare to reach $6.6 billion by 2021, a 40 percent growth rate.  The study further confirms that AI will enhance patient care delivery by strengthening the medical imaging diagnosis process.    As an industry disrupter, AI will create real value for patients by supporting prevention, diagnosis, treatment, management and drug creation.

Technology experts predict that in the next couple of decades AI will be a standard component of healthcare – augmenting and amplifying human effort.  Its role will be as impactful and as quiet as the common X-ray machine.  It will also automate several health care tasks that are time-consuming and which require tons of unstructured data to be converted into intelligence.

While some of the innovations that we are talking about are futuristic in nature, AI has already quietly infiltrated this industry. It is already being used by healthcare players to manage billing, appointment fixing, and logistics planning.  To move into core clinical areas requires an amassing of data and that too has already begun.  With quantifiable data, diagnostics will become accurate and as a result indispensable in medical treatment.  Does this mean that we will see robot doctors in the place of human medical professionals?  Let’s leave that to science fiction movies for now.  What is more likely to happen is AI-enabled medical professionals.

To summarize, we can only imagine AI’s impact on saving human lives, going forward. For example, just imagine people in remote areas with limited access to diagnostics.  AI has just helped the local medical professional to remotely prescribe treatment, deliver medicines through an automated delivery system and prescribe telemedicine.  In a way, it has just helped to shrink the world.

Technology companies focusing on the healthcare segment are investing in Centers of Excellence where AI empowered healthcare IoT will bring about some dynamic changes, not to mention better control over existing processes such as supply chain, inventory management, equipment management, invoicing and drug development and reduce latency, lower cost and deliver operational efficiency. At Trigent, while we solve the problem of productivity, we remain focused on helping healthcare organizations take care of more people with less resources.  We do this by tapping our knowledge, experience and expertise in data and machine learning.