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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organizational change initiative, and how can you prevent them from happening: Mistake #1: Failure to plan Issue: An outdated legacy system is impacting business performance, and it needs replacing quickly.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,

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6 tips to help you win at omni-channel

Even if retailers have been talking about investing in omni-channel for over a decade, many still lack basic omni-channel capabilities. For example, only 5 percent of retailers can successfully give consumers the ability to start and finish a sale in their preferred channel, Luxury Daily reports. But consumers aren’t waiting for retailers to get their act together. In the past year, almost 9 out of 10 (88%) shoppers have researched and selected options online before heading out to a store, the Ecommerce Foundation reports. And when in-store, Google reports, 50% of them turned to the internet: to research products they’ll then discuss with the sales staff, to remind themselves of what to buy, to see product specs, and more. Retailers have no time to waste. They need to be where their customers are, with answers to their questions, smooth and simple shopping journeys, and timely information and support. In your journey on improving your omni-channel strategy, here are seven points on which you should concentrate your efforts: 1. Be consistent with your branding There’s nothing worse for an omni-channel brand than to offer a disconnected experience across the different channels. Successful brands are consistent in both brand image (think color scheme, corporate story, style, products, voice) and quality of service (customer support, return policies, personalization, product suggestions) in-store, on their website, on the loyalty app and on social media. International coffee company Nespresso is a great example of cohesive visual branding. The graphic design and color palette are kept consistent throughout the channels, and they function as a common thread that guides every step of the customer journey, from e-commerce website, to mobile app, to the confirmation e-mail customers receive after placing an order — all the way to the package that arrives to the customer’s doors. If your offline presence is hip, youthful and colorful, but your app is dull and offers few options to interact with products; if you emphasize customer service, but then don’t respond timely (or don’t reply at all!) to customer queries on Twitter; if customers receive different information depending on which representative they contact – you will confuse and lose customers. 2. Unify the sales channels Customers want to be able to see on your website whether the latest smartphone model is available in gold in a specific store. They want to go on your e-commerce, and add to their cart that art deco lamp they saw in your shop while they were on holiday. They want to send back at their convenience the too-tight shoes they bought in one of your store locations. These are all common requests – and yet, too many retailers can’t fulfil them. That’s because many of them are still using separate best-of-breed, badly-integrated solutions. “Many retailers have pieced together disparate systems and processes to try and create a holistic shopping environment, but it really doesn’t provide what the customer is looking for,” says Kathleen Fischer, director of marketing at Boston Retail Partners, Boston. The result is Inability to see what products are available in real time – or where they are located; Inability to accept returns across channels; Risk of selling items that are not in stock; Inability to offer highly in-demand services like click & collect, ordering from store, or online inventory search. The only way you can fulfil these demands is by implementing technology that gives you centralized visibility and control over your stock, locations and sales. A unified commerce platform like LS Central gives you the visibility you need to know how many items are still available and where they are located exactly, and lets you easily accept exchanges and returns across your whole retail network. 3. Be honest and clear Research shows that seventy percent of online shoppers abandon their shopping cart before finalizing their purchase. The most common cause? Unclear or excessive shipping costs, which often become apparent too late in the buying process. Successful retailers display their sales conditions in clear and visible format on their website. Take, for example, sportswear and outdoors retailer Transa. When you browse the product selection, the key sales conditions (delivery time, shipping costs, return conditions) are stated clearly next to each item. Buyers know the conditions of the sale before they have added an item to their cart, so they can make an informed decision early in the shopping journey. To decrease the chance of shopping cart abandonment, create a relationship of trust with your customers, and be upfront about shipping prices and times, shipment restrictions and special conditions. You don’t want to tell a customer that their country is not eligible for delivery when they are ready to check out a full cart of products. 4. Let customers check product availability According to Forrester research, 71 percent of customers expect to be able to see available inventory online. Leading retailers are taking note, and even taking it one step further: on its e-commerce website, IKEA lists where each item is available alongside the quantity left in stock in each store. Even if you don’t want to go to such lengths, your product listing should at least: Be complete and updated. Customers should be able to see in which location the product they want is available, in their preferred variant. If you use a unified commerce system, you can maintain information in one database, and then distribute it to the e-commerce, POS and back office. This way, both staff and customers can access the same real-time data, and if the inventory changes, for example if an item is sold, this is instantly reflected on all touchpoints. Include detailed product information. When shopping for items online, customers don’t have the touch-and-feel element. Make up for it by including the item materials (or ingredients), any special care warnings, warranty information, and special return policies. If you stock similar products, you should ensure that you give enough information so consumers can make an informed choice. Better yet, include a comparison table. Feature clear, high-quality pictures. According to research by Field Agent, 83% of consumers believe product images are very important when selecting and purchasing a product. If you can, consider including videos: according to a survey by Wyzowl, 80% of people say that product videos give them more confidence when purchasing a product online. From showing

