Healthcare benefiting from automation

What would someone decipher by the term ‘automation in healthcare’? Does it appear to you as robots operating human limbs or machines empathizing with patients? Well, not exactly! Automation in the healthcare sector focusses on improving the overall service that patients deserve since healthcare is a basic right and should not be mistaken as a privilege.

Healthcare industry – How is the transition shaping up?

The healthcare industry has made a massive shift; from the paper-based method of maintaining records to compiling digital records and practicing online information sharing. This industry, in particular, is critical and cannot afford even an iota of downtime. The medical practitioners must have consistent access to medical records and information of patients. Thus, the IT team needs to ensure a smooth functioning of the machines. In this regard, automation is truly an amazing solution that assists in enhancing the capabilities of data centers and ensured seamless operation. It also provides constant monitoring and real-time alerts, further preventing life-threatening system downtimes.

Automation in Healthcare: Still a mile apart

Currently, the two key focus areas of the healthcare industry include cost reduction and efficiency boosting. Highlighting trends, it is worthwhile to mention that the Japanese Lean approach has been adopted by the healthcare industry with basic focus on waste reduction and improvement of performance and efficiency through automation of manual tasks. Now, automation is reduction of human intervention by increasing dependence on artificial intelligence (AI). Infact, automation has engulfed our daily lives with ATMs, self-checkout in stores and auto-park assistance in connected vehicles etc. However, automation in the healthcare sector is comparatively a new concept, yet to be explored in entirety!

Need for automation is a priority

Population explosion has directly impacted the growth in ageing population. With age, people require greater medical attention and care. This increases the demand for healthcare professionals and care givers and in order to meet that growing demand, automation is the best possible solution. The rise in demand for healthcare solutions has been addressed by healthcare organizations by hiring more care givers. However,  secondary research reveals that the nursing shortage in the US is predicted to increase and the current number will come down to 260,000 registered nurses by 2025, thus indicating a steep fall in the volume of care givers. This shortage can be aptly handled by adoption of technology, further maximizing efficiency with minimal human resources. Although this may look like an ideal scenario, yet it is a massive challenge to motivate employees to imbibe technological changes and embrace the evolving landscape.

The acceptance of automation in healthcare industry transformed the concept of medical care and facility. According to Institute for Health Technology Transformation, “Automation makes population health management feasible, scalable and sustainable.” Similar to other sectors, initially automation was considered a negative aspect even in the healthcare sector. Pharmacists and medical professionals feared unemployment with the onset of automation and robotics. The thought here is not to replace a doctor by a robot, rather blend automation with the workflow of a medical professional to enhance efficiency and productivity of the medical attention procedure.

Engaging patients for an effective care

Medical care flourished and improved through empowering patients with gadgets and apps, that can engage and initiate awareness to participate in the healthcare process. For example, automated health monitoring reminders can create a great impact on the patient’s health, creating consciousness.

Garnering benefits of automation in healthcare

Introduction of automation in the healthcare sector has revolutionized the concept of medical facility and care. It has evolved from complete dependence on humans to sophisticated merger of both, humans and machines. The following are the advantages of leveraging automation in the healthcare domain.

  • Saving considerable time

Automation of manual tasks saves time. This, however, does not indicate firing of employees, rather, it focuses on elevating employee efficiency and support to successfully manage higher-functioning roles. Costly and repetitive individual tasks and complex workflows are usually time-consuming and can easily be automated.

  • Connecting medical facilities

Automation ensures end to end processing of customer information and reports for easy access and creation of a synergy between all healthcare activities conducted by the care center. A patient ideally is not well-versed with the series of medical services and fail to understand the correlation of one with the other. Here, automation helps to create that connect, extending a level of comfort to patients.

  • Enhancing quality and reliability

Automation in healthcare can improve quality and consistency to a great extent since, it reduces the chance of human error and fatigue. Thus, patients can expect consistency in care and service.

  • Data storage and access

As per market research, automation eases the process of storing medical data and order entries. This is useful during emergencies when doctors need quick access of patient’s reports and medical history, acting promptly to save a life.

  • Supporting system for decision-making

Automation ensured data-driven insight on patient’s health conditions. This impacted the decision making and choose the correct course of treatment which is reliable and efficient. Also, this enhanced decision-making capabilities of medical professionals, reduced deaths, minimized surgery complications and brought down medical expenses. Hence, the doctors have started relying on automation to support complex clinical decisions.  

  • Enhancing customer support

Automation empowered patients with self-service options and customer support for seamless self-service. This optimized the process with innovative technology and improved the course of patient care.

  • Improving understanding of patients  

Patients are unaware of the medical processes and its complexity hence, automation connected the medical team with the patients efficiently, helping them to understand the entire process of medical attention. It reduced the time and effort wasted in bridging the gap between a doctor and the patient.

  • Monitoring critical patients

The healthcare sector also implemented automation in post-operative care and Intensive Care Unit (ICU). This ensured automation of the patient’s lifecycle increasing visibility of the treatments given and its consequent result.

  • Managing outcome

For any industry to operate seamlessly, outcomes should be predictable. This is so true for the healthcare industry as well. It is convenient for patients to follow a standardized care path through automation due to its monitoring advantages.

  • Reducing wait-time for medical attention

Automation of healthcare tools can handle larger patient population with efficiency and satisfaction. This also enhanced the patient’s experience of the medical facility.

  • Changing the payment structure

The concept of health insurance has improved due to automation. Treatment was made possible without making any advance payment. This is a revolution in the field of medical attention.

  • Merging of technology

The forte of automation is its ability to integrate old legacy systems with the new evolving technology. The hospitals in United States of America maintains an integrated patient management system that contains reports, information and details of all patients. This combination improved the efficiency of the healthcare sector massively.

  • Ensuring security and compliance

The healthcare industry deals with sensitive information about patients, which is why, the data is critical and requires protection from hackers. Automation, here, plays an important role in safeguarding the data through stringent security regulations.

All the above are constructive steps towards improving the healthcare sector through adoption of automation technology.

Areas to Automate

Healthcare and automation in developing countries

Investments in the healthcare industry will not yield any direct and immediate gain. However, both Government and private investments in this sector will strengthen the automation that will ensure both, qualitative and economic advantages. Infact, the healthcare sectors in developing nations need a thrust of automation to meet the global standard of medicine and healthcare.

Hospitals and automation: Real-life scenario

Secondary market research on hospitals in Texas US, that adopted and implemented automation, showcased exemplary results. Patients treated in those hospitals had lower death rates, very few complications and manageable treatment cost. Government initiatives made it simple for the hospitals to adopt the automation technologies such as electronic medical records, computerized order entry systems and clinical decision support systems. This on one hand, reduced waste of manpower and time while on the other hand, improved its service quality. Automation of the hospital’s clinical information is categorized into four segments viz. medical notes, test results, order entry and decision support.

Healthcare reformed with GAVS

A need to improve patient care has led to the coalesce of technology and healthcare industry. In an attempt to do so, the industry eagerly embraced cloud computing, data analytics and security. GAVS Technologies is one such prominent company which empowered the healthcare sector with technology-led solutions and SMART delivery. Infact, GAVS successfully enabled many hospitals and healthcare centers to improve the quality of care offered to the patients.

GAVS revolutionized the healthcare sector with strategic and cost-effective healthcare technology solutions that blend conventional clinical approach with modern technologies. Needless to say, the world is witnessing a transformed healthcare facility through automation.

Role of artificial intelligence in the realm of cyber security

Are your Chopsticks (read AI Capabilities) strong enough to hold Cyber Threats?

Many psychologists have deciphered that intelligence is contagious. To a certain extent it might be true. If followed in entirety, the entire world would have been intelligent. Intelligence does create a spark and spreads an aura of enlightenment around the bearer. What if, a machine possesses a similar acumen? Wouldn’t that be a welcoming change? Artificial intelligence (AI), indeed, has been a well-accepted transformation that efficiently combines cognitive science, neuroscience and computer science to deliver tangible benefits. The benefits may be manifold, but the threats are equally voluminous, one key aspect being in the realm of cybersecurity.

Does AI make organizations vulnerable?

It’s both, a ‘Yes’ and a ‘No’! Yes, because, despite the presence of the right kind of technology to prevent cyber security breaches and safeguard data, each time hackers manage to develop newer avenues and tools to launch a cyber-attack. On the contrary, some deny this statement because AI plays a prominent role in enabling IT professionals to act proactively and take necessary corrective measures during potential cyber threats, thus ensuring enhanced safety over the company’s data pool.

Focusing on the “Yes”!

Interconnected workspaces couple with a massive and unprecedented growth of cloud and mobile technologies triggered a chain reaction, making the cyber space extremely vulnerable. This rapid growth of the cyber security landscape has compelled industry leaders to embrace AI and compete with hackers. However, hackers too depend on AI to initiate malware, that changes the system structure and prevents anyone from detecting it. Needless to say, the pace at which machine learning is being deployed in the cyber environment, it is seemingly difficult to keep up to that pace and upgrade the cyber security in tandem.

Cyber criminals adopt AI initially with a mindset to learn cyber defense tools in order to bypass the security algorithms to access personal information. Attackers leverage AI to customize email attacks, through which the invaders force individuals to share their security credentials. Such information is, then, misused to cause damage to the entire system. Thus, it isn’t incorrect to state that, AI can, both, be considered as a weapon of destruction and a sophisticated solution to cybercrime; depending totally on the mindset of individuals.

Role of AI in cyber security

AI provides innovative ways to increase cyber security in order to protect the network of the organization from unauthorized access or to prevent damage. Irrespective of the size of the organization, a vast amount of data is generated periodically. Such massive quantity of data, when stored in the company’s system, becomes vulnerable to cyber-attack. When sensitive information or personal or financial data of both, individual and organization, is compromised, it leads to serious consequences. Hence, cyber security is essential to protect data from exploiters.

The implementation of AI by organizations for daily cyber risk operations, has reduced pressure on humans to detect such intrusive attacks. Security software powered by AI can be leveraged to auto detect any suspicious activity and initiate necessary action to ensure normalcy. Since AI is designed to continuously learn and get implemented, hence it becomes more feature-enriched (showcasing better resistance) with each upgrade. In certain instances, companies are even adopting the hybrid approach integrating AI with nominal human intervention to garner optimum results.

Common cyber threats

The following are few cyber threats powered by AI:

  • Trickbot is an AI-based malware that targets only large enterprises.
  • Trojan is a malicious code that can infect systems automatically and it is extremely difficult to detect and remediate.

Organizations that embraced AI in cyber security space

Dodge the clasp of cyber threat

The following can be practiced for a cyber threat-free environment:

  1. Popup blocker should always be enabled, and one should fight the urge to click on a popup to open an unknown site.
  2. Keeping the system and the security tools updated can improve the overall cyber security since, older versions of operating system are vulnerable to cyber-attack.
  3. It is advisable to avoid third-party installations since; it has the potential to infect system with virus and malware.
  4. Periodic backup can also help to protect data.
  5. Finally, good anti-virus tools like ITL Total Security, Malwarebytes and Malware Crusher can ensure initial protection.   

Cyber security powered by AI – Advantages

  1. A cyber security system powered by AI can easily detect unexpected attacks on cyber space and protect the system from further intervention. Mostly, the malware attacks the core system, making it dysfunctional in a way that it is difficult to identify the affected area. This is where AI plays a crucial role in applying relevant algorithms to isolate malicious files in order to protect the system. 
  2. AI successfully reduces human intervention to fight unauthorized entry. Its usage of predictive analytics enhances the speed and competency of cyber security. The specialty of predictive tool is that, it collects user’s credential required to access the system and analyze the same with user behavior to predict any suspicious activity.
  3. AI plays an important part, especially in protecting login credentials based on biometrics. Biometric login access is dependent on fingerprints, palm prints and retina image scanning and large-scale enterprises has incorporated AI, based on global authentication to leverage real-time biometric login access.
  4. Organizations encounter cyber threats daily; it is manually cumbersome to segregate the actionable threats with those that can be ignored. This is where AI plays a big part in detecting actionable cyber threats.
  5. AI-based cyber security system can gauge and prioritize threat and automate threat response to manage security better.

What triggers AI-based cyber security?

According to secondary research, 29% of professionals dealing with cyber security focus on increasing the pace of incident detection. 27% of professionals try to improve system operation through prioritizing incidents and automating remediation of the same. Through AI-based cybersecurity 24% of the technology team can identify risk better and communicate the same to the enterprise as a precaution. 22% of IT professionals also emphasize on improving awareness across the organization.

The growing concerns

Although technology has come a long way yet, the irony lies in the fact that, many enterprises till date are trying to fix the internal security issues manually, whereas, the cyber bullies are launching their attacks leveraging AI. The usage of traditional tools to prevent cyber attacks is a futile effort since, the time lost in identifying the problems can compromise the entire system. Also, there is a shortage of security professionals who can handle challenges related to data security. Secondary research confirms that, on an average, enterprises invest approximately 146 days to fix critical issues. This indicates a need to change the approach in dealing with cyber security.

An ancient Chinese philosopher once said, “Don’t depend on the enemy not coming, depend rather on being ready for him”. So, why not improve the organizational detection and response capabilities through leveraging AI? In the past, protection of network and endpoint, what used to be just sufficient, is no more the situation. The security horizon has expanded beyond human controllable limits. There is also an eminent need to corelate internal security and external threats with business criticality. This can define the actual security gap and the impact it creates on the business. Another challenge that concerns business leaders is whether the cyber security powered by AI will be able to protect organizations in an automated manner.

Addressing challenges: Growing dependence on AI

According to market research, about 32% of companies are dependent on AI for their cyber security and on top of that, only 7% of the employees use cognitive-based AI tools till date. Big enterprises take a dual approach, where in one, AI is leveraged on top of the existing security systems, while in another approach, AI security system is incorporated along with other technologies such as security operations and analytics platform architecture (SOAPA).

As per secondary research, 91% of cyber-attacks trigger from an email which compels the business leaders to enhance security intelligence to safeguard systems. This acts as a game changer by creating a robust system, unaffected by the cruel intensions of cyber criminals. Only time can decide the fate of cyber security in the hands of AI. There is still some time to comprehend whether you have a strong chopstick in hand!

How our AIOps led Predictive Analytics platform can assist Service Desk Agents?

by Karthik Natesan Paranjothi

The following delivery model depicts a Typical Service Catalogued delivery of the IT Services with Onsite/Offshore Helpdesk and EUC services team to cater to the end-user queries. If the resolution is not made by the Helpdesk team, the ticket is transferred to the L2/L3 team.



“A typical day in the life of the service desk” as above

Typical Challenges in IT Service Desk

A key driver of customer satisfaction is related to how quickly a helpdesk team can resolve an issue (As per Gartner 2018 Key Service Desk Recommendations, the average IT service desk first contact resolution rate is 70.6%.). Organizations are constantly striving to provide better customer service by optimizing key metrics such as Mean Time To Resolution (MTTR), Defect Removal Efficiency (DRE) and so on.

Considering the volumes of data produced annually in this digital world, the conventional technologies cannot keep up with it or analyze to produce valuable insights for the workforce to take necessary actions. There is a deluge of data types at increasing velocities.

Currently, IT operations team is spending more time in sharing or interpreting the data produced by the various ITIM monitoring tools which monitors and collates the availability and resource utilization metrics of servers, networks, database instances, hypervisors and storage.

Clients are seeking vendors who can provide the following benefits

  • Provide better diagnosis capability to improve the accuracy of anomaly detection and alerting
  • Provide unified dashboards with better user interfaces across various domains
  • Vendors who can provide both on-premise and SaaS based service offerings
  • Without any restrictions to their own environment (Ex: Amazon Web Services [AWS] CloudWatch)
  • Better tools to monitor the health of the devices and capture interesting data from the environment where the devices are deployed

GAVS’ Solution

Leveraging our experience in providing Service Desk and managed IT infrastructure services across industries, GAVS developed an AIOps based TechOps platform that enables proactive detection and remediation of incidents helping organizations drive towards a Zero Incident EnterpriseTM. (ZIF).  ZIF’s components Discover,, Monitor, Analyze, Predict and Remediate, collaborate with each other and prepares IT organizations to aspire for incident free enterprise.

AIOps based TechOps platform consists of AIOps based Predictive Analytics & Automation platform which provides cost-effective and efficient solution for service desk clients across geographies. It has helped us provide FCR over 80% and cost savings in the range of 30-40% for our clients.

Gartner describes ‘AIOps Platform’ as using big data, modern machine learning and other advanced analytics technologies “to, directly and indirectly, enhance IT operations (monitoring, automation and service desk) functions with proactive, personal and dynamic insight.” And it sees AIOps platforms as taking data from all those different domain-specific monitoring tools to provide a centralized, unified view of operations.

GAVS’ AIOps platform – the application of AI and machine-learning (ML) technologies to IT operations to detect, diagnose, and resolve issues even before service desk agents become aware of those issues. Our ML model is trained to process all types of data generated by your monitoring systems. The data generated from the IT operations monitoring tools are aggregated and correlated using advance machine learning algorithms. It enables enterprises to view day-to-day functioning of IT operations using Unified Dashboard, leading to improved transparency and setting expectations with users, to reduce negative CSAT. The AIOps platform integrates with our automation platform and automates common and repetitive tasks / work.

Predictive algorithms enable technicians to pre-empt and resolve incidents. It provides the status of tickets through dynamic visualization and uses statistical models on past incidents to help assign accurate estimated time to resolve issues thereby improving customer satisfaction.

By introducing or integrating, GAVS’ AIOps Platform with <<Client>> existing environment “A day in the life of Service Desk agent” will be transformed as depicted in the below image

GAVS’ Solutions

We will implement AIOPs based Analytics Platform on top of existing ITSM tool and provide the following solution

AIOps Platform

  • Automated pattern discovery and prediction – Our AIOps platform goes through a three-stage process of data aggregation, analysis and visualization. The platform uses AI and ML algorithms to correlate events that are generated from various monitoring tools and then proactively identifies risks based on patterns that are occurring in the environment
    • Event Correlation though events / logs / alerts aggregation from multiple OS, applications, correlate them using ML & NLP techniques to identity the root cause quickly
    • Reduce ‘false positives’ through correlation by Pattern recognition and machine-learning capabilities
    • Faster root cause analysis through correlation
  • ZIF uses ML and predictive techniques to identify an event that can turn into a high severity incident even before it reached the service desk agent
  • ZIF can perform Level-0 Triaging of incidents and assign it to the appropriate desