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Tag Archives: Strategy

3 Ways a Microsoft Dynamics 365 Supply Chain Management and EDI Integration Enhance E-Commerce CRM Strategy

March 6, 2021   CRM News and Info

With the increased e-commerce demand caused by the dependency on online shopping, it is more important than ever to provide seamless customer experiences. If your company sells a product online, you know there’s so much more than just taking orders. A trusted solution like Microsoft Dynamics 365 Supply Chain Management as part of Dynamics 365 CRM helps you manage service, resources and inventory; resolve product issues quickly; mitigate delays and accelerate your time to market.  

There are two prominent e-commerce business models. The first — you handle it all. You have your own factory, sales, service and marketing departments and a warehouse. Supply chain management, logistics management, business process management and customer service are typically managed by the CRM. The second model, a rapidly increasing trend, is to outsource parts of the supply chain including manufacturing, and delivery and distribution via a Third-Party Logistics (“3PL”) partner, which typically leaves customer service and marketing to you.  

2021 03 03 14 27 00 625x407 3 Ways a Microsoft Dynamics 365 Supply Chain Management and EDI Integration Enhance E Commerce CRM Strategy

If you operate using the second model, you know that working with the multiple business processes and systems of your partners can create challenges in maintaining an agile supply chain. Dynamics 365 Supply Chain Management unifies your data, but if you work with multiple supply chain partners, you must also create secure connections to each third-party system, which means multiple connections to manage individually. Integrating your CRM with an Electronic Data Interchange (“EDI”) is an effective solution that enhances visibility and real-time data access across the entire outsourced supply chain.  

When Dynamics 365 Supply Chain Management integrates with an EDI partner, it creates efficiencies and process improvement in three key ways for logistics, supply chain management, compliance, sales and marketing.  

1) Synchronized Data 

Even if you never touch your own product, when your data is synchronized across all your partners, you have access to the data you need in real time. You can answer customer inquiries as well as fulfill demand quickly and efficiently. The manufacturer gets timely orders on when to produce product, and 3PLs know exactly when and where to deliver the order. Inventory transparency will help you answer buyer inquiries. Issues like shrinkage and lost orders are communicated so you have full visibility of your inventory and issue resolution.  

2021 03 03 14 28 39 625x348 3 Ways a Microsoft Dynamics 365 Supply Chain Management and EDI Integration Enhance E Commerce CRM Strategy

2) Data Analytics 

Access to insights and data analytics aids marketing strategy as well as helps you to better research and respond accordingly to service-related issues. Dynamics 365 Supply Chain Management delivers fast reporting, analytics, predictive insights and intelligence to help with data-driven decisions that improve operations. Reporting and analytics is available across planning, production, inventory, warehouse and transportation management.   

With Dynamics 365 Supply Chain Management and an integrated EDI solution, you can easily access business impact analytics based on data across all supply chain partners that you need to support your own internal analysis. This includes classic financial data such as sales territory, regions, product types and sales.  

3) Manage Multiple Data Connections Seamlessly 

Whether you work with a couple third-party partners or several, you as the seller must communicate with multiple providers in the supply chain electronically. A standard data integration from your Dynamics 365 would have to be set up with each partner individually. But an EDI integration brokers those connections. This means less for you to manage, and more time and resources that you can spend on customer service or marketing strategies.  

2021 03 03 15 33 11 625x314 3 Ways a Microsoft Dynamics 365 Supply Chain Management and EDI Integration Enhance E Commerce CRM Strategy

Integrating your Dynamics 365 Solutions with an EDI Solution  

Using Microsoft Dynamics 365 Supply Chain Management helps you to streamline your operations, build agile processes, and optimize resources to consistently deliver your products on time and create the best customer experiences.  

If you work with supply chain partners, instead of creating multiple connections, you can work with an EDI that provides one simplified, centralized place to manage and broker all the traffic and transactions back and forth between Dynamics 365 and your various suppliers. Dynamics 365 integrates with the EDI to enhance tracking of all your transactions, inventory management, and fulfillment. The EDI partner already has the connections and transactions established with all the common trade partners in the supply chain. They work with all the online e-commerce sites and common 3PLs and can easily build a new connector as you need. The partner doesn’t just provide EDI connections, they also round out their offering with portal service for vendors and customers. 

Read the full blog here.  

Get Started with JourneyTEAM 

JourneyTEAM was recently awarded Microsoft US Partner of the Year for Dynamics 365 Customer Engagement (Media & Communications) and the Microsoft Eagle Crystal trophy as a top 5 partner for Dynamics 365 Business Central software implementations. We have heard from many companies looking for a flexible, scalable solution to address their challenges with the eCommerce outsource business model. We can provide demos and full custom introductions to determine if an EDI integration with Dynamics 365 is right for your service and marketing operations. Contact JourneyTEAM today! 


George Sagen 519x625 3 Ways a Microsoft Dynamics 365 Supply Chain Management and EDI Integration Enhance E Commerce CRM StrategyArticle by: George Sagen – ERP Solution Architect | 801-938-7821

JourneyTEAM is an award-winning consulting firm with proven technology and measurable results. They take Microsoft products; Dynamics 365, SharePoint intranet, Office 365, Azure, CRM, GP, NAV, SL, AX, and modify them to work for you. The team has expert level, Microsoft Gold certified consultants that dive deep into the dynamics of your organization and solve complex issues. They have solutions for sales, marketing, productivity, collaboration, analytics, accounting, security and more. www.journeyteam.com

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How to know if federated learning should be part of your data strategy

February 13, 2021   Big Data

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AI researchers and practitioners are developing and releasing new systems and methods at an extremely fast pace, and it can be difficult for enterprises to gauge which particular AI technologies are most likely to help their businesses. This article — the first part of a two-part series — will try to help you determine if federated learning (FL), a fairly new piece of privacy-preserving AI technology, is appropriate for a use case you have in mind.

FL’s core purpose is to enable use of AI in situations where data privacy or confidentiality concerns currently block adoption. Let’s unpack this a bit. The purpose of AI systems/methods/algorithms is to take data and autonomously create pieces of software, AI models, that transform data into actionable insight. Modern AI methods typically require a lot of data, collect all the necessary data at some central location, and run a learning algorithm on the data to learn/create the model.

However, when that data is confidential, siloed, and owned by different entities, gathering the data at a central location is not possible. Federated learning very cleverly gets around this problem by moving the learning algorithm or code to the data, rather than bringing the data to the code.

As an example, consider the problem of creating an AI model to predict whether patients have COVID-19 given their lung CT-scans. The data for this problem, CT-scans, are obviously confidential, and are owned by various different entities — hospitals and medical and research facilities. They are also stored all across the world under very various different jurisdictions. You want to combine all of that data because you want your AI models to be able to detect all the forms in which the disease has manifested in CT-scans. However, combining all this data in the one location is not possible for obvious data confidentiality and jurisdictional reasons.

Here’s how federated learning bypasses the confidentiality issue: A worker node, which is a computing system capable of machine learning, is deployed at each hospital or facility. This worker node has full access to the confidential data at the location. During federated learning, each such worker node creates a local AI model using the data at the facility and sends over the model to the central FL server. Note that the confidential data never leaves the client site — only the model does. A central server combines all of the insights from the local models into a single global model. This global model is sent back to all the local worker nodes, which now have insights from all the other worker nodes without having seen their data. When you iterate on these steps many times, you end up with a model that is, in many cases, equivalent to a model that would have been built if you’d trained it on all the data in the same place. (See a schematic illustration of the process below.)

Federated learning was initially developed by Google as a way to train the Android keyboard app (GBoard) to predict what the user will type next. Here the confidential data being used is the text that the user is typing. However, it turns out that the data confidentiality issue appears in many guises across industries. Indeed, you will face this problem if you are

* a maker of autonomous vehicle and you want to combine confidential video and image data from across your vehicles to build a better vision system,

* a bank and want to build a machine learning based anti-money laundering system by combining data from various jurisdictions, possibly even other banks,

* a supply chain platform provider and you want to build a better risk assessment or route optimization system by combining confidential sales data from multiple businesses,

* a cell service provider and you want to build a machine learning model to optimize routes by combining confidential data from cell towers,

* a consortium of farmers and you want to build a model to detect crop disease using confidential disease data from the members of your consortium,

* a consortium of additive manufacturers and you want to build AI-based process controllers and quality assurance systems using confidential build data from members of your consortium.

An important point to note about the above examples is that the owner of the data can be different units of the same organization but in different jurisdictions (as in the bank and cell service provider examples) or clients of the same organization (as in the autonomous vehicle maker and supply chain service provider examples), or completely independent units (as in the consortium of farmers and additive manufacturer examples above, and the hospitals/COVID-19 example described earlier).

You can use the following checklist to see if federated learning makes sense for you:

I will end by emphasizing that, if you are able to combine your data into a central location, you should probably go for that option (barring cases where you want to, for instance, future-proof your solution). Centralizing your data may make for better final model performance than you’ll be able to achieve with federated learning, and the effort required to deploy an AI solution will be significantly lower. However, if it turns out that FL is just what you need to remove your barrier to AI adoption, part two of this series will provide you with an overview of how to do that.

M M Hassan Mahmud is a Senior AI and Machine Learning Technologist at Digital Catapult, with a background in machine learning within academia and industry.

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Apple’s self-driving car strategy may be stuck in neutral

February 9, 2021   Big Data

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After weeks of confusion and contradictory news, it has almost become confirmed that Hyundai-Kia will start manufacturing Apple’s mysterious self-driving electric vehicle at one of its factories in 2024. Or later. Or not at all.

As is with nearly all news coming from Apple, the report is shrouded in secrecy, unconfirmed facts, and lots of quotes from anonymous sources. But this latest news does have some key points that, if true, paint a clearer picture about Apple’s self-driving plans — and leave many more questions unanswered about the future of the company.

Manufacturing the Apple Car

Apple’s self-driving car will reportedly be manufactured at the Kia assembly plant in West Point, Georgia, in 2024. But “people familiar with the talks between Apple and Hyundai-Kia say the eventual rollout could be pushed back,” according to CNBC. And Apple is in talks with other carmakers as well, so the entire deal might fall apart, or Hyundai might become one of several companies that will be manufacturing the Apple Car.

Hyundai is definitely a good candidate for the task. The Georgia facility has the capacity to deliver up to 100,000 vehicles in the first year, according to a source who spoke to The Wall Street Journal.

Aside from capacity, Hyundai also has much experience both in electric vehicles and self-driving cars. The carmaker already has a joint venture with automotive tech company Aptiv to develop and test autonomous vehicles and a robotaxi service. Hyundai also made the high-profile acquisition of robotics company Boston Dynamics last year, which put it in control of a company that has a lot of talent and experience in computer vision and mobility.

On the other end, Hyundai would benefit from a deal that is said to be worth $ 3 billion, and it might also get access to Apple’s experience in artificial intelligence, battery technology, and lidars.

The one thing that makes the deal risky for Hyundai is Apple’s requirement to have full control of the hardware and software of the manufactured car. This has made Hyundai a bit reluctant to close the deal and become an Apple contract manufacturer. According to an unnamed Hyundai executive who spoke to Reuters in late January, “We are not a company which manufactures cars for others.”

Another executive said that such an agreement would effectively make Hyundai the Foxconn of the Apple Car. Foxconn, which you might not have heard of, is one of several companies that manufacture Apple’s iPhones. Foxconn doesn’t sell phones. It rents its supply chain and manufacturing capacity. Hyundai, on the other hand, is a carmaker. It will have a conflict of interest with a flourishing Apple Car that would undermine its own plans for becoming a leader in electric and autonomous vehicles.

In the long term, the two companies will be set on a collision course. This might lead to the deal falling apart. Alternatively, Apple might decide to change the Apple Car into a joint Apple-Hyundai venture, which would be a first for the tech company, which has a penchant for keeping a total monopoly over its entire hardware and software stack. Or, if the Apple Car business turns out to be very serious and promising, Apple might consider acquiring or merging with Hyundai or another carmaker. This would mark an even greater shift for Apple and the broader tech industry, which has been gradually encroaching on every sector.

Self-driving technology

One person who spoke with CNBC said: “The first Apple Cars will not be designed to have a driver.” This is in contrast to the strategy of most other companies, whose self-driving cars still have a steering wheel and a driver’s seat.

In a fashion, it makes sense for Apple to develop a fully autonomous vehicle, also called a level 5 self-driving car. Current self-driving car systems are level 3, which means the car can drive itself under some conditions, and the human driver must be alert and take control whenever the AI fails. The problem with level 3 is that it is an incomplete technology. Every company that is working on level 3 self-driving cars also has backup drivers sitting behind the steering wheel, ready to jump in and take control when the AI stumbles into a situation it can’t handle.

But level 3 self-driving is a mess because the boundaries between human and autonomous driving are fuzzy. Human drivers tend to get distracted when the AI is driving the car, and they don’t react quickly enough, which can lead to fatal incidents.

By going fully autonomous, Apple will be avoiding legal complications and accountability for human mistakes. But the problem is, we don’t know when and if we will reach fully autonomous driving technology that is acceptable on public roads. There are technical, legal, and social hurdles that must be overcome before we see cars without drivers sharing the road with human drivers.

Apple knows this too. “These will be autonomous, electric vehicles designed to operate without a driver and focused on the last mile,” the source told CNBC.

This means that the Apple Car is meant to be driven in specific areas where the driving conditions are much more predictable and easier to handle for AI systems. But then, it wouldn’t make sense for consumers to own an Apple Car, because they wouldn’t be able to use it to drive to work or home or go on a vacation. Instead, Apple would either have to set up its own robotaxi service in select areas or partner with another company that does so. In either case, it would mark another major shift for Apple, whose longstanding business model has been to sell its products and services directly to consumers.

How will Apple train its AI models?

The major AI technology used in self-driving cars is deep learning. Along with lidars, radars, and other sensors, deep learning models enable self-driving cars to make sense of their surroundings. The problem with deep learning, however, is that it needs a lot of data for different road, light, and weather conditions.

Waymo, Cruise, Zoox, and other self-driving car companies have logged millions of miles with vehicles sporting their gear and software. Tesla, which has integrated its self-driving technology into its vehicles, is collecting training data from hundreds of thousands of cars it has sold to consumers.

Apple, on the other hand, doesn’t have a fraction of the data other companies have collected. Its last recorded self-driving program, which dates back to 2019, only logged about 7,500 miles on California roads.

Therefore, unless we see a major breakthrough in AI and self-driving technology, Apple will have to overcome a huge data gap before it can compete with other players in the industry. And since it plans to go straight to level 5 autonomy, it’s not clear how it will overcome this gap.

One possibility will be for Apple to acquire another self-driving car startup and take ownership of its data and experience. But all major candidates have already been grabbed by other big tech or automotive companies. Another would be to become more closely involved with Hyundai’s self-driving program. But that would weaken Apple’s stance as the exclusive owner of the Apple Car.

Finally, Apple might just scrap the driverless car plan and shift toward Tesla’s strategy, developing a human-driven electric vehicle that has the infrastructure for self-driving capabilities in the future. As Apple sells more cars and gathers more data, it will be able to develop and roll out self-driving car features to its customers.

As is the case for any unreleased Apple product, there are too many ifs. Apple will continue to keep a tight lid on its plans and change them as the market develops. And we won’t know for sure what the Apple Car will look like until we see it.

Ben Dickson is a software engineer and the founder of TechTalks. He writes about technology, business, and politics. This post was originally published here.

This story originally appeared on Bdtechtalks.com. Copyright 2021

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VentureBeat’s mission is to be a digital town square for technical decision-makers to gain knowledge about transformative technology and transact.

Our site delivers essential information on data technologies and strategies to guide you as you lead your organizations. We invite you to become a member of our community, to access:

  • up-to-date information on the subjects of interest to you
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How to Deploy an Effective Mobile CX Strategy for E-Commerce

January 29, 2021   CRM News and Info

By Jack M. Germain

Jan 28, 2021 6:00 AM PT

Digital commerce transactions spiked in 2020 as consumers generated spending sprees from smartphones that produced 42 percent of all online shopping. As the pandemic continues to keep shoppers out of brick-and-mortar stores, new shopping behaviors continue to include smartphones to nudge products into consumers’ digital shopping carts.

U.S. consumers spent $ 28 billion using mobile devices last year, up 55 percent from 2019. The spending patterns through the end of 2020 show that all consumers — millennials and Gen Zers among them — are doing everything from mobile devices rather than laptops or desktops. That presents a challenge for all shop owners, physical and digital, to continue adapting to the market changes and consumer behavior, according to Dennis Reno, senior vice president and head of customer experience at Cyara.

Businesses must pivot their customer experience (CX) approaches to meet the demands of mobile-friendly and omnichannel experiences. That also creates silos when customer data is stored on various platforms. Customers get frustrated when their orders, profile, or payment information is not connected across in-person and online shopping channels, Reno noted.

To remedy this, automation technology can help retailers monitor disparate data to overcome these silos for more cohesive CX. To keep up with morphing customer demands, businesses must pivot their customer experience approaches to enable mobile-friendly and omnichannel customer experiences, he observed.

“In the COVID-19 era, it is especially critical to invest in digital CX programs that will build brand loyalty,” Reno told CRM Buyer. “For a strong CX program, business leaders should prioritize listening to their customer base and make sure teams are responsive on social media and digital channels, as well as more traditional forms of B2C communication, in order to stay connected with customers during these uncertain times.”

CRM Buyer discussed with Reno more details about how mobile CX is influencing e-commerce, and how these changes can help to improve the customer’s overall experience.

CRM Buyer: With the expanding migration of consumers from laptops and desktops to shopping mostly on mobile devices, how can businesses pivot their CX approaches to meet demands for mobile-friendly and omnichannel experiences?

Dennis Reno: To become more mobile-friendly, businesses should first make sure their website translates well on a mobile device and is just as easily viewable, navigable, and intuitive as on a computer browser. Also, ensure that customers can reach your customer service team through their preferred channel at any given time.

With omnichannel established as a standard form of B2C communication nowadays, CX programs should encompass all the various channels that consumers use, whether it is in-person, email, text, chat, or through social media platforms. This provides flexibility for the customer, who may need to be on the move while they resolve their issue.

In fact, many millennial and Gen-Z customers comment and direct message brands instead of using contact centers. So it is an ideal way to engage with customers through the platforms they prefer.

How costly is this pivoting process to mobile CX, and how much time must businesses devote to the process?

Reno: This process does not need to be costly or time-consuming thanks to easily deployable solutions, such as mobile shopping apps. Another key enabler to being able to pivot quickly is the adoption of Agile and DevOps practices.

In particular, automated testing can dramatically reduce development cycles. Being proactive by automating testing during the development of your CX systems can increase your businesses’ efficiency, decrease expenses, and improve customer retention.

How does an automated CX platform keep businesses in touch with customer data stored in separate e-commerce silos?

Reno: With omnichannel, unconnected data stays in multiple locations on various platforms.

86999 Dennis Reno How to Deploy an Effective Mobile CX Strategy for E Commerce

Dennis Reno, SVP Customer Experience,
Cyara

That is becoming a worsening sore spot among both business contacts and shoppers. Unified interaction platforms can help retailers monitor disparate data across various communication channels to overcome these silos for more cohesive CX management and data analysis.

We are also seeing many of the larger players acquire customer data platforms. For example, the recent acquisition of Segment by Twilio provides a single view of customer data. However, it is impossible to know if a communication platform is working correctly without regular automated testing.

How can businesses utilize automation to ensure CX teams are ready for the spikes in mobile e-commerce traffic?

Reno: By testing ahead of spikes, CX teams can ensure that all customer journeys are working properly. From there, CX teams can use automated processes to streamline how the customer service team responds to requests. This helps the team make sure the business is operating as efficiently as possible.

That benefits two critical CX situations. One is when holidays arrive, and buyers become more active with ordering. The second is when you are having a sale that generates a large spike in Web traffic. In both cases, your team and your communications system will be fully equipped to handle the surge in the volume of requests.

Are automated CX platforms in general customer-facing or strictly accessible only internally?

Reno: Automated CX assurance is used internally to ensure that the customer has a seamless experience. This ensures chatbots, interactive voice responses (IVR), and other avenues for customer service are functioning correctly to avoid friction.