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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.   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. 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. 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

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Microsoft Dynamics 365 for Manufacturing dashboard displaying production planning, inventory, supply chain management, and quality control.

Manufacturing’s Biggest Inefficiency Isn’t the Plant Floor — It’s the Gap Between Systems

INTRO A machine on the shop floor and a service technician in the field often work off completely different data — one sees production output, the other sees a support ticket, and neither sees the customer’s purchase history. Dynamics 365 for manufacturing exists to close exactly that gap, by ending the divide between CRM and ERP instead of running them as separate systems that happen to sit on the same network. Here are the six shifts that gap-closing actually produces on the ground. 1. Supply Chain Visibility That Goes Beyond a Dashboard Collecting and visualizing supply chain data across every location does more than create a nicer report — it changes how fast a disruption gets caught. Manufacturers using remote monitoring across distributed installations have shortened time-to-market by catching supply issues before they cascade into production delays, rather than discovering them after a shipment is already late. 2. Asset and Production Management, Consolidated Into One View When production oversight and real-time equipment monitoring sit in one system instead of three, manufacturers stop reacting to breakdowns and start resolving issues remotely before they cause downtime. This is the operational basis for near-continuous uptime models in equipment-heavy manufacturing — and it also opens a second revenue line: monitoring and proactive support sold as an ongoing service, not a one-time sale. 3. Customer Engagement Built on Usage Data, Not Guesswork Personalized service at scale requires predictive analytics and self-service options that are actually relevant to what a specific customer does with the product — not a generic contact form. Manufacturers with a connected sales-through-service platform can flag potential equipment issues before a customer notices a problem, while also tailoring offers based on that customer’s real purchasing and usage pattern. 4. Service Centers as a Profit Center, Not a Cost Center Falling costs for IoT sensors and mobile devices have made remote monitoring and proactive maintenance commercially viable additions to standard break/fix support — not just a premium add-on for enterprise accounts. Combining customer records, technician availability, and inventory into a single mobile-accessible system is what lets a service team actually deliver on that model instead of just theorizing it. The Data Advantage: Better Products, Not Just Better Service IoT-connected parts and equipment feed usage data back to engineering — which components fail early, which are over-built, how products actually get used in the field. That feedback loop is what shortens the cycle between a design flaw and a fix, rather than waiting for failure reports to pile up. 5. Technicians Who See the Full Job, Not Just the Ticket A 360-degree view of a customer’s asset and service history changes what a technician can do on-site — they’re working from context, not just a work order. Paired with machine learning that surfaces similar past cases, this turns troubleshooting into pattern-matching against real precedent instead of starting from zero on every call. 6. One System Connecting the Floor to the Front Office Manufacturers that unify production and project management data with CRM stop treating customer service and customer engagement as separate departments working from separate records. The practical result is service and recommendations grounded in what a customer has actually bought and experienced — not assumptions. Why Dynamics 365 Specifically Dynamics 365 for manufacturing removes the artificial line between CRM and ERP, running both on one system with embedded analytics rather than bolting a reporting layer on top of disconnected tools. For a mid-size manufacturer, this matters less as a technology upgrade and more as an operating model change — supply chain, service, and sales working from the same data instead of reconciling three versions of it. Curious what a unified CRM-ERP model would look like on your production floor? Talk to Trident about a Dynamics 365 manufacturing assessment.

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