Artificial intelligence (AI) and machine learning (ML) are revolutionizing the insurance industry by improving risk assessments, reducing payouts on fraudulent claims and boosting customer experience. Companies who implement such technologies can expect to see customer satisfaction increase and operational costs drop.
In this whitepaper we'll detail the specifics of telematics, chatbots and machine learning. Learn how each of them are currently being used to save companies both time and money by reducing hours spent dealing with tedious paperwork and lowering loss ratios through calculating more accurate predictive models.
In January 2021, Silicon Valley (where I live) emerged from a 2-month “shelter-in-place” order. Although I have found working from home to be fairly tolerable, the primary thing missing for me is the serendipity of unexpected interactions: hallway conversations with colleagues, grabbing coffee with a client, and all the experiences you have while traveling for work.
I think the main problem with online-only interactions is that they are too structured. Even relatively unstructured online interactions have constraints put on them by the limitations of the device, the technology, and the user interface. For example, in most video conferencing systems, there can be a time lag between speakers and reduced visual cues. When more than two or three people are involved, this tends to make interactions more “lecture style” with sequential speakers, rather than a free-flowing conversation.
I'll provide another scenario from my own work experience. Last spring, GlobalLogic started doing online advisories during the pandemic to help clients design and architect new or next-gen systems. In the past, I always relied on onsite visits and face-to-face interactions, so I was initially skeptical about how well an entirely online approach to brainstorming and information gathering would work. Happily, I found that online interviews can be more effective when interviewing busy subject matter experts (SMEs) such as surgeons, investors, and CXOs. Where in the past I would have to chase these busy people around the globe, now I could schedule interviews at their convenience.
But everything has a cost. The cost of information gathering and brainstorming online is that by necessity, the interactions have become more structured. People have to speak more-or-less one at a time, and while you can structure interactive discussions and side conversations, you need to plan them. You don’t have spontaneous interactions over lunch, you don’t pick up behavioral cues from people in their work environment, and you can’t read people’s body language in the same way. You can have sidebar conversations through the chat system of a video conference, but even that is more formal that a whispered question or remark.
What’s wrong with more formality? It increases the odds of missing something that you didn’t know to ask about, because the “serendipity” factor goes down compared to face-to-face. A key maxim we take into any advisory is: “You don’t know what you don’t know.” In other words, everyone remains ignorant of the areas they don’t know enough to ask about. You obviously try to shrink those areas into insignificance by doing your homework ahead of time, but when you are designing and architecting a new system that’s central to a company’s business, you have to be humble enough to realize that you won’t know everything. Even for the long-term players within a business, there is generally no one individual who knows everything about all aspects of a company’s business and technologies. The knowledge is always in many heads, and it's my team's job to extract what’s meaningful from a wide variety of SMEs.
We’ve had success bridging this gap by asking open-ended questions like, “Please lead us through this process from end-to-end,” and “Please tell us anything you think we need to know that we didn’t ask about.” We also use “mirroring” to reflect back our current understanding for clarification because, although people may not fully answer a question when you ask it, they are almost always willing to correct you. Nevertheless, there’s still a risk that an SME will assume you know something because they take it for granted. It’s the “fish in water” effect. We've now learned to be super-aware of such potential gaps since the “serendipity” we gain through physical interaction is not present online.
In time, I think technology and people’s comfort with technology will bring more serendipity to the online experience than it currently does. Even today, in an advisory setting, we could theoretically mimic an onsite visit using technology. We could “look over people’s shoulders” as they worked by using screen sharing. We could even visit the office or worksite using telepresence robots, helmet- or glasses-mounted cameras, and “see what I see” AR technology. In some areas like training, we are using all of these technologies today. However, for the demographic of most current-generation SMEs, this technology is still seen as unusual and intrusive enough that it would not be accepted, or would change people's behavior.
I don’t think online interactions necessarily have to be more limited than physical ones. I really believe that the distinction between online and physical will continue to blur until the two merge into an augmented, enhanced reality blend. But we are far from that today.
Broadcasters and streaming service providers are experiencing a surprising new trend: Gen Zers aren’t sports fans.
Well, that’s not entirely true. Even though most young people are still interested in sports, the vast majority of them place it behind other entertainment activities. According to a national tracking poll by Morning Consult, “only 53% of Gen Zers identify as sports fans, compared to 63% of all adults and 69% of Millennials.” More than half of Americans are Millennials or younger, so pay attention broadcasters — Gen Z will be your buyers for the next 10-15 years.
According to Tim Ellis, the NFL’s chief marketing officer, “There’s no strategy for bringing in a 35-year-old fan for the first time. You have to make them a fan by the time they’re 18, or you’ll lose them forever.” Even though modern TV services continue to change significantly, most sports-related offerings — as well as teams and leagues — are very slow to adjust to this new generation of fans.
Scientists and researchers can spend years studying the roots of this development, but one factor seems especially significant: technology. The boom of social media, a constantly growing dependency on smartphones and mobile apps, the evolving role of immersive entertainment, etc. — all of this shapes the way modern youth consume, interact, and communicate. But the good news is that if technology has changed the way Gen Z interacts with the world, then technology can turn them into more avid sports fans.
eSports
I think the first step should be to consider broadcasting alternative content like eSports. Sometimes I feel that Fortnite, Dota, Counter-Strike, or League of Legends will outpass regular football games. eSports attract millions of unique viewers worldwide, but you cannot find these tournaments on regular sports channels. These games are evolving at a surprising rate through Twitch, YouTube, and their own platforms. Yet even though most streaming happens in this sector — and COVID-19 is only strengthening this trend — media giants have been quite slow to react. A lot of teams, leagues, and broadcasters try to keep pace with technology trends, but this only results in adding new tech and outreach channels to existing fandoms. The problem is that fandoms change, and great OTT/DTC capabilities are no longer enough of a market differentiator for Gen Z audiences.
Short-Form Videos to Support Micro Betting
As of 2018, any state that wishes to legalize sports betting may now do so. Currently only 20 states have legalized sports betting, but I believe most states will have some form of legal sports betting by 2023. This opens up huge opportunities for broadcasters, as betting can make sports more engaging and interactive for Gen Z viewers. For example, they can offer viewers more short-form game videos to support micro betting (i.e., betting on whether a team will score within a specific timeframe or play). Micro betting could even become part of a physical arena’s tech infrastructure, not just the off-arena experience.
360 Access to Players
Younger generations like to follow the careers and personal lives of their favorite celebrities. Athletes like Virat Kohli, Lionel Messi, Cristiano Ronaldo, Neymar, and Lebron James are already celebrities, so why not translate their celebrity status into a new type of fandom? Broadcasters can use technology like computer vision and machine learning to gather and share data about an athlete’s physical condition, performance, events, and so many other parameters. Not only are you giving fans a whole new level of access to athletes, but you get a new set of audience data points.
Personalized Viewing Experiences
As my colleague pointed out in a previous blog, COVID-19 has forced broadcasters to leverage more automatic, high-quality solutions to minimize human involvement in the production phase. However, these solutions have also brought a certain level of personalization for fans. For example, by placing a number of wide angle 4K cameras mounted around the arena, you can provide viewers with the ability to jump between cameras and different angles, follow game or athlete from their own point of view, see what is happening behind the scenes, etc. Now add the above-mentioned 360 degree access to data about a team’s athletes, and a viewer is literally the owner of the moment.
Reliable Broadcast Technology
At the end of the day, no matter which way you choose to chase your Gen Z fans, the content viewing experience is still the most important factor to keeping your viewers happy. Waiting for content to load, difficulties in navigating or searching for content, not being able to use your preferred platform or even payment method — this will decimate your audience before they can even become real fans. Make sure your viewers can reliably watch the content they want to watch, when they want to watch it, and through their preferred platform. If you can’t guarantee a seamless viewer experience, then find a technology partner who can.
Dark data remains hidden in the form of unstructured emails, social media posts, and digital and scanned documents including invoices, purchase orders, contracts, written agreements and policies, survey results, and application forms.
How can your organization derive value and reap benefits from the dark data using advanced analytics and techniques like AI, Deep Learning, and NLP? In this post, we explore the benefits and challenges of activating dark data and share examples of how dark data is delivering meaningful value.
What is Dark Data?
Gartner defines dark data as, “The information assets organizations collect, process, and store during regular business activities, but generally fail to use for other purposes (for example, analytics, business relationships and direct monetizing).Similar to dark matter in physics, dark data often comprises a universe of information assets. Thus, organizations often retain dark data for compliance purposes only. Storing and securing data typically incurs more expense (and sometimes greater risk) than value.”
According to industry reports, a large portion of unstructured data is never analyzed. There are two key reasons why:
There is simply too much dark data to analyze
The sheer amount of data generated these days makes activating its insights difficult. The variety of data being collected can also be overwhelming, as it ranges from social media data and IoT/sensors to data buried in documents, call records, and transcripts from audio and video files.
We lack specialist tools for analyzing dark data.
The technology required for effectively deriving value from such data for practical production scenarios is limited.
AI Advancements Are Driving New Possibilities for Dark Data Analysis
Over the last 50 years, we have seen Moore’s Law—that the number of transistors on a microchip doubles every two years, though the cost of computers is halved—realized as computer storage and processing capabilities have become smaller, cheaper, and faster.
We have also witnessed many other technological advancements such as:
The emergence of more distributed computing and storage solutions.
Innovations in processing technologies including graphics processing units (GPUs) and tensor processing units(TPUs).
A resurgence of artificial intelligence (AI) including machine learning, natural language processing (NLP), and deep learning.
These have all significantly contributed towards making the collection, storage, and analysis of all kinds of data possible.
AI and related technologies have been applied to the classification of written texts like spam in emails, the sentiment analysis of social media posts, the recommendations of most relevant news/media by search engines, and help assessing risks/threats to national security in social media posts.
Now, they are also being used as an effective way of identifying relevant information from both digital and handwritten documents for the purposes of:
Automated extraction and storage of information in the form of key-value pairs.
Three-way matching data from invoices, purchase orders, and receipts.
Taking information from claim forms and application forms and passing it on to downstream systems.
Processing more textual documents such as Statements of Work (SOWs), Master Service Agreements (MSAs), Tower Lease Agreements, International Bid Documents, SLAs, and policies enables organizations to extract various clauses and entities, automate downstream processing, and better assess risks.
Activating Dark Data is Not Without Its Challenges
Many organizations are still not utilizing dark data despite a general understanding and acceptance of the value gained from extracting information from it. Here’s why:
First, it is not at all easy to understand the semi-structured format of documents and artefacts such as purchase orders, invoices, forms, handwritten texts. Extracting data, meaning, and risks from long textual documents such as contracts, agreements, policies, etc. is inherently challenging. There are complications and complexities such as isolating specific documents from a cluster of documents, classifying them, and understanding sections, headers, tables, images, abbreviations, watermarks, stamps, bullet points, and much more.
It is important to give special consideration to the “tables” in the documents, as they are complex for machines to identify and comprehend.
Second, there are also issues associated with validating the extracted data for further processing. This must be automated to the possible extent and must be done before final approval. If all fields require manual validation before the final processing, the amount of savings and value that can be brought to the table is questionable.
Practical Solutions for Illuminating Dark Data
Similarly to how the human mind approaches document analysis (extraction, key-value pair identification, clause identification, risk analysis), solutions require an end-to-end amalgamation of technologies such as rule engine, traditional NLP, machine learning, deep learning, and cognitive search incorporating multiple pathways.
After extracting the required data and information, it must be filtered for manual validation only for low confidence extractions. The automation flow is further enhanced by allowing configurability of straight-through processing for extractions where confidence is higher.
Here are a few options for stitching the automation process:
Manually validate only those fields which are low in confidence for accuracy
Take a call at the document level and enable straight-through processing for all documents where overall confidence is high.
This requires deeper analysis of the fields to be extracted and classification into categories of accuracy sensitivity on impact of high and low.
For lower sensitivity fields, thresholds can be set lower; for high sensitivity, thresholds can be higher.
Allowing settings to be completely configurable is key.
The real challenge (and excitement) is to make option #2 possible with an increasingly higher percentage of documents going via straight-through processing.
The whole concept of post-deployment model performance tracking, feedback mechanism, auto-learning new data, and improved model deployment after manual approval makes this a long-lasting, sustainable, and successful AI implementation for extracting value from the dark data.
Conclusion
“I am convinced that machines can and will think in our lifetime.” — Oliver Selfridge (The Thinking Machines — 1961).
Hidden dark data translates to hidden risks, value, profits, efficiencies, savings and worse for enterprises and organizations. There is an immense potential to uncover insights from this data and deliver meaningful business value to the enterprise.
A few examples of areas where this has been applied successfully include:
Procure to Pay: for information extraction and enhanced automation in three-way matching.
Contract Management and Administration: for review assistance, improved compliance, and risk management.
Claims Processing: for enhanced automation and improved effectiveness and efficiency.
Customer Onboarding: for enhanced automation and improved effectiveness and efficiency.
Policy Administration: for information extraction and improved customer service.
Knowledge Management: for improved and meaningful knowledge discovery.
Thanks to technological advancements, the time is upon us to start out on the journey towards improved automation. This will allow for valuable insights to be gained from this otherwise hidden treasure trove that is dark data.
Apple Pay is a mobile payment and digital wallet service by Apple Inc., which provides an easy and secure way to make payments in stores via iOS apps, watchOS apps, and Safari. Customers love the simplicity of Apple Pay, and you’ll love the increased conversion rates that come with it.
In this white paper, we’ll provide businesses with an end-to-end guide to setting up and using Apple Pay. Learn about the Apple Pay system architecture, how to integrate it with mobile apps and web sites, which devices and countries are supported, and even applicable charges and limitations.
Telemedicine and telehealth have been around for decades, but patients continued to visit doctors’ offices instead of just having a video conferencing. And although some patients preferred virtual visits, providers were afraid that it wasn’t reliable and were reluctant to adopt this approach. Also, the technology was simply not widespread enough to attract many people.
COVID-19 has changed the outlook of telehealth. The pandemic has accelerated the digitalization of patient engagement and has led to a massive increase in virtual healthcare delivery (e.g., telemedicine, remote patient monitoring, mHealth applications).
Between January 1 and August 31, 2020, Gartner saw more than a 300% increase in virtual care inquiry volume when compared to the same period in 2019. According to McKinsey, with over 70% of in-person visits cancelled during the pandemic, 76% of patients responded they are very likely to use telehealth going forward.
Let’s look at the patient experience “pre-COVID-19” and “post-COVID-19.” Across all the steps of a digital patient engagement lifecycle, we see how the standard processes are “virtualizing” via telehealth using mHealth applications, chatbots, online portals, and so on.
As you have heard countless times, the coronavirus pandemic has created a “new normal.” Healthcare providers, academic institutions, and IT service providers are extending their existing solutions and creating new ones to enable new capabilities and reduce the demand on health delivery organizations.
Benefits for Patients
With telehealth in place, patients will be able to receive high-quality healthcare much faster, as they won’t need to wait days before they get to their physician and then spend a lot of time in overcrowded clinics. Telehealth will especially benefit rural residents, elderly patients, and people with disabilities who have difficulties getting to the hospital; now they will be able to reach their physicians online and get quality support.
Critical health patients will get a lot of benefits, too. Telehealth can help physicians assess whether a patient requires immediate attention, preventing unnecessary visits and improving care for those with more urgent needs. At the same time, healthcare workers can use remote patient monitoring to allow stabilized patients to leave the hospital faster without compromising treatment.
Benefits for Healthcare Providers and Payers
Ineffective healthcare methods cost the healthcare system billions of dollars annually, which increases treatment costs for patients. Telehealth can reduce unnecessary costs and recover lost profits by making certain processes more convenient and efficient. According to America’s Health Insurance Plans (AHIP), “telehealth could help save the United States as much as $4.28 billion on health care spending per year.” Reaching a wider audience and providing new offerings can also create new revenue streams.
Telehealth can reduce hospital readmissions and unnecessary emergency department visits. It can also facilitate ongoing care for discharged patients, deliver preventative care, and improve patient no-show rates. For example, healthcare providers can use live videoconferencing to monitor patients after discharge within the required timeframe, especially within the critical 30-day post-discharge period.
Security and Privacy Concerns
As healthcare providers scramble to meet the accelerated demand for telemedicine solutions during COVID-19, privacy and security requirements have unfortunately become more relaxed. Healthcare organizations have been in survival mode, turning to free online communication platforms that are not HIPAA-compliant. This can lead to unsecure patient visits, wrong patient visits, etc. Therefore, healthcare organizations should assess the risks and how to handle them. Doctors working from home should also be aware of who can hear them during telehealth visits or see their screens.
When it comes to security issues, healthcare IT and security teams are the ones who are responsible for the safety of patients and healthcare teams. To address privacy concerns, healthcare providers are looking into access control tools such as multi-factor authentication solutions, as this approach can help better protect people who access data through patient portals. In addition, security teams must take additional steps to properly educate their healthcare providers on cybersecurity and potential threats associated with telehealth. The healthcare team can then share this security information with patients so that they feel more comfortable with the new process and have confidence in the security of their data.
Conclusion
Telehealth has shown great potential and proven its ability to provide timely and safe care during the COVID-19 pandemic. It has also demonstrated various benefits, like healthcare costs reduction and increased convenience and access to care for vulnerable patients. It also enables continuity of care support for patients with chronic conditions at a distance. And after the pandemic is ended, telehealth will still play a vital role in moving towards value-based care.
✓ What’s the difference between Server and Data Center?
✓ The benefits of upgrading to Data Center
✓ Deliver fast, reliable, and scalable products
✓ Stay secure and compliant
✓ Take advantage of infrastructure flexibility
Atlassian understands the need for secure and compliant software. To address that need, they are continually investing in these areas in their Atlassian-managed cloud products. But for those of you who have strict requirements or who are looking for a slower transition to cloud, Data Center is a great option.
But if you’re not ready for Atlassian’s cloud products, keep reading to learn more about the value in our Data Center products and the benefits of upgrading from Server to Data Center.
What’s the difference between Server and Data Center?
Simply put, Data Center is designed for businesses. High performance and availability, scalability, seamless user management and flexible deployment options are just some of the ways Data Center meets the needs of organisations working at scale.
You may be wondering what all of these added Data Center features really mean for your organization. They’re summed it up in three main groups of benefits.
1. Deliver fast, reliable, and scalable products
As an enterprise, you’re probably dealing with large, complex, growing, and/or geographically distributed teams. And if those teams need Atlassian products to get their work done, any performance or availability issues can mean a huge loss in productivity. If you’re unsure whether you need greater speed, reliability, or scalability in your Atlassian products, consider the following questions:
Are your users experiencing delays?
One major culprit of performance issues is concurrent usage. Under high load or at peak times, your product performance is at risk of degrading, which can be frustrating for the teams who are trying to get work done. With the ability to deploy Data Center in a clustered environment, you can better support your company’s scale across multiple nodes, giving your teams a faster, more seamless experience.
Additionally, Atlassian offers features within their Data Center products themselves to help improve performance. In Jira Software and Jira Service Management, you can archive both projects and issues to clear up space, clean up your instance, and make your products more performant.
Speed may also be an issue for employees who are physically distant from your servers. To help you better serve geographically distributed teams, Atlassian offers support for content delivery networks (CDNs) in Jira Software, Jira Service Management, and Confluence, as well as smart mirroring & mirror farms in Bitbucket.
Have you suffered from any downtime?
While speed and performance are critical, you may see an even bigger difficulty in productivity if you experience any downtime. Ensuring the reliability and availability of your Atlassian products is crucial. With active clustering, the load balancer will automatically redirect traffic from a failed node to an active node in the cluster, meaning uninterrupted access for your users. Additionally, product-specific features like zero downtime upgrades in Jira Software and Jira Service Management and read-only mode in Confluence ensure consistent access to the products, even when you’re going through planned upgrades.
Are you adding (or expecting to add) new users and teams to your Atlassian products?
Lastly, if you’re growing and adding more users to your Atlassian products, scaling Data Center is quick and easy. You can add nodes to your cluster without any downtime in order to easily scale your products and get them in the hands of the people and teams that need them.
2. Stay secure and compliant
Nowadays, security is important for all businesses, but if you’re in an industry that’s subject to specific regulations, security and compliance are must more important.
One big piece of your security puzzle is making sure that the right people have access to your Atlassian products. Support for SAML and OpenID Connect help meet your authentication standards.
In addition to solid security, demonstrating compliance is critical for businesses in regulated industries. Data Center products make it as easy as possible to comply the ever-evolving regulatory landscape. Advanced auditing in Data Center provides a security-relevant digital record that improves visibility.
3.Take advantage of infrastructure flexibility
In addition to increased control, enterprises have a need for more flexibility in their software. Not every enterprise is the same. With that in mind, Atlassian offers infrastructure flexibility and leaves it up to you to decide how to host your Data Center products.
While you can deploy Data Center on your own hardware, you can also take advantage of the benefits of cloud computing and turn to IaaS vendors like AWS or Azure to deploy your Atlassian products. In doing so, you can save time and money and make it even easier to scale Data Center as needed.
Every few years, Scrum originators Ken Schwaber and Jeff Sutherland publish an updated version of their Scrum Guide, which completely defines the framework, including its roles, events, artifacts, and rules. It’s been a while since the last updates in Scrum Guide happened. And here it is!
The new version from November 2020 brings some really interesting changes. Personally, I welcome such amendments, which bring more flexibility into the process. But, let's have a step-by-step overview according to scrum.org.
1 . Even Less Prescriptive
Over the years, the Scrum Guide started getting a bit more prescriptive. The 2020 version aimed to bring Scrum back to being a minimally sufficient framework by removing or softening prescriptive language (e.g., removed Daily Scrum questions, soften language around PBI attributes, soften language around retro items in Sprint Backlog, shortened Sprint cancellation section, and more).
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What does it mean?
It is a current reality that there are as many Scrum implementations as products that use Scrum as a main SDLC approach. The above changes bring more flexibility to the framework. Why? Let’s take a look at it closely:
(a) We are not obliged to use Daily Scrum questions as a must-have. It is important that people hear each other, share opinions, and seek help if needed. There are many ways to build up a conversation in the team, and we should not limit ourselves with the questions/statements, “What I did,” “What I will do,” and “What are impediments?”.
(b) If we are talking about Product Backlog Items (PBI), then it is always a good idea to have a sufficient level of details, size, value, etc. However, it is important that such items should correspond to business needs and domains. As a result, PBIs may contain the mentioned attributes, but they are not limited to them. Softening the PBI attributes is an extension to flexibility and avoiding the call to order.
(c) Retro items are now more abstract. Authors give us just a heads-up of what key aspects should be worked through during the retrospective meeting. Dozens of available tools allow us to pick the approach to retrospective that works best for our team. Overall, it leads to decreasing the prescription on who should do what and focusing more on the results.
(d) ScrShortening other parts in the guide gives more clarity and does not overload the process description with obvious consequences if some action like “Sprint Cancellation” takes place.
2. One Team, Focused On One Project
The goal was to eliminate the concept of a separate team within a team that has led to “proxy” or "us and them” behavior between the PO and Dev Team. There is now just one Scrum Team focused on the same objective, with three different sets of accountabilities: PO, SM, and Developers.
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What does it mean?
The previous version recognized no sub-teams in the Development Team, and finally this approach has been moved to the level of the entire Scrum Team. The very first elimination of “us and them” behavior happened in 2011 by removing the reference to chickens and pigs concept. And now it is a logical continuation of eliminating the separation of PO and Dev Teams. The size of a team is now in reference to the whole Scrum Team and not to Developers only. In addition, the 2020 version of the guide recommends but is not limited to having up to 10 people in a Scrum Team, with a good explanation of why small teams work better.
Such changes should bring more product and process ownership to the Scrum Team. The closer a Scrum Team works together, the better its cooperation to deliver really valuable products.
3. Introduction of Product Goal
The 2020 Scrum Guide introduces the concept of a Product Goal to provide focus for the Scrum Team toward a larger valuable objective. Each Sprint should bring the product closer to the overall Product Goal.
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What does it mean?
Perhaps the most important change is the introduction of the Product Goal into the overall concept of the framework. Nowadays, Scrum is being adopted by many domains beyond software product development (where it has its roots). A product can also be a service, a physical product, or something more abstract. Depending on the expected results, in many approaches, this could be considered as an intermediate result for those products that slice their value by milestones or releases.
The Product Goal describes a future state of the product, and it is very important to stick to the defined goal in order to constantly check if the Scrum Team produces valuable products. Without sprint-to-sprint aligning to Product Goal, the Scrum Team could turn to the wrong path and doom the product.
4. A Home for Sprint Goal, Definition of Done, and Product Goal
The previous Scrum Guides described the Sprint Goal and Definition of Done without really giving them an identity. They were not quite artifacts but were somewhat attached to artifacts. With the addition of the Product Goal, the 2020 version provides more clarity around this. Each of the three artifacts now contain "commitments’"to them. For the Product Backlog, it is the Product Goal; the Sprint Backlog has the Sprint Goal; and the Increment has the Definition of Done (now without the quotes). They exist to bring transparency and focus toward the progress of each artifact.
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What does it mean?