For example, if your call center keeps dropping calls when agents try to transfer a customer to another department, that can be a huge source of dissatisfaction and could potentially lead to losing customers. CX assurance and testing prevent these types of issues from being overlooked.

How does Cyara’s automated CX assurance platform specifically improve an unassisted mobile CX experience?

Reno: Cyara’s Automated CX Assurance platform proactively monitors contact center technology from the customer’s perspective. It quickly identifies issues to reduce the risk of downtime and poor-quality customer experiences.

Cyara Pulse simulates real-world customer interactions and delivers real-time insight in the palm of your hand through the app. This enables CX teams to spot issues, troubleshoot problems. It also ensures that the business is delivering the best possible experience for customers every time.
end enn How to Deploy an Effective Mobile CX Strategy for E Commerce


Jack%20M.%20Germain How to Deploy an Effective Mobile CX Strategy for E Commerce
Jack M. Germain has been an ECT News Network reporter since 2003. His main areas of focus are enterprise IT, Linux and open-source technologies. He is an esteemed reviewer of Linux distros and other open-source software. In addition, Jack extensively covers business technology and privacy issues, as well as developments in e-commerce and consumer electronics. Email Jack.

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Teradata Appoints Nicolas Chapman Chief Strategy Officer

September 30, 2020   BI News and Info

Chapman will lead the development of the current and future strategies for the organization, focusing on growth and innovation

Teradata (NYSE: TDC), the cloud data analytics platform company, today announced the appointment of Nicolas Chapman as Teradata’s Chief Strategy Officer (CSO). In this newly created position, Chapman will be responsible for working collaboratively across the organization to develop Teradata’s strategic plan, annual operating plan, as well as the ongoing measurement and refinement needed to achieve the company’s strategic goals.

Nicolas Chapman 280x400 Teradata Appoints Nicolas Chapman Chief Strategy Officer“As we execute across the company to be cloud-first and accelerate our position as a profitable growth company, we must ensure that we have a well-defined strategic and operational plan that guides our way,” said Steve McMillan, CEO at Teradata. “Nicolas has a proven track record in accelerating organizational performance through cohesive strategy planning and execution. Teradata has made solid progress on this front over the last several years and Nicolas will help us build on our momentum.”

In his most recent role as SVP of Strategy at Imperva Inc., an enterprise cyber security software and services company, Chapman successfully led a team that worked to transform Imperva into a world-class, highly profitable growth company. Prior to that, Chapman held leadership roles at McKinsey & Company, guiding technology companies around the world in executing successful business turnarounds.

“Teradata’s market position and opportunities are tremendous,” said Nicolas Chapman, Chief Strategy Officer at Teradata. “It’s clear that Teradata has already turned a corner to become focused on providing the very best data analytics solutions for a hybrid, multi-cloud world, and I am committed to ensuring this momentum not only continues – but accelerates. By listening to the market and to our customers, we will find new opportunities to grow Teradata by providing value for our customers.”

During his time with Imperva and McKinsey, Nicolas was actively involved as an executive sponsor for various inclusion communities. Fluent in French, Chinese & Hungarian, Nicolas has a Bachelor of Arts (BA) degree in International Relations & Economics from the University of Toronto and an MBA from Columbia Business School.

Teradata Reports Inducement Award Pursuant to NYSE Rule 303A.08

In connection with Chapman’s appointment, Teradata also announced today that the Compensation and Human Resource Committee of the Board of Directors (the Committee) has granted an equity award to Chapman, effective September 22, 2020. The award was granted pursuant to the company’s previously-announced New Employee Stock Inducement Plan (NESIP) and as a material inducement to Chapman joining Teradata as Chief Strategy Officer.

The award granted to Chapman under the NESIP is a new-hire award consisting of service-based restricted share units covering 42,955 shares, which shall vest in equal amounts on the first, second and third anniversaries of the grant date. Pursuant to the NESIP, the company may grant equity incentive compensation as a material inducement for certain individuals to commence employment with Teradata within the meaning of Rule 303A.08 of the NYSE Listed Company Manual, and, as such, the NESIP is not a stockholder-approved equity compensation plan. As an award under the NESIP, the restricted share units were granted by the Committee in reliance on the employment inducement exemption under Rule 303A.08.

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Refocus Your Sales Strategy on the Phone Call

July 20, 2020   CRM News and Info

When the coronavirus pandemic first hit, telecommunications companies prepared for an uptick in internet use. While they were right to ready themselves, there’s been an even larger surge toward a more time-honored device: the classic telephone.

Indeed, the number of daily phone calls U.S. carrier Verizon handles has risen to 800 million — the same as on a typical Mother’s Day, when phone lines are at their busiest. That’s a 33 percent increase over last year, compared to the 25 percent growth in internet traffic.

While some have declared this a “comeback” for the “humble” phone call, the simple truth is that the phone never really went away. While we may use messaging apps and video calls to navigate much of our personal lives, savvy leaders know the power of the phone call in a business environment. Now, as people spend even more time talking rather than tapping on their phones, the power of voice will become even more important — particularly as a means of increasing sales.

Raise Your Voice, Win the Sale

For a robust 21st century sales strategy, you need to go omnichannel. Maintaining your social media presence and content marketing strategy online can lead to great inbound results, yet for making the pitch and closing the deal directly, you simply can’t beat a one-to-one conversation.

Getting a prospect on the line and talking to them directly matters. It’s the ability to deliver the pitch with the right content, cadence, and care for your future clients’ needs that makes a voice call so effective. It’s not just salespeople who prefer a call — 92 percent of all customer interactions happen over the phone. Simply put, that direct human connection creates the right environment to establish trust.

That’s not to say sales is easy. Your salespeople need to have the conviction to promote your product in a clear, persuasive way, knowing when to utilize your other marketing resources when needed to win over leads. Emphasizing phone calls as part of a holistic sales and marketing strategy gives your employees the tools they need to develop their voice — literally.

The emphasis on direct, clear communication goes above the bottom line. As a whole, companies lose over US$ 37 billion each year due to poor communication. Helping your employees gain a better understanding of effective telephone conversation improves not only sales, but internal communications as well — in a way that video conferencing simply can’t match.

The Problem With Zoom

Predictions about the seamless, unstoppable climb of videoconferencing have been a mixed bag in practice. In the early weeks of March 2020, videoconferencing apps experienced a 90 percent surge in demand on the app store. These numbers have declined over time, as the entire workforce takes part in the global remote experiment.

The results? Serious security and privacy concerns
aside, many people have simply become tired of video calls. Remote employees and friends looking to reconnect have all noted a type of fatigue that comes with meeting remotely, one that’s been the topic of scientific scrutiny.

The results of these studies find that the visual stimulation provided by video calling apps is at odds with our brain’s desire to actually be present with another person we can see. Simply put — eye contact through a webcam just doesn’t feel real and ends up being a distraction from the content of the conversation.

That’s not to say that video calling doesn’t have its place. There are times when live streaming helps to show off a product, or when you’ll just want to see everyone’s face on a conference call. Yet the fatigue noted by researchers can be extremely limiting for your sales strategy. The last thing you want a salesperson to feel is exhausted or disconnected from their prospect due to the alienating nature of a video call.

Old-school phone calls allow both salespeople and prospects to focus on the content of the message — not the pixelated face on their screen. It opens up an avenue for conversation without the likelihood of technical issues endemic to video applications.

Sales Calls in a Socially Distanced Age

Since the start of the global lockdowns in March, nearly every worker has seen a major shift in the way they conduct business. Salespeople are receiving an overwhelming portion of these changes, due to the very nature of their jobs.

Business lunches, in-house meetings, cross-country travel to make a sales pitch — so much of what your sales team does has historically relied on face-to-face conversation. Obviously, phone sales calls are nothing new. What has changed is their importance to your bottom line — and their surprising effectiveness in the face of all this change.

Preliminary research on the effects of COVID-19 have found that nearly half of all workers with jobs prior to the pandemic are now working remotely. That’s an incredible shift given that the previous number for remote workers was roughly 15 percent. With those kinds of numbers, companies face an obvious yet unprecedented reality: remote work may simply be the new norm.

As mentioned earlier, these changes have brought with them an emphasis on new technologies. Video calls, chatbots, and a focus on social media can all bring your company into the digital age more effectively, particularly when it comes to inbound marketing. At some point, however, your biggest customers are going to want to get to know you and your employees personally, in a way a tweet or a chatbot simply can’t satisfy.

This is where the phone call can truly shine. Instead of having your best customers email you with concerns, company leaders can now offer a dedicated phone number that’s exclusive to the clients they value most. This sort of offer is based on the Pareto Principle, which states that 80 percent of your results come from 20 percent of your customers.

VoIP technology and other tools that help your employees stay connected can significantly boost your sales results. Just having the ability to stay in touch with customers from wherever your employees are helps lead to better, more frequent engagement — and thus, higher sales.

It’s not just outbound calls that are becoming a more notable presence in the work from home space. While remote work brings numerous benefits, the distance felt between your employees can reduce creativity and idea generation. We rely on that real-time communication between employees to spur the kind of new ways of thinking essential to improving current business practices.

In the sales department, this means restrategizing, rethinking, and redeploying once new methods are in place and ready to be tested. Your best salespeople should consistently strive to help out those who may struggle a bit more or need further coaching. Since the sales themselves happen on the phone, so too should the level of instruction.

Finally, don’t be afraid to invest more funds into the technology your employees use. Consider the savings you’ll be able to free up by having a less-mobile, more phone-focused sales team. It will take some time to adapt to this new approach, just like with most business processes in our new remote era. However, the investment in infrastructure can pay dividends as your company grows.

Omnichannel With a Phone-First Approach

If you’d like to test how a phone-first sales strategy can improve your marketing, start by taking a look at your current CTAs on inbound marketing materials. Where do they lead? If you’re seeing great results by getting in touch via email or chatbot, great. If you think there’s room to improve, however, it may be time to run an A/B test.

Have some of your prospective buyers fill out an email form while the rest are prompted to call or schedule a call to get more information. Put your expectations aside and focus on looking at the data. At the end of the test, collect the results and compare them against the historical model.

You and your sales team are results oriented. You may find that leads in one region prefer to go at their own pace, while in others an early phone call leads to a stronger chance of success. Remember — just because a prospect is browsing your company profile on social media doesn’t mean they’ll never want to get in touch. A bit of prompting to make the call might be all they’re looking for.

If you don’t have a phone-first sales strategy in place already, it’s likely time to start building one. Remember that there’s a limit to how much change employees, clients, and prospects can handle without feeling ill-at-ease. Your team has likely seen changes beyond anything they expected in their lifetimes happening in the span of a few short months.

We’re working from home, staying socially distanced, and wondering what the future might hold. With so much change happening all at once — good and bad — relying on time-tested, effective, communication methods like the telephone call gives a sense of control and familiarity needed in today’s hyperconnected yet socially isolated business environment.
end enn Refocus Your Sales Strategy on the Phone Call


Eric%20Schurke Refocus Your Sales Strategy on the Phone Call
Eric Schurke is VP Operations at
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Monitoring the Power Platform: Power Automate – Run Time Part 3: Implementing a Monitoring Strategy

June 27, 2020   Microsoft Dynamics CRM

Summary

 

Microsoft Power Automate is a service allowing makers to create business processes, orchestrations and workflows to help achieve common and even complex business requirements. Within the Power Platform, Power Automate represents one of the most important pillars of the platform. It provides a no to low code solution to process automation. From sending push notifications to mobile devices, to complex robotic process automation flows, Power Automate can be used in virtually any workload.

The goal of this article is to describe how to implement a monitoring strategy for both Power Automate and the Logic App services. We will explore how to create custom identifiers to be used for tracking run time actions and flow history. We will discuss using the Azure Log Analytics Data Collector connector. The article will also show how to build a delivery mechanism to Azure Application Insights from Power Automate Flow. Finally, we wrap with considerations for using Azure Log Analytics and Azure Application Insights.

Adding Custom Identifiers

 

Power Automate Flows generate tracking identifiers for each individual flow and specific action within a flow run. For each workflow, triggers and action, these auto generated identifiers are included and available as part of the various objects documented in Part 1: Triggers, Workflows and Actions. These typically are very helpful, specifically the workflow run name, when reviewing previous run information via the UI or PowerShell.

We’ve also seen, in Part 2: Tracked Properties and Error Handling, how connectors themselves can often provide identifiers in form of header properties that can be tracked. These returned properties from the connector response are vital when troubleshooting and supporting standard and especially custom connectors.

That said, there will come a time when you may need to generate or provide an identifier yourself. Luckily, Power Automate Flow provides the ability to do both, by passing in a tracking identifier or generating one which can be used across actions or even other flows as the calling flow. This allows makers to set the expectation that the flow will return a pre determined identifier which can then be used across other workloads.

Tracked Properties

 

Before we get into identifiers, please take a moment to review the Tracked Properties section in Part 2: Tracked Properties and Error Handling to familiarize yourself with attaching data to actions.

Utilizing a system provided Correlation Id

 

Power Automate includes its own correlation identifiers as referenced in the Get-FlowRun cmdlet as part of the ClientTrackingId. This identifier can be obtained in the flow itself by use of the outputs object. Consider using this or a custom tracking identifier when working with external integrations to assist with application and workload monitoring. By implementing this early, the beginnings of an application map can appear when working with Azure Application Insights as shown below.

AUTHOR NOTE: CLICK ON EACH IMAGE TO EXPAND FOR DETAIL

4382.pastedimage1593183235379v1 Monitoring the Power Platform: Power Automate   Run Time Part 3: Implementing a Monitoring Strategy

Using the guid() function, we can generate a identifier based on various formats that can be used as the ClientTrackingId or passed to other connector actions such as Common Data Service creates or updates or even custom connectors as detailed below.

 Monitoring the Power Platform: Power Automate   Run Time Part 3: Implementing a Monitoring Strategy

Adding a custom Tracking Id

 

The Custom Tracking Id, part of the trigger, allows for the static of dynamic input of an identifier that can be passed in or set from the trigger and added to the response. This identifier can also be used across child flows to represent the calling or parent flow.

As the image below shows, we can use the “Custom Tracking Id” field to set a static or dynamic value. This example shows setting the custom tracking id from a property in the body of a HTTP request called correlatonid.

 Monitoring the Power Platform: Power Automate   Run Time Part 3: Implementing a Monitoring Strategy

An added bonus to using the trigger in this fashion is that we now can add conditions that work as a gate keeper to our flow. In this scenario we can strictly enforce that if a correlating identifier is not provided to the flow, the flow will not run and return a message expecting the identifier. This design is very important to ensure visibility and supportability, and as such needs to be included as a first step, as we include more and more integrations into our workloads.

In the example below we have a HTTP request and response Power Automate flow. In the request a Tracking Id “PowerAutomateArticleExampleId” has been provided.

In the response, captured in Fiddler or Postman, we can see the response header now includes our custom tracking Id represented by “x-ms-client-tracking-id”.

 Monitoring the Power Platform: Power Automate   Run Time Part 3: Implementing a Monitoring Strategy

This technique can be propagated down to Child Flows as well as shown below. As with the parent, the “x-ms-client-tracking-id” is now included within the Child Flow. This allows the Child Flow to use the same tracking Id for any actions or tracked property.

 Monitoring the Power Platform: Power Automate   Run Time Part 3: Implementing a Monitoring Strategy

Finally, an added benefit is that this same custom tracking identifier will be available as part of the “Get-FlowRun” cmdlet covered in Part 4: Reviewing Run History with Get-FlowRun.

 Monitoring the Power Platform: Power Automate   Run Time Part 3: Implementing a Monitoring Strategy

The Log Analytics Connector

 

One approach that can help deliver event data to Azure Monitor is to utilize the Log Analytics Data Collector connector. Utilizing the Azure Monitor HTTP Data Collector API, we can ingest data in virtually any structure using a JSON formatted string. Since every object in our Power Automate Flow is formatted in JSON we can send any item we want, from scopes to actions to the entire workflow.

 Monitoring the Power Platform: Power Automate   Run Time Part 3: Implementing a Monitoring Strategy

Creating Custom Tables

 

Below is an image showing custom tables created by using the Log Analytics Data Collector connection action.

 Monitoring the Power Platform: Power Automate   Run Time Part 3: Implementing a Monitoring Strategy

Here are the actions that created these tables starting with the PowerAutomateFlow custom table.

 Monitoring the Power Platform: Power Automate   Run Time Part 3: Implementing a Monitoring Strategy

Here is the action for PowerAutomateActions:

 Monitoring the Power Platform: Power Automate   Run Time Part 3: Implementing a Monitoring Strategy

As shown, one of the benefits of Log Analytics is the ability to add custom tables to the workspace. When these custom tables are created, they can be added to by passing in additional properties. For instance, in the image I have a table for Power Automate Actions that was created by passing an action object in. Starting with a simple initialize variable I may only have a couple of fields created in my new table. However by passing in a more robust output from an action, like the Common Data Service, I begin to grow my table exponentially.

 Monitoring the Power Platform: Power Automate   Run Time Part 3: Implementing a Monitoring Strategy

Here is an example gif showing using the workflow and action object. The workflow object is well defined however actions can become cumbersome. In this example we are splitting these into two separate tables.

NOTE: Consider using custom tables for specific actions.

1665.pastedimage1593183235382v13 Monitoring the Power Platform: Power Automate   Run Time Part 3: Implementing a Monitoring Strategy

This approach provides extreme flexibility but does come with a cost. Data can quickly become fragmented, null saturation can become unmanageable and even fields that we would often use for identifying can become obscure. We quickly can render our logs useless working this way and should provide some limits to what can be provided. Without meaningful data, what value are the logs we’re capturing?

Thoughts on Controlling the Collector

 

I like the approach shown due to the flexibility of the endpoint and the native integration it has with Azure Logic Apps. Creating custom tables and allowing data ingress in any shape or form does have benefit. Also, by using the Log Analytics Connector, all Azure Logic App and Power Automate Flow run time data (tracked properties, action results, etc) can be centralized. This allows for ease of use reporting and monitoring. That said, we need to build in enforceable and stringent rules to what our tables will accept to ensure quality as we move ahead.

The Case for Application Insights

 

Azure Application Insights, as mentioned in previous articles, is an application performance monitoring platform. Power Automate, at the time of this writing, does not have a native integration or feature to push events to Application Insights. However, as with Log Analytics, there is an HTTP endpoint that can be used to send messages to Application Insights. How that HTTP endpoint is invoked is up to the enterprise. HTTP requests can be issued directly from Power Automate Flows. Custom connectors can be created to help delivery of messaging.

The next section will go into building a direct request to Azure Application Insights. This is similar to the approach I’ve documented in the past for sending messages from Dynamics 365 Plug-ins.

Utilizing the Application Insights REST API directly

 

To achieve this we will send a POST message to the Application Insights endpoint with the definition of the specific event we want to capture. This endpoint can accept one or multiple messages so it can be used at the end of a Power Automate flow run or really anywhere. Combining the messages and sending at the end would follow a similar approach as with the Azure Log Analytics Data Collector action. As long as the action is ensured to run and we have our contracts correctly defined, we can rely on the API to deliver our messages. One of the benefits of the Application Insights endpoint is it does allow any well defined message payload and will report back the number of accepted and failed messages.

 Monitoring the Power Platform: Power Automate   Run Time Part 3: Implementing a Monitoring Strategy

The trigger I’m using here is the Power Apps trigger which allow for use of this flow as a child flow. Remember, to use this flow in this manner utilizing Child Flows, the flow must be solution aware.

Building the Message Body

 

Azure Application Insights, like Azure Log Analytics, can accept JSON serialized requests and store within tables within the log store. Unlike Log Analytics, specifically the Data Collector, is that Application Insights expects a well formed structured message. Each message contains these minimal properties: time (represents timestamp), iKey (Instrumentation Key), name (the name of the table/message) and data (the message payload). A reference to building this contact can be found here.

The data property is specific to each message type and will include a baseType and baseData property within. A good reference for finding out more can be found on the ApplicationInsights-JS Interfaces folder. For each message type, be it exceptions, custom events, traces, etc., there are common and explicit properties. Consider the below image.

