Tag: microsoft dynamics 365 for hospitality

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Issue: An outdated legacy system is impacting business performance, and it needs replacing quickly.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

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

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
Uncategorized

How to get ready for the rise of mobile payments in retail

The retail payment space is going through a sea change, and the Starbucks mobile payments app is a shining example of that. Despite being specific to one retailer, in 2018 the app held the title of top mobile payment app in the US. During that year, 23.4 million people aged 14 and above used the app to make a POS purchase at least once every six months, according to estimates from market research firm eMarketer. Even though in 2019 it was finally overtaken by Apple Pay, which racked up an estimated 30.3 million users compared to Starbucks’ 25.2 million, the widespread adoption of the Starbucks app shows that  retailers can get true value out of mobile payments.

Key to Starbucks’ success has been its ability to combine convenience, ease and reward in the payments experience. Its Mobile Order and Pay functionality lets users order ahead of time and skip queues. The app is also integrated with the Starbucks Rewards loyalty program, allowing customers to automatically earn points (called Stars) and start earning free drinks and food. Customers can even add a tip to purchases. The value of using this app to pay is clear and simple: you can save time and money at the till, and access rewards and special offers at the same time.

Stores upgrade their payments options

Over the last few years cash has been losing its market share to electronic payments methods, which give consumers a faster, more secure and convenient experience when shopping both in store and online.

As consumer preferences move away from traditional payment methods towards mobile checkout technologies such as Apple and Android Pay, contactless card payments and direct bank transfers, retailers must be prepared to accept these new methods.

In the US, it’s estimated that around 70% of retail stores are now equipped to accept Apple Pay and similar mobile payments apps. As more credit card companies and banks shift to chip-based cards, retailers are forced to upgrade their checkout systems and. Those who think ahead are opting for readers that can also accept payments from smartphones using near-field communication (NFC) technology. Invest in contactless payment options

Millions of consumers now have contactless-enabled cards in their wallets and mobile payment apps on their phones. This tap-and-go technology is fast becoming the norm for customers – and therefore something they expect when making a purchase. Contactless transactions are particularly popular for smaller ticket purchases in convenience stores and supermarkets, and now frequently replace cash. This kind of technology also offers many benefits to retailers, including decreased checkout times, increased card use and an improved consumer payments experience.

Combine convenience and rewards

While contactless payments are an in-store essential, retailers must also consider a holistic payments strategy across all channels to ensure they’re meeting their customers’ expectations and delivering a seamless experience. That means embracing tools and technologies that harness consumer trends around cashless payments and connect both the digital and physical, enabling customers to order ahead and pay in advance, pick up reward program points regardless of the channel they shop via, and take advantage of new “buy now, pay later” options such as Klarna and Laybuy. Being able to offer a wide variety of payment options will be critical as retailers look to build their presence in an increasingly digital marketplace that is characterized by convenience and speed.

Explore digital wallet providers

While businesses like Starbucks decided to build their own mobile app, most retailers do not need to go down this route. That’s because digital wallet providers like Apple Pay and Google Pay are already designed to make setting up mobile payments fast and affordable.

Today, there are dozens of digital wallet payment providers for retailers – and consumers – to choose from. It’s worth talking with your existing payment provider to understand what options they have available as you develop your own mobile payments and digital wallets strategy.

Be open to payments innovation

As payment solutions are transforming from purely transactional to more customer oriented, the friction of payments will continue to fade with further innovations coming to market.

Invisible payments, for example, offer consumers ultimate convenience and completely automated payment options. Although they’re still in their infancy in the retail space, they’re being driven by businesses like ride-sharing app Uber, which automatically collects payment once a customer has reached their destination. Innovative retailers such as Amazon and Dutch supermarket brand Albert Heijn are already trialing invisible payments in stores with success. These shopping concepts allow customers to simply pick up or scan the products they want and leave without having to check out. Instead, payment is automatically deducted from their account.

“Connected cars, automatic replenishment via internet of things devices, and increasingly friction-free checkout experiences at the physical point of sale are just a few of the practical applications of invisible payments,” Worldpay’s Global Payment Trends report said.

As retailers plan for the future, then, it is in their best interests to be aware of the latest payments innovations and to consider how they will play out in their industry.

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