Commitment is the willingness to work hard and give the energy and time to a job or an activity. The creation of an artifact must be dictated by the desire to achieve specific goals. And thanks to "commitments," we can draw a single line from the Product Backlog Item to the desired state of our product. PBI becomes an increment once it meets the commitment "Definition of Done." The set of increments aligned to the commitment "Sprint Goal" moves the product closer to the desired state, which is outlined in the "Product Goal" commitment.
5. Self-Managing Over Self-Organizing
Previous Scrum Guides referred to Development Teams as self-organizing, choosing who and how to do work. With more of a focus on the Scrum Team, the 2020 version emphasizes a self-managing Scrum Team, choosing who, how, and what to work on.
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What does it mean?
Involving the Product Owner and Developers into a single Scrum Team leverages the opportunity to flatten the SDLC by better incorporating what needs to be considered during upcoming development.
6. Three Sprint Planning Topics
In addition to the Sprint Planning topics of “What” and “How,” the 2020 Scrum Guide places emphasis on a third topic, “Why,” referring to the Sprint Goal.
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What does it mean?
The idea is quite simple. During the Sprint Planning, the Product Owner proposes how the product could increase its value in the current Sprint. The whole Scrum Team then collaborates to define a Sprint Goal that communicates why the Sprint is valuable to stakeholders.
The order of Sprint Planning: Why -> What -> How
In fact, this is another opportunity to ensure that the current Sprint Goal is aimed to increase the value. Also, this type of planning connects the dots between the Sprint Goal and Product Goal.
Conclusion
The 2020 Scrum Guide provides overall simplification of the language for a wider audience. It has placed an emphasis on eliminating redundant and complex statements, as well as removing any remaining inference to IT work (e.g., testing, system, design, requirement, etc). The Scrum Guide is now less than 13 pages.
The newer version has less prescriptive language because, based on current realities and wide Scrum usage, the main elements of Scrum should be context-sensitive and dependent on particular products or conditions rather than work as a comprehensive solution that could not fit other products.
The COVID-19 pandemic has continued to impact social, economic, and health parameters across the globe — which seems to be far from over. There is a significant amount of uncertainty across industries and businesses — irrespective of scale — about what the fallout will be like.
The retail industry has seen its fair share of turbulent times in the past, but this pandemic has tested this industry to its limit. Due to quarantine measures, retail customers have been opting for minimal human contact and moving towards online consumption patterns. Now, as some countries start to re-open shops, restaurants, and other public places, retailers are highly aware of the importance of health safety for both their customers and associates in this new post-COVID world.
Innovation and digital disruption are the only way to survive, but adoption needs to happen at an even faster pace than before. At GlobalLogic, we have observed multiple trends that boomed during the pandemic and are likely to become the new normal.
Post-COVID Retail Innovation Trends
E-Commerce
Since the pandemic started, online sales in the U.S. jumped 49% in comparison to last year. Customer shifted from store visits to ordering from home. This trend will likely continue post-COVID, as most customers realized its convenience while also minimizing their health concerns. According to a World Economic Forum article, department stores are expected to decline by over 60%, and e-commerce is expected to grow by nearly 20% in 2020. Retail giants like Walmart, Target, CVS, and Kohl’s have embraced their omnichannel fulfillment methods to successfully address this shift; other organizations are beefing up their e-commerce strategy as an immediate measure.
In-Store Digitization
As countries are opening up, so are the stores and malls. However, the important thing to notice is how many customers will come back and how much time they are willing to spend in the stores. Hence, it is imperative for stores to make themselves digital-friendly, such as offering product information sharing, real-time inventory information, and customer loyalty management using fewer associates in coherence with their customers' omnichannel activities.
Touchless Experience
The stigma of this pandemic has made customers realize they would prefer touchless interaction in a store to complete their buying process. In fact, curbside orders increased 208% during the pandemic. We will see a lot more adoption of BOPIS (buy online, pick up in store) with curbside pickup, touchless payments, book appointments for pickup, etc. for years to come.
Inventory Management/Fulfilment
This is a major concern faced by almost every retailer; there was either a crunch of essential supplies or a stockpile of non-essential goods. To address this inventory automation and fulfillment, digitization became critical. Retailers started adopting inventory digitization to have minimal human intervention, and closed stores were converted into dark fulfillment stores for delivery and inventory stock-up. These measures enabled retailers to get back to a normal supply chain.
AR/VR Adoption
A Coresight Research report estimated that the AR/VR market is forecasted to reach $18.8 billion in 2020, citing pre-COVID-19 projections from Statista. Customers can now experience products virtually through various AR/VR options like virtual try-on, virtual malls, product visualization, access to product information, etc. This technology provides customers with viable options to engage with a product before buying it. We expect to see a lot more focus and investment in this segment.
Key Acceleration Themes for Retailers
GlobalLogic partners with multiple leaders in the retail space to design and develop innovative new products and platforms. In fact, we have created blocks of well-architected accelerators backed by a repository of scale, encapsulating 5000 person-years of industry and technology expertise in Retail/CPG. Based on this deep industry knowledge, we are predicting that the below themes will be pivotal for retailers to accelerate their business post-COVID.
BOPIS with Curbside Pickup
BOPIS with curbside pickup is the most asked-for feature by customers. BOPIS allows customers to order products online and pick them up from the store, while curbside pickup provides a more convenient way for users who do not want to physically go inside the store to retrieve their purchases. Curbside can also be completely contactless by having an associate place a customer's purchases directly into the trunk of their vehicle.
Contactless Payments in the Store
These days, customers prefer contactless payments in the store to minimize the risk of virus spread. Customers can use their mobile phone to make payments in-store using NFC or by scanning a QR code. This method makes payments safer, faster, seamless, and efficient, resulting in an enhanced customer experience.
In-Store Digitization
Retailers must empower store associates by providing them with digital tools to enhance their efficiency. With the right tools, associates can spend more time serving customers effectively. They can easily answer customers' questions about stock inventory, find products at nearby stores, or check the price of a product.
Voice Commerce Capabilities
Customers now want the ability to search for and buy products online through voice commands. Using Google Assistant or Amazon Alexa, customers can add products to their shopping lists, make purchases, and check the status of their orders. It is so natural, like talking to your personal assistant.
In Conclusion
There is no going back to pre-COVID days for multiple industries due to the unforeseen impact of this pandemic. However, as with any downturn, there is a more prominent upturn — including for retail. New trends and innovations have come into play and will keep evolving as we move towards a brighter post-pandemic era.
✓ Set context for custom fields as you create them
✓ Personal access tokens
✓ Embedded Crowd and password encryption
Meet Jira Service Management
We are excited to introduce Jira Service Management, the next generation of Jira Service Desk. Jira Service Management is an ITSM solution built on Jira that helps IT operations and development teams collaborate quickly.
New events in the audit log
Atlassian has added new events to the audit log:
SLA conditions created
Updated SLA terms and conditions
Organisation linked to project
Organisation disconnected from project
JSM notification rule template updated
Email channel updated (password changes)
The following features are included in the Jira Platform, meaning they are available across the Jira family – Jira Core, Jira Software and Jira Service Management.
Email templates made better
You can now download email templates for your notifications directly from Jira. This should give you easy access to all the files you need. Once you have changed the templates, you can upload them again and Atlassian will take care of moving them to the right places.
After upgrading to Jira Service Desk 4.14, Atlassian copies the default Jira Mail templates to your shared Jira Home directory. Thanks to this, any changes you make will be preserved in future upgrades without requiring any extra steps from you.
Set context for custom fields as you create them
Custom fields can have two configurations – global and project-specific. Global context has been the default choice, but such custom fields are applied to all outputs in your instance and can affect performance. Atlassian has made a few simple improvements to help you choose the right context.
Now you can select the context of the custom fields as soon as you create them. This should help you limit the number of global custom fields and keep your Jira instance in the best shape possible.
Personal access tokens
The Jira REST API offers numerous options for automation and integration with other systems. For added security, you can now create personal access tokens, which are a secure alternative to using a username and password for authentication.
Go to your profile in Jira and select Personal Access Tokens to create a token. By default, you can create up to 10 tokens and set different expiry dates for each. In the Jira Data Center, Jira system administrators can additionally view all tokens and revoke them at any time.
Embedded Crowd and password encryption
Atlassian improves security with Embedded Crowd. Starting with Jira 8.14, all passwords held in the Jira database in plain text will be encrypted. If you are a user of the upgrade, the encryption of passwords will be performed during the upgrade.
Hier ist die Liste der sensiblen Daten, die verschlüsselt werden:
