Tag: Ls retail partner

Uncategorized

Case Study : Abu Dhabi government builds one-of-a-kind integrated customer service platform using Microsoft Dynamics 365

Established to lead excellence in government services, Abu Dhabi Digital Authority (ADDA) strives to lead the digital future of Abu Dhabi. Taking advantage of Microsoft Dynamics 365, Power BI, and Azure solutions, TAMM integrates Abu Dhabi government services to provide communities and businesses with a seamless, proactive, and personalized customer experience, one that promises to change the way UAE citizens and residents interact with their government for the better.

Abu Dhabi as a digital innovation destination

Abu Dhabi Digital Authority (ADDA) has a vision that offers a new way of interacting with the citizens and residents in Abu Dhabi and throughout the world. ADDA’s vision embraces technology that delivers value through innovation and service excellence. ADDA is building a digital hub that integrates Abu Dhabi’s 1,600 government and business services with over 55 entities into one central platform. This modernizing journey toward global competitiveness means citizens can look forward to a smarter, happier future with better quality of life—all thanks to the TAMM integrated services platform.

Digital smart government, powered by Microsoft

The TAMM integrated service platform is an intelligent customer support center. Taking advantage of Microsoft Dynamics 365, Power BI, and Azure solutions, TAMM unifies Abu Dhabi’s government and business services into 80 integrated journeys. This integration merges a 360-degree view of customers’ information and their interactions across the government into a seamless, proactive, and personalized customer experience. It promises to completely revolutionize the way citizens interact with the government.

Dynamics 365 creates a seamless omni-channel experience. The portal provides United Arab Emirates (UAE) citizens, residents, and visitors with a range of government services through one access point. Operating with Azure and AI increases efficiency and improve customer experience through fast, agile responses to citizen information requests. It provides stakeholders and field workers with decision-making capabilities through in-depth business intelligence on customer behavior.

“Through Power BI, we are now able to ensure that all government data is viewed, including our services that are unified and user-centric,” explains Fatima Al Obeidli, Director – Contact Center Business Management Department at ADDA. “This drives our commitment to superior customer service. The Power BI unified dashboard replaces the multiple reports of the past, ensuring one-of-a-kind customer service experience.”

Microsoft’s customer-first approach has been proven by its profound understanding of ADDA’s vision. “The aim is to establish a unique service model for Abu Dhabi government. Microsoft is a trusted partner, providing us with tools and mechanisms that empower us to lead the digital future of Abu Dhabi,” explains H.E. Saeed Al Mulla, Director, Government Services at ADDA.

Powered by innovation, inspired by society

“By leading with a modern, reliable, and integrated digital system that serves all walks of life in society, ADDA supports the business environment, attracts more investments into Abu Dhabi, and enhances the Emirate’s global competitiveness,“ says Ali Nimer, Strategy Advisor to the Director General and Head of Digital Excellence Office at ADDA.

Retail ERP Software

Why organizational change projects fail and how to prevent implementation disaster

New IT installations often fail. At least that’s the widespread belief surrounding organizational change initiatives today.

One frequently cited study from the 1993 book Reengineering the Corporation goes as far as saying that as many as 70% of the organizations that undertake a reengineering effort do not achieve the dramatic results they intended. A more recent McKinsey survey of more than 1,500 executives who had undertaken a significant change effort in the past five years found that only 38% of respondents said “the transformation was ‘completely’ or ‘mostly’ successful at improving performance.

After two decades of hearing about high failure rates related to change, it’s unsurprising that business leaders are wary of organizational change projects. Organizational psychologist Nick Tasler explained that these negative biases can create a toxic self-fulfilling prophecy.

“When a change project falls a day behind schedule, if leaders and employees believe that successful change is an unlikely outcome, they will regard this momentary setback as the dead canary in the coalmine of their change initiative. (Never mind the fact that three other initiatives are still on time or ahead of schedule),” he wrote in an article for Harvard Business Review. “Suddenly, employees disengage en masse and then the change engine begins to sputter in both perception and reality.”

Yes, change is hard, and complex IT implementation projects, particularly ERP installations, can be particularly challenging. But it doesn’t mean they are doomed to failure.

So where do you start? How can you choose the right technology for your retail business, and ensure that the implementation project runs as smoothly as possible and you get the most from your investment?

Here are some of the main causes for failure in any organizational change initiative, and how can you prevent them from happening:

Mistake #1: Failure to plan

Issue: An outdated legacy system is impacting business performance, and it needs replacing quickly. In their rush to get the project going, business management jump straight into the implementation without taking the time to develop a well thought-out organizational change management plan.

Solution: Don’t be tempted to cut corners in your planning. Analyze your business, decide what should be prioritized, and understand all the different ways the project will impact your routines at every stage of the process. “Companies should start by analyzing their current and future requirements and processes,” says Gunnar Ingimundarson, Chief Consulting Officer at LS Retail. “How many software solutions are they currently using, and what are they used for? Map out the disparate solutions in the stack, alongside their dependencies and interconnections. The next step is to figure out where they can draw the biggest – or quickest – benefits. Is your POS system not generating the information you need on stock levels and product visibility? Or, are there integrations that repeatedly cause problems or break down? Do you experience missing data? Identify the area(s) where a new system would bring immediate value in terms of savings or returns. That’s where you should start, and that should determine your priorities.”

Once the priorities are set, break the project down into manageable chunks, from pilot phase to initial implementation to company-wide rollout. Consider when it’s most appropriate to start each phase of the installation so you won’t place unnecessary strain on your business during busy times.

Mistake #2: Key stakeholders aren’t onboard, or have unrealistic expectations

Issue: Management want the new technology in place quickly and only focus on the end goals. They get frustrated by how long the project is taking and threaten to pull the plug. Or they wonder why the new software isn’t being adopted widely and successfully when they failed to communicate the changes to everybody in the business and get company-wide buy in.

Solution: All stakeholders need to be committed to the project’s success right from the beginning, and to clearly understand the project’s scope and goals. “Internal resistance can kill even the best implementation project,” says Eric Miller, Regional Director for the Americas at LS Retail, building on his 13 years of experience in software implementations. “Get the buy-in from all stakeholders from the start, and make sure that the goals, objectives and expected end results of the project are clear and communicated from you to the stakeholders, and from the stakeholders to all the customer parties involved. It never pays off to sell a dream you can’t deliver on.”

Bring together personnel from different departments to understand their requirements and what outcomes they hope to achieve from the implementation. Similarly, they need to understand how much time should be devoted to a project like this and ensure project teams are given sufficient time to carry out the work. Set realistic timeframes from the start, and ensure everyone knows exactly what’s required of them.

Mistake #3: Unforeseen changes throw the project off track

Issue: Even the best prepared projects encounter hurdles along the way, but if unforeseen issues arise and major milestones are missed, it can be tempting to throw in the towel and deem the entire project a failure.

Solution: Know that when you’re dealing with a large-scale IT implementation, it’s hard to plan for every eventuality. Be willing to adapt and take a different approach if it ultimately means the project will be a success. “What was deemed to be the best approach initially may need to change – this might even happen after the pilot is completed. I have seen companies that went through multiple pilots before finding the right balance. It’s a learning process, and it’s never over,” says Miller.

It’s worth learning everything you can from the pilot implementation. Instead of rushing on to roll out store #2, take a moment to see how the system is working and to identify any issues that you couldn’t have planned for in your testing environment. Success comes to those who take a considered approach.

Mistake #4: Picking the wrong technology partner

Issue: It may be tempting to go for the cheapest technology provider, but cheapest upfront may not necessarily deliver the long-term business value you hoped for. You quickly realize they can’t help you achieve your outcomes, because they lack drive, or even expertise.

Solution: Before you enter a work relationship, ask yourself who your long-term partner should be and what knowledge they should have in order to support you throughout the project. Are they familiar with the retail industry, its requirements and workings? Do they fully understand your business needs? Can they come up with ideas and solutions when a challenge arises? Once the pilot and system roll out are complete, will they provide the ongoing support that you’ll need?

It’s important to choose an IT partner that has deep knowledge of the industries you operate within. Their technology has to relate directly to your business needs and they need to appreciate the unique intricacies of what you need to be able to do. Consider how they tackle problems as they arise, and if they can foresee challenges and risks that you may not have considered. Your technology provider should be a long-term partner, someone you are confident working with and that you trust to take the right decision for your success. Trident is one of Best ERP Implementation partner in India, UAE & South Africa, you can contact us for any type of ERP Implementation, Support, Training, Resource, etc.

Mistake #5: A focus on short term wins rather than the bigger picture

Issue: The upfront costs of the project are high and management struggle to see the overall business value. They’re concerned about how quickly they’ll achieve a return on investment. They begin to think that it may be cheaper and easier to simply fix their legacy system and keep it ticking over for a few more years.

Solution: While it’s important to focus on the immediate benefits the new solution will bring to your business, it’s just as critical to consider the longer-term impacts too. You may be looking for your solution to quickly boost productivity, deliver business efficiencies and achieve a fast return on investment, but consider other far-reaching benefits it can bring too. How will it positively change the way your employees work? That is, how many work hours will you save by automating tasks that are currently done by hand? How will it enable your business to scale and grow? What other functionality will you be able to add, which will impact the bottom line? “When calculating the software solution’s return on investment, it pays off to keep your perspective open,” Eric Miller suggests. “You can’t really put a price on a platform that will help you streamline the business, cut needless manual processes, and that can scale with your needs and adapt to changing consumer requirements.”

Do you need expert help to make your next organizational change project a success? Get in touch: our team of  can help you get the most from your technology.

Blog Reference : LS Retail Blogs

Restaurant Management ERP

How the self-service trend is transforming restaurants

Modern consumer places a huge value on convenience. A recent report by the National Retail Federation found that 97% of consumers have backed out of a purchase just because it was inconvenient for them. And in quick service restaurants, figures show that lengthy queues can be off-putting: almost three out of four guests say they would leave if there were seven people in line. More than nine out of ten said they would go elsewhere if there were more than 10 people queuing before them.

Taking the example of supermarkets, which have successfully alleviated queues with self-service checkouts, fast food brands are now adopting touch-screen self-service kiosks. And as more report the positive impact of these kiosks, adoption is rapidly taking off.

The rise of self-service kiosks

McDonald’s now has self-service kiosks in all 14,000 of its US restaurants. When it began rolling them out in 2017, it said its intention was to enhance the customer experience by speeding up ordering time, reducing human error and allowing for easier order customizations.

Almost three years on, McDonald’s is living proof of the success of self-service kiosks. During its 2019 Q2 earnings call, CEO Steve Easterbrook said the chain is seeing impressive incremental sales rises from its use of kiosks.

“As we convert the restaurants, we’re getting an incremental sales lift from that, some of which will come through growing and increasing use of the self-order kiosks where we generate higher average checks,” he said.

Interestingly, not only are self-service kiosks delivering on consumer desire for ultimate convenience, they’re altering behavior too. As the use of the technology grows, self-ordering has been demonstrated to boost sales by increasing the average order size per customer, while at the same time lowering costs in the restaurant by improving efficiency.

There are some compelling statistics to illustrate the impact. When the Dodgers Stadium concession stands in the US tried out new self-service kiosks, the average order size increased by 20%. Similarly, Subway noted that kiosks encourage more consumers to purchase add-ons and generally spend more.

The traditional experience

Lee heads to his local Easy Burger for lunch. He isn’t a regular customer so he doesn’t know the menu well. It’s a busy Friday afternoon in the restaurant and as he joins the queue he starts scanning the menu board behind the counter to see what he would like. When he gets to the front, he still isn’t quite sure what he wants and spends a few more moments deciding. By this point he’s a bit flustered. He doesn’t want to hold up the queue, so he quickly orders the standard burger meal with no cheese and large fries. It’s noisy in the kitchen, and the server asks Lee to repeat his order. She presses the buttons on the cash register to input Lee’s choice, and politely waits for him to decide which drink he’d like before finalizing the order and taking his payment. This all takes place in the midst of noises coming from the kitchen, voices of customers waiting, and general pressure from people standing in line waiting for their turn. It’s clear to see that there are several opportunities for mistakes, delays and general frustration from both the customer and the cashier.

The self-service experience

What would the same scenario look like with a self-service kiosk? Again, Lee heads to Easy Burger to pick up his lunch. It’s busy, but Lee heads to a self-service kiosk, where he doesn’t have to queue to place his order.

Lee hasn’t actually used one of these kiosks before, but because it looks just like a large version of his mobile phone and all the menu items are clearly labelled, he has no qualms about trying out the technology. With nobody standing behind him putting pressure on him to quickly place his order, Lee feels he can take the time he needs to choose his lunch. He scrolls through the menu and takes in the appealing pictures of food, drinks, and add-on items. He ends up trying out a new meal deal and customizes his burger (no pickles, extra onions and mushrooms), adding the curly fries with cheese – they look too good not to try them. It’s a pleasant, stress free experience.

After selecting the items, Lee taps his credit card on the contactless card reader and heads to the counter to wait for his order. He can clearly see his order on the screen above him, so he know there are five orders before his – a bit of a wait, but not too much, before it’s ready. A few minutes later, his number is called out. He picks up his food and heads straight to a clean, empty table. That’s another added bonus. With fewer employees required at the counter, they can spend more time in the kitchen, speeding up food preparation, and on the floor, making sure the restaurant stays clean and tidy.

Embracing the trend with LS Central

Restaurants are embracing the trend in different ways. Some are buying self-service kiosks running systems and interfaces separate from what is used across the rest of restaurant. This decision entails a lot of extra work, as these systems will have to be integrated with the IT setup, and then updated and maintained individually over time.

Thankfully, there is another option. If you selected a unified restaurant management solution like LS Central, you enable customers to order and check out for themselves using the exact same POS system that cashiers use at the manned tills. This wouldn’t be possible with many other restaurant management systems because they are too complicated, and can’t be used effectively without previous training.

Not LS Central.

There are more benefits, too. You can easily amend and customize the looks of the kiosk to suit your needs. Just as you would customize the POS, you can change interface and menu options to suit your branding, and apply the changes across all your locations – no headache of setting up the brand look for each individual kiosks.

Simple menu customization also means you have the freedom to A/B test ways to present the menu to see what works best and yields the greatest results. When you get smart about how you showcase your menu, you can capitalize on more upsell and cross-sell opportunities and promote the higher margin menu items. Perhaps you choose to highlight your latest meal deals on the top level of the screen or maybe you collapse certain menu choices at different times of the day to speed up the ordering process.

Digitalized self-ordering also helps you to manage your inventory proactively. So, if you find that beef burgers are running low, but you have plenty of chicken burgers available, you can quickly change the menu on the machines to highlight mouth-watering chicken burgers on the first-level menu instead. Or perhaps your smoothie machine breaks down: instead of striking a line across the item, you can temporarily remove those items from the menu and highlight alternatives such as milkshakes and ice creams.

Making a difference in the kitchen

This streamlined, user friendly experience transfers into the kitchen too. Orders are automatically sent to the kitchen display system (KDS) and presented clearly to your kitchen staff. The system can further help improve efficiency by routing orders to the proper food preparation stations, organizing items so they are prepared in the right order and ready at the same time, and alerting staff when orders have been in the queue too long. At the same time, front-of-house staff (and customers) can see the exact status of each order and pick them up as soon as they are ready.

Setting your restaurant business up for long-term success

Despite the current success of kiosks, many restaurateurs wonder whether this is just the flavor of the month. Will kiosks still be popular with consumers another year or two down the line? While we can’t predict the future, we can see that the big brands have been cautious. A quick service restaurant expert and Forbes contributor wrote an article in 2010 called “Quick-service restaurant kiosks: What’s taking so long?” One reason why we’re seeing wider adoption now is because the technology is proving its success.

As kiosk usage rises, customers will increasingly expect to find self-ordering options in fast food outlets. Research shows that customers are more likely to visit restaurants with self-service kiosks and a growing number prefer this option to interacting with a cashier behind the counter.

As more diners seek ultimate convenience, faster ordering and more payment options, self-service kiosks are proving the best solution to meet their demand and enhance the transaction journey from start to finish.

 

blog Reference: https://www.lsretail.com/blog/how-the-self-service-trend-is-transforming-restaurants

Microsoft Azure Cloud Services, Uncategorized

Advancing Azure service quality with artificial intelligence: AIOps

We are going to share our vision on the importance of infusing AI into our cloud platform and DevOps process. Gartner referred to something similar as AIOps (pronounced “AI Ops”) and this has become the common term that we use internally, albeit with a larger scope. Today’s post is just the start, as we intend to provide regular updates to share our adoption stories of using AI technologies to support how we build and operate Azure at scale.

Why AIOps?

There are two unique characteristics of cloud services:

  • The ever-increasing scale and complexity of the cloud platform and systems
  • The ever-changing needs of customers, partners, and their workloads

To build and operate reliable cloud services during this constant state of flux, and to do so as efficiently and effectively as possible, our cloud engineers (including thousands of Azure developers, operations engineers, customer support engineers, and program managers) heavily rely on data to make decisions and take actions. Furthermore, many of these decisions and actions need to be executed automatically as an integral part of our cloud services or our DevOps processes. Streamlining the path from data to decisions to actions involves identifying patterns in the data, reasoning, and making predictions based on historical data, then recommending or even taking actions based on the insights derived from all that underlying data.

 Infusing AI into cloud platform and DevOps – with AI at the center of Customers, Engineering, and Services.
Figure 1. Infusing AI into cloud platform and DevOps.

The AIOps vision

AIOps has started to transform the cloud business by improving service quality and customer experience at scale while boosting engineers’ productivity with intelligent tools, driving continuous cost optimization, and ultimately improving the reliability, performance, and efficiency of the platform itself. When we invest in advancing AIOps and related technologies, we see this ultimately provides value in several ways:

  • Higher service quality and efficiency: Cloud services will have built-in capabilities of self-monitoring, self-adapting, and self-healing, all with minimal human intervention. Platform-level automation powered by such intelligence will improve service quality (including reliability, and availability, and performance), and service efficiency to deliver the best possible customer experience.
  • Higher DevOps productivity: With the automation power of AI and ML, engineers are released from the toil of investigating repeated issues, manually operating and supporting their services, and can instead focus on solving new problems, building new functionality, and work that more directly impacts the customer and partner experience. In practice, AIOps empowers developers and engineers with insights to avoid looking at raw data, thereby improving engineer productivity.
  • Higher customer satisfaction: AIOps solutions play a critical role in enabling customers to use, maintain, and troubleshoot their workloads on top of our cloud services as easily as possible. We endeavor to use AIOps to understand customer needs better, in some cases to identify potential pain points and proactively reach out as needed. Data-driven insights into customer workload behavior could flag when Microsoft or the customer needs to take action to prevent issues or apply workarounds. Ultimately, the goal is to improve satisfaction by quickly identifying, mitigating, and fixing issues.

 

AI for Cloud: AI Ops and AI-Serving Platform showing example use cases in AI for Systems, AI for DevOps, and AI for Customers.

Figure 2. AI for Cloud: AIOps and AI-Serving Platform.

AIOps

Moving beyond our vision, we wanted to start by briefly summarizing our general methodology for building AIOps solutions. A solution in this space always starts with data—measurements of systems, customers, and processes—as the key of any AIOps solution is distilling insights about system behavior, customer behaviors, and DevOps artifacts and processes. The insights could include identifying a problem that is happening now (detect), why it’s happening (diagnose), what will happen in the future (predict), and how to improve (optimize, adjust, and mitigate). Such insights should always be associated with business metrics—customer satisfaction, system quality, and DevOps productivity—and drive actions in line with prioritization determined by the business impact. The actions will also be fed back into the system and process. This feedback could be fully automated (infused into the system) or with humans in the loop (infused into the DevOps process). This overall methodology guided us to build AIOps solutions in three pillars.

AIOps methodologies: Data (Customer/System/DevOps), insights (Detect/Diagnose/Predict/Optimize), and actions (Mitigate/Avert future pain/Optimize usage config/Improve architecture & process).
Figure 3. AIOps methodologies: Data, insights, and actions.

AI for systems

Today, we’re introducing several AIOps solutions that are already in use and supporting Azure behind the scenes. The goal is to automate system management to reduce human intervention. As a result, this helps to reduce operational costs, improve system efficiency, and increase customer satisfaction. These solutions have already contributed significantly to the Azure platform availability improvements, especially for Azure IaaS virtual machines (VMs). AIOps solutions contributed in several ways including protecting customers’ workload from host failures through hardware failure prediction and proactive actions like live migration and Project Tardigrade and pre-provisioning VMs to shorten VM creation time.

Of course, engineering improvements and ongoing system innovation also play important roles in the continuous improvement of platform reliability.

  • Hardware Failure Prediction is to protect cloud customers from interruptions caused by hardware failures.  Microsoft Research and Azure have built a disk failure prediction solution for Azure Compute, triggering the live migration of customer VMs from predicted-to-fail nodes to healthy nodes. We also expanded the prediction to other types of hardware issues including memory and networking router failures. This enables us to perform predictive maintenance for better availability.
  • Pre-Provisioning Service in Azure brings VM deployment reliability and latency benefits by creating pre-provisioned VMs. Pre-provisioned VMs are pre-created and partially configured VMs ahead of customer requests for VMs. As we described in the IJCAI 2020 publication, As we described in the AAAI-20 keynote mentioned above,  the Pre-Provisioning Service leverages a prediction engine to predict VM configurations and the number of VMs per configuration to pre-create. This prediction engine applies dynamic models that are trained based on historical and current deployment behaviors and predicts future deployments. Pre-Provisioning Service uses this prediction to create and manage VM pools per VM configuration. Pre-Provisioning Service resizes the pool of VMs by destroying or adding VMs as prescribed by the latest predictions. Once a VM matching the customer’s request is identified, the VM is assigned from the pre-created pool to the customer’s subscription.

AI for DevOps

AI can boost engineering productivity and help in shipping high-quality services with speed. Below are a few examples of AI for DevOps solutions.

  • Incident management is an important aspect of cloud service management—identifying and mitigating rare but inevitable platform outages. A typical incident management procedure consists of multiple stages including detection, engagement, and mitigation stages. Time spent in each stage is used as a Key Performance Indicator (KPI) to measure and drive rapid issue resolution. KPIs include time to detect (TTD), time to engage (TTE), and time to mitigate (TTM).

 Incident management procedures including Time to Detect (TTD), Time to Engage (TTE), and Time to Mitigate (TTM).
Figure 4. Incident management procedures.

As shared in AIOps Innovations in Incident Management for Cloud Services at the AAAI-20 conference, we have developed AI-based solutions that enable engineers not only to detect issues early but also to identify the right team(s) to engage and therefore mitigate as quickly as possible. Tight integration into the platform enables end-to-end touchless mitigation for some scenarios, which considerably reduces customer impact and therefore improves the overall customer experience.

  • Anomaly Detection provides an end-to-end monitoring and anomaly detection solution for Azure IaaS. The detection solution targets a broad spectrum of anomaly patterns that includes not only generic patterns defined by thresholds, but also patterns which are typically more difficult to detect such as leaking patterns (for example, memory leaks) and emerging patterns (not a spike, but increasing with fluctuations over a longer term). Insights generated by the anomaly detection solutions are injected into the existing Azure DevOps platform and processes, for example, alerting through the telemetry platform, incident management platform, and, in some cases, triggering automated communications to impacted customers. This helps us detect issues as early as possible.

For an example that has already made its way into a customer-facing feature, Dynamic Threshold is an ML-based anomaly detection model. It is a feature of Azure Monitor used through the Azure portal or through the ARM API. Dynamic Threshold allows users to tune their detection sensitivity, including specifying how many violation points will trigger a monitoring alert.

  • Safe Deployment serves as an intelligent global “watchdog” for the safe rollout of Azure infrastructure components. We built a system, code name Gandalf, that analyzes temporal and spatial correlation to capture latent issues that happened hours or even days after the rollout. This helps to identify suspicious rollouts (during a sea of ongoing rollouts), which is common for Azure scenarios, and helps prevent the issue propagating and therefore prevents impact to additional customers.

AI for customers

To improve the Azure customer experience, we have been developing AI solutions to power the full lifecycle of customer management. For example, a decision support system has been developed to guide customers towards the best selection of support resources by leveraging the customer’s service selection and verbatim summary of the problem experienced. This helps shorten the time it takes to get customers and partners the right guidance and support that they need.

AI-serving platform

To achieve greater efficiencies in managing a global-scale cloud, we have been investing in building systems that support using AI to optimize cloud resource usage and therefore the customer experience. One example is Resource Central (RC), an AI-serving platform for Azure that we described in Communications of the ACM. It collects telemetry from Azure containers and servers, learns from their prior behaviors, and, when requested, produces predictions of their future behaviors. We are already using RC to predict many characteristics of Azure Compute workloads accurately, including resource procurement and allocation, all of which helps to improve system performance and efficiency.

Looking towards the future

We have shared our vision of AI infusion into the Azure platform and our DevOps processes and highlighted several solutions that are already in use to improve service quality across a range of areas. Look to us to share more details of our internal AI and ML solutions for even more intelligent cloud management in the future. We’re confident that these are the right investment solutions to improve our effectiveness and efficiency as a cloud provider, including improving the reliability and performance of the Azure platform itself.

 

Note blog reference: https://azure.microsoft.com/en-in/blog/advancing-azure-service-quality-with-artificial-intelligence-aiops/

Uncategorized

Is your business ready to take supply chain management to the next level?

When you lack deep visibility and insight into your supply chain, you leave money on the table

It turns out what you don’t know as a manufacturer can and will hurt you. For too long, manufacturers have settled for siloed and inconsistent information, as well as manual processes, to understand and manage their supply chain. Why? Because for a long time, these systems were good enough to keep production going.

But plenty of manufacturers don’t want to settle for good enough. IDC predicts that by 2019, 50% of manufacturing supply chains will have benefited from digital transformation, and the remainder will be held back by outdated business models or functional structures. Smart manufacturers understand that supply chain transformation is necessary. They are connecting assets across their factories, gaining visibility into their supply chain, and acting on insights from increased visibility to address inefficiency, as well as increase customer satisfaction and margins.

Don’t accept operational inefficiencies as a limit on your business

Supply chain management is complex, so doing it right requires a solution that simplifies and consolidates disparate information, while retaining flexibility. Data from the sales process, suppliers, order fulfillment, product performance, and customer service all matter for a full understanding of the supply chain. The core tools for accomplishing this fall into three categories: IoT-enabled visibility and services, powerful analytics, and cloud-delivered data visualizations.

Like many aspects of manufacturing, IoT is the starting point. The best way to lower production costs is by using a single IoT-friendly platform to integrate back and front office processes. Using IoT-based modeling to create digital twins, manufacturers can understand in real-time the amount of wear and tear on parts and adjust designs in response. This insight can help identify simple inefficiencies like sourcing a part from the company that’s always supplied it, rather than buying a similarly-performing part at a lower cost from another supplier.

Powerful analytics is the next step in transforming your supply chain. A truly intelligent system for supply chain management dynamically adjusts distribution, as well as production, to accelerate the speed of delivery. By using built-in analytics and machine learning, public data like weather conditions can be used to create richer, more accurate schedules and delivery forecasts. On top of that, opportunities to consolidate or expedite shipments can be automatically identified using artificial intelligence—passing lower shipping and order fulfillment costs on to customers.

Finally, consolidating all this information won’t completely optimize your supply chain without the ability to easily visualize and manage it. That’s why a real-time and mobile-delivered view is so crucial. Understanding how to solve problems is hard enough; there’s no need to complicate it further by using different systems to identify where problems are occurring. Decision makers on the factory floor or in global headquarters need instant access to relevant information, and the collaborative power to communicate with or work alongside employees anywhere in the world. These investments in operations put manufacturers in position to embrace new technology and adjust to whatever business challenges they may be facing.

Get the tools to transform with Microsoft Dynamics 365

The power of a supply chain management and operations platform that combines all these capabilities at cloud speed and scale is obvious. Companies positioned to digitally transform their supply chains will see accelerated time to market and reduced cost to enter new markets or scale new lines of business. Microsoft supports flexibility in deployment, enabling you to leverage existing investments while expanding with either a cloud or a hybrid model that includes both on-prem and cloud systems. That can shorten deployment from months to days and ensure security and analytics capabilities are consistent across every location and tuned appropriately for every team.

Microsoft Dynamics 365 ends the artificial separation of ERP and CRM and makes it easy for employees to collaborate and even role-switch to engage customers or address supply chain issues. Only Dynamics 365 unites the front office and the back office with a single end-to-end system for managing every aspect of your business, all backed by industry-leading enterprise cloud. That means manufacturers can develop at the pace and scale that’s right for them, while taking advantage of current investments such as existing productivity and technology stacks. With Microsoft, consistent development practices and R&D investments combine to offer manufacturers rich analytics, embedded intelligence, partner-created applications, and the ability to collaborate worldwide.

Retail ERP Software

How AI and AR can help retailers stay in business in moments of crisis

Store closures and social distancing have caused a rise in demand for virtual tools and technologies that bring the shopping experience into consumers’ homes. Beauty brands, which were among the first to try out AI and AR to enhance the consumer experience, are increasingly using the technology to suggest products based on people’s preferences and unique characteristics, including skin tone and face shape, as well as to help customers virtually try on products before committing to a purchase. Even before the Covid-19 crisis, the technology had already proved its worth. Figures from Perfect Corp, which develops virtual makeup technology, show that virtual try-on technology generated 2.5 times higher e-commerce conversions for brands and decreased return rates by more than 8%. Trident is offering Cloud Based Retail ERP Software to manager retail operations effectively

As the technology develops and becomes more sophisticated, consumers are progressively trusting in AI to help them make purchase decisions.

“Consumers trust AI to curate a choice of products, services and experiences that reduce complexity and make life more fulfilling,” writes Andrew Cosgrove, Global Consumer Knowledge Leader & Lead Analyst at EY. “AI knows its “owner” so well that it suggests new and unexpected product ideas or experiences they love.”

Digital suddenly finds itself one of the main commerce channels for retailers. We expect AI and AR are here to stay, as more consumers become aware of their virtues when it comes to convenience, and as these technologies can help retailers to continue trading regardless of what happens in the real world.