 Monitoring the Power Platform: Power Automate   Run Time Part 3: Implementing a Monitoring Strategy

The image above shows how to take the contract for a specific table and inject variables which will show up in Application Insights. In this example I’m only using the customEvents table but this can easily be extended for all tables within Application Insights.

Most tables in Application Insights include a customDimensions and customMeasurements property bag which I would recommend passing contextual data from the flow. In the example above, the properties property within baseData allow for a json object to be passed in. The image above shows the trigger function but this could also be the workflow object, or maybe a particular action that failed. The below image shows using the action object output with the Exception message in Azure Application Insights.

 Monitoring the Power Platform: Power Automate   Run Time Part 3: Implementing a Monitoring Strategy

All tables include user and session data points which can be used to help facilitate out of the box capabilities in Application Insights such as the application map mentioned above.

 Monitoring the Power Platform: Power Automate   Run Time Part 3: Implementing a Monitoring Strategy

Utilizing Azure Functions and Custom Connectors

 

Azure Functions provide a great way to build micro services including ones to help surface run time data from Power Automate Flow or Model Driven Application Plug-in tracing. Azure Functions can be written using .NET Core and included is native integration with Azure Application Insights. Alternatively, we can import the Azure Application Insights SDK to provide a streamlined approach to delivering messages. The article Monitoring the Power Platform: Custom Connectors – Building an Application Insights Connector covers building both an Azure Function and Custom Connector to realize this approach.

Choosing between Log Analytics and Application Insights

 

The information above has provided mechanisms showing how to deliver events to Azure Monitor utilizing the Azure Log Analytics Data Collector or the Azure Application Insights REST API. Choosing one of the other requires considerations into the features and benefits and maybe more importantly the limitations of both. For an overview of each please review the Monitoring the Power Platform: Introduction and Index article.

6076.pastedimage1593183235383v18 Monitoring the Power Platform: Power Automate   Run Time Part 3: Implementing a Monitoring Strategy

As we progress through the Monitoring the Power Platform series, we will dive deeper into these considerations and why to choose one over the other based on requirements. Ultimately the log store for Azure Application Insights is available in Azure Log Analytics but the features provided by Azure Application Insights allow for deep “insights” into scenarios we are interested in.

Next Steps

 

In this article we have discussed using custom identifiers to help track flow history and specifically group parent and child flows together. We have examined how we can use trigger conditions to enforce the use of custom identifiers. From there we reviewed the Azure Log Analytics Data Collector connector and how to setup and send messages to custom tables. After that, we went into building and sending Azure Application Insights messages directly in Power Automate flow.

In previous articles, we discussed how to evaluate workflows, triggers and run functions to help deliver insights. In the following articles covering Microsoft Power Automate Flow run time, we will discuss pushing events to Application Insights and reviewing previous flow runs for monitoring and governance.

If you are interested in learning more about specialized guidance and training for monitoring or other areas of the Power Platform, which includes a monitoring workshop, please contact your Technical Account Manager or Microsoft representative for further details.

Your feedback is extremely valuable so please leave a comment below and I’ll be happy to help where I can! Also, if you find any inconsistencies, omissions or have suggestions, please go here to submit a new issue.

Index

 

Monitoring the Power Platform: Introduction and Index

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What Your Business Can Learn from an Open Banking Strategy

June 23, 2020   TIBCO Spotfire
TIBCO OpenBanking scaled e1592844442712 696x365 What Your Business Can Learn from an Open Banking Strategy

Reading Time: 2 minutes

Digital businesses today don’t have the luxury of sitting static on old infrastructure. In our current era of digital transformation, it’s not even enough to be a fast follower—you have to be an innovator. And there is one thing every innovative organization has in common that enables them to provide superior customer experience: Data. 

Data is the asset that allows you to keep your customers at the center of your business strategy. However, you have to know how, with a combination of the right tools, strategy, and people, to make smart use of that data. Being an early adopter of the latest technologies means you see those opportunities first, leaving no space for market disruption from competitors. 

How data is used to improve the customer experience might vary across fields, but banking and financial service firms are currently front and center of this business reinvention. By adopting an open banking strategy, these institutions are using data to personalize customer experiences and connect the overall customer journey, This also provides new openings for cross-sell and up-sell opportunities and new revenue streams through partner ecosystems. 

While banking and finance are already taking advantage of this strategy, every industry can benefit from collecting, analyzing, and sharing data. To successfully harness the power of your data, adopt an open banking type mindset. Create personalized customer journeys, introduce new digital products, and discover new channels of revenue; these aren’t limited to core banking alone. 

Data is the asset that allows you to keep your customers at the center of your business strategy. However, you have to know how, with a combination of the right tools, strategy, and people, to make smart use of that data. Click To Tweet

To take the first step, you must have the right foundation in place. This will allow you to connect the data across your enterprise, govern and secure that data, and even bring in outside data from partners through APIs. To learn more about the open banking approach and to gain some insights into how a connected ecosystem can help you take advantage of data can benefit your digital business, download this eBook and watch the solution whiteboard video today!

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How to Build an Outcomes-Focused Data Strategy

May 5, 2020   Sisense

Money never sleeps and neither does your data. In Monetizing Your Data, we look at digital transformation: the ways of turning data into new revenue streams and apps that boost income, increase stickiness, and help your company thrive in the world of Big Data. 

The first waves of digital transformation started decades ago and the ripples of this trend continue to be felt to this day. However, what exactly a digital transformation looks like varies widely from company to company. One common theme among many transformations, however, is trying to make better use of data, whether to build analytic apps to unlock new revenue streams or to make smarter decisions internally (or both).  

While these are worthwhile applications, one blind spot that many teams charged with these projects share is that they look at the data they have on-hand before figuring out what kind of problems they wish to solve with it. 

“I recommend starting your data strategy with a right-to-left approach, focusing on the desired business outcomes first, instead of the data, to support those outcomes,” says Charles Holive, Sisense Managing Director of Data Monetization and Strategy Consulting. “And there are primarily three areas that industries across the world look to improve: the top line, the bottom line, and customer satisfaction.”

sisense blog BI Trends 20191218 bl blog banner1 How to Build an Outcomes Focused Data Strategy

Define your desired outcome — before you start building

Every company knows they need to digitally transform in order to survive and excel in the modern era. However, many organizations fail to define their goals for this process before they start, and predictably encounter obstacles or outright failures instead of paving a path for future success.

Business goals should be defined at the very beginning of the digital transformation in the “right-to-left strategy” that starts by answering this question: What is the organization specifically looking to solve or improve? Understanding the details is key, otherwise “digital transformation” will be merely a corporate buzzword that causes headaches, heartbreaks, and lost money instead of producing measurable improvements.

From there, rather than trying to accumulate and house the company’s entire dataset, the digital transformation team should identify the specific actionable insights and associated data needed to solve for (and measure) agreed-upon outcomes.