Here are four ways to make AI and AR work for your business:

1. Bring the in-store shopping experience to your customers’ homes

AI and AR take online shopping to a whole new level by making it possible for consumers to choose from selected products picked out just for them, try out new experiences and test products in ways they wouldn’t have been able to previously – all from the comfort of their homes.

Early pioneers of AI- and AR-powered online shopping include opticians, who realized that consumers still want the option to try on glasses and see what styles suit them before committing to a purchase. Virtual fitting technology has made this possible, with some retailers further elevating the experience using AI to automatically suggest the perfect frame to suit your face.

Indeed, AI lends itself to verticals where consumers may find themselves bogged down in complex choices. Instead of having to scroll through hundreds and hundreds of beauty products, for example, new services such as My Beauty Matches use AI-powered algorithms, and using the consumer’s previous searches, purchases, and known preferences, they suggest items from large databases (in this case, there are over 400,000 products) that couldn’t be easily browsed by the consumer.

Advances in machine learning help brands to identify consumer styles and preferences to gain a granular level of customer understanding, so they can optimize each customer’s individual journey.

“In one of the worlds we modeled, consumers valued time much more than money,” Andrew Cosgrove, Global Consumer Knowledge Leader & Lead Analyst at EY, said. “Their personalized AI learned about their unique preferences and used those insights to buy most of the things they needed. This allowed them to spend their time shopping only with brands that reflected their values and purpose.”

2. Find the right items across infinite aisles of products

The most successful AI and AR experiences today tend to be delivered by retailers that have large item assortments and the ability for consumers to personalize their choices. Home goods and furniture retailers are a clear use case, with many using the technology to help customers choose products that will fit beautifully into their homes and match their existing décor.

Online furniture retailer Wayfair is known for using AI to target customers with personalized recommendations. The company’s search algorithm extracts the customer’s style preferences from their search history to present a selection of furniture that is likely to appeal. Another service allows customers to take a photo of a furniture piece they like and match it to a similar item in the Wayfair inventory, which holds millions of products.

AR then takes this a step further by giving consumers the ability to virtually see how products will look in situ before committing to a purchase. Returns on investment have been demonstrated with increased conversion and reduced returns.

AI is proving its worth in fashion too, helping customers choose clothing that will fit them best by analyzing previous purchases and suggesting sizing based on their profile. Iconic jeans brand Levi’s uses an AI-based chatbot to help customers find the perfect pair of jeans. It asks consumers their preferences when it comes to fit, rise, amount of stretch and wash, and asks what size they are in another brand to determine the best size in Levi’s and suggest the right pair.

And in beauty, brands are using the technology to offer services such as instant foundation shade matching and advanced skincare analysis, as well as matching consumers with products and looks that will suit their complexion, style and occasion.

3. Anticipate consumer demands

One of the major benefits that retailers can draw from AI and AR experiences is the amount of data they can collect about their consumers along the way. This data, if collected appropriately, can be used to improve the accuracy of stock and inventory requirements forecasts throughout the year.

“As consumers browse, test features and make purchases, they are providing retailers with an entirely new set of data points,” writes Hamaad Chippa on Retail TouchPoints.

Retailers can then use this information to rethink product assortments for a better shopping experience, or to develop highly targeted marketing campaigns that lead to greater conversion rates. For example, a customer who just bought a whole load of supplies from a pet store for their new kitten is likely to want to sign up for home deliveries of cat food.

AI can also help retailers target consumers with promotions that are more likely to lead to purchases based on past browsing and purchase history.  “Whether that is 10% off online, 15% in-store or free shipping, customers automatically receive the promotions that are most likely to make them convert,” writes Imtiaz Mohammady on Forbes.

4. Optimize inventory, both present and future

Retailers are increasingly using AI to gain a better picture of what stock they hold currently and what they will need in future. Although many are used to interrogating their data to anticipate demand and make accurate forecasts, AI is taking the game to new heights by helping them to better prepare for unexpected events and predict and prevent potential supply chain disruptions. Advanced forecasting and replenishment tools can help react to changes, recalculate new quantities to reorder for stores and warehouses, and adjust the supply systems to keep up with demand.

Supermarkets in particular are turning to AI models to help keep store shelves stocked. Companies such as Walmart have been trialing robots that scan aisles for missing products. And in its Walmart Neighborhood Market store in Levittown, New York, the company is exploring the possibilities of AI and using real-time information to help store associates know more precisely when to restock products, so that items are available on shelves when they’re needed.

“Customers can be confident about products being there, about the freshness of produce and meat,” Mike Hanrahan, CEO of Walmart’s Intelligent Retail Lab, said in a press release. “Those are the types of things that AI can really help with.”

Technology to overcome challenges

Retailers need to be able to offer rich and convenient customer experiences, and both AI and AR are very quickly opening up new possibilities that could transform retail, making it more adaptable to diverse situations.

In the not too distant future, AI and AR could help to make retail experiences even more personalized, unique, collaborative and social. Without moving from their sofa, customers may be automatically sent a selection of outfits and beauty products curated just for them in anticipation of an upcoming family party. They will simply scroll through the selection, try everything on virtually, mark down what they want to purchase, and wait for everything to arrive well in time for the big event – no hassle, ultimate convenience.   Contact us for Retail ERP Software demo or write us at info@tridentinfo.com

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How Manufacturing Industry Transformed using Microsoft Dynamics 365

The future of manufacturing will be defined by the quality of investments companies are making today

In the not too distant past, efforts in manufacturing to optimize productivity and increase customer satisfaction were viewed as separate endeavors. Today, the convergence of physical and digital trends is disrupting these kinds of assumptions.

Manufacturers today care about integrated digital and physical systems, improved visibility, increased efficiency, additional flexibility, and lower costs. They want to connect equipment and factories, leveraging data from the factory floor to the customer call center to improve every aspect of their operations.

But this is just the beginning. Digitization is fundamentally changing the way manufacturers do business, enabling a customer-centric approach while optimizing operations. Digitally empowered manufacturers engage customers throughout the product lifecycle from design to field service. They sell value-add services to complement the product sales, opening new revenue streams and strengthening their customer relationships. And they are revolutionizing delivery of these differentiated services, using technology like augmented reality to combine the eyes of a technician in the field with the insights of an expert back at headquarters.

Capitalizing on these trends isn’t limited to large, well-resourced manufacturers. Across all kinds of manufacturing operations, the opportunity to digitize and transform your business has never been more accessible.

Imagine your business transformed

The Microsoft vision for supporting digital manufacturing embraces the seismic shifts in the industry today. We’ve created solutions that provide a unified and flexible approach across front office and production floor processes. Our approach enables transformation in six ways:

 

Optimize supply chain operations through better visibility and collaboration

By collecting, integrating, and visualizing global supply chain data worldwide, manufacturers gain better visibility into their operations from production to sales. For example, one of the world’s largest industrial automation firms found that by automating the collection and analysis of data from remote installations across the petroleum supply chain, they strengthened their competitive advantage with a faster time to market. Improved access to supply chain data is also the basis for better collaboration across production, supply, service, and sales. 

Streamline the management of assets, products, and production

With a consolidated view that unifies process oversight and provides real-time insight, manufacturers can institutionalize efficiency gains and use connected devices to monitor and resolve issues remotely. One leading manufacturer of industrial robots enabled 24-hour continuous uptime using this approach. The additional insights into production and customer usage also allow manufacturers to provide value-added services like ongoing monitoring and proactive support.

Engage customers in powerful new ways

To deliver personalized and contextual engagement across any channel, manufacturers must provide customers with more visibility and build trust through fast and convenient responses. This engagement approach is built on a combination of predictive analytics, the ability  to deliver value-added services at scale, and guided or self-directed service that’s relevant to customer needs. With the implementation of a connected platform for sales through service, a leading home technology manufacturer not only solved potential problems remotely before customers ever felt the impact, but provided custom differentiated offerings based on unique customer usage and purchasing history.

 Transform service centers into profit centers

Thanks to the ever-decreasing cost of IoT sensors, sophisticated mobile devices, and cloud-based data aggregation, manufacturers can improve service quality and margins by offering remote monitoring and proactive maintenance services that supplement break/fix support. By more intelligently coordinating technicians equipped with mobile and virtual reality tools, companies can leverage existing expertise and minimize costly engagements. A leading tire service and manufacturing company found that by combining customer records, technician availability, and back-end inventory in a single mobile-friendly system, it could provide a seamless user experience as well as improve its service delivery.

 

understand their business more deeply, from customer usage through supply chain sourcing and production. With IoT-enabled parts, assets, and products, manufacturers can gain the insights needed to innovate. Data from connected products and equipment can empower developers, engineers, and technicians to collaborate. For example, teams can identify overengineered or faulty components and track product usage in the field to improve future designs. When a leading information and communication technology company implemented remote monitoring, they decreased time to production as well as accelerated the cycle of innovation using a data-driven approach.

Empower employees to work more effectively

When a company can provide 360-degree views of customer assets and work order history, technicians are empowered by a better understanding of not only the job in front of them, but of other similar and successful field service engagements. This goes hand in hand with empowering service agents to provide instant feedback, using machine learning to find and follow similar cases for successful troubleshooting, and scheduling a visit or evaluation. A leading auto manufacturer wanted to save money by unifying their siloed customer service and customer engagement while providing employees with better tools to understand customer sentiment. To accomplish this, it implemented a system to connect production and project management with their customer relationship management systems in order to deliver personalized service and recommendations to their customers. 

Introducing Microsoft Dynamics 365

For manufacturers, Microsoft Dynamics 365 ends the artificial divide between CRM and ERP systems and supplements necessary capabilities with rich analytics, embedded intelligence, and the convenience people expect from consumer apps on their phone or tablet. Dynamics 365 unites the front office and the back office with a single end-to-end system for managing every aspect of your business, at the pace and scale that’s right for you. Digital transformation isn’t accomplished overnight and leveraging current investments is a key component of any successful approach. With Microsoft, you can optimize across all your processes while laying the foundation for connecting advanced technology in the future.

 

Blog reference: https://cloudblogs.microsoft.com/dynamics365/bdm/2017/05/30/manufacturing-transformed-microsoft-dynamics-365
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