“Not every dataset is made equal; some are more valuable than the others. So being outcome-focused is a way that can you stack-rank the data sets that are most important. Your team can then begin moving that most-important data into your warehouse.”

Experiment to guide a winning data strategy

Just as the waterfall method of software development—the strategy of gathering all the requirements upfront and then building and releasing a complete application—has fallen out of favor for agile methods, the same thing should happen when creating an outcome-first data strategy: Rather than trying to build a complete data warehouse right from the outset, approach data strategy as an “innovation factory.”

“Identifying the exact data you need to solve a singular problem results in a perfect candidate to go into your warehouse on the first cycle. This is because you know exactly what the business is going to do with that data set,” Charles explains. “It’s powerful because it’s already informing or measuring a specific business outcome.”

And when this data is warehoused and accessible to business partners to make key decisions, you already have a chance to quickly prove this outcome-first data strategy. You’ve immediately created an experiment to win.

Another piece of advice that Charles talks about in his “Hacking the Analytic Apps Economy” video series is where the innovation factory should live. Namely, not in a mature business unit, but in an agile, fast-reacting department that reports to a Chief Innovation Officer or similar highly-placed exec. This team can deliver on new ideas quickly and won’t get bogged down in pre-existing frameworks or goals that don’t work for what the new data experiments are trying to achieve.

Create an innovation factory at your company

“Creating an innovation factory for your company results in faster innovation. You can do these smaller experiments more cost-efficiently, saving money over the traditional data strategy. This also should help your team prioritize projects for the data warehouse that deliver the greatest value, as opposed to the department that screams the loudest.” 

And while any experiment can fail, but here are some solid tips to help improve your likelihood of success and to maximize the impact of triumphant experiments: 

  • Start by listening to the frontline employees who use the data to make decisions—this will improve the odds of success for your experiment out of the gate.
  • If your experiment works, find other departments that can benefit from that same data—this is where it is key to have a good semantic layer on top of your data warehouse (courtesy of your data analytics software) so you can repurpose the same dataset for different ends.
  • If your experiment fails, see if you can tweak the dataset or use case to apply elsewhere in the company.

Regardless, approaching data strategy with a focus on business outcomes will put you on the right course.

“Everything else in the company is business-centered. It just seems counterintuitive not to approach data strategy in the same way.”

packages CTA banners BI and Analytics1 How to Build an Outcomes Focused Data Strategy

Jack Cieslak is a 10-year veteran of the tech world. He’s written for Amazon, CB Insights, and others, on topics ranging from ecommerce and VC investments to crazy product launches and top-secret startup projects.

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COVID-19 & Building a Strategy to Go Remote: 3 Tips for CIOs

April 11, 2020   CRM News and Info

Need to Go Remote? Follow These 3 Tips 

With the current COVID-19 pandemic, businesses nationwide are faced with the same challenge: transitioning their workforce from office-based to home-based.

For some organizations, having employees who work remotely is nothing new or unusual. But for many businesses, this is unfamiliar territory. If you’re the CIO of a business that’s suddenly having to transition dozens (or hundreds, or even thousands) of employees to remote work, what should you do?

First off, take a deep breath. Remember that there are countless examples of successful, multinational companies who have had employees telecommuting for many years. In the end, you may decide that having some of your employees working from home is a good thing — and you may even keep it up once this situation passes.

That said, we know that developing and executing a strategy to go remote can be complicated. To help you start the process, here are three essential tips.

Tip 1: Make the Switch to the Cloud

 

Is your business still using an Exchange server? Are you still dependent on physical in-house file servers? If so, it’s time to transition to the cloud.

If you’re using a network share, your employees have to be physically on premises in order to access important files and software systems. The only way around this is with some kind of VPN solution — but getting hundreds of employees set up with a VPN takes a considerable amount of time and money, and can also create security concerns.

Rather than opting for a complicated workaround, the better option is to simply switch to the cloud with Microsoft Office 365. With a cloud setup, employees can access everything they need from home. There’s no need to be on premises and logged into the company network. You can also rest assured that employees will be accessing files and software in a completely secure environment, minimizing security risks.

Tip 2: Use Microsoft Azure for Legacy Client/Server Issues

 

In our experience at AKA, we’ve found that while many companies have upgraded the majority of their software to SaaS (Software-as-a-Service) and other modern solutions, it’s still common for businesses to rely on one or two legacy client/server applications. These apps are based around physical installs, often on desktop computers, which means that employees won’t be able to access them when working remotely.

Fortunately, there’s a relatively simple solution to this problem. With Microsoft Azure, it’s possible to set up a remote desktop that gives employees access to legacy client/server software from their home office. Thanks to the power and efficiency of Azure, developing this sort of solution can often be accomplished in just a few hours and for a minimal investment.

Tip 3: Enable Collaboration with Teams

 

Once you’re up and running in the cloud and have ensured that your employees can access what they need from home, there’s one other major consideration to account for: the ability to collaborate. Employees working from home will sometimes struggle with a lack of face-to-face interaction–an essential element of effective collaboration.

With Microsoft Teams, employees can keep in touch, work together on group projects, and monitor one another’s progress. With Teams running on an employee’s mobile phone and home computer, they’ll receive push notifications for upcoming meetings and ongoing chat conversations. Built-in video capability allows team members to interact more naturally during remote meetings. Sharing documents and files is easy, and Teams keeps all of your communication in one easy-to-access place.

The Time is Now: Modernize Your Organization’s Culture

 

Over the past few years, successful businesses have been transitioning to the cloud and setting their employees up to work remotely. And with tools on special trial offer like Microsoft Azure and Teams, it’s never been easier.

While the current situation brings with it certain challenges, it also presents businesses with an opportunity to modernize and update their company culture. AKA can help your business get started with Dynamics 365 CRM, Microsoft Azure, Microsoft Teams, and other essential solutions for working remotely via the cloud.

Want to learn more about transitioning your workforce to remote work? Read The Sudden Need to Work Remotely: How This Company Transitioned 500 Users in Just One Weekend with a Cost-Effective Solution on Microsoft Azure. Ready to take the next step? Contact the experts at AKA to discuss your needs.


ABOUT AKA ENTERPRISE SOLUTIONS
AKA specializes in making it easier to do business, simplifying processes and reducing risks. With agility, expertise, and original industry solutions, we embrace projects other technology firms avoid—regardless of their complexity. As a true strategic partner, we help organizations slay the dragons that are keeping them from innovating their way to greatness. Call us at 212-502-3900!


Article by: Greg Inks | 212-502-3900

With two decades specializing in Microsoft and Azure platforms, Greg leads AKA’s Cloud practice. He is a Cloud evangelist offering deep expertise in Cloud architectures and adoption strategy. Greg has developed subject-matter expertise and wide-ranging business acumen by working with some of the largest, most successful technology providers and client companies on the planet.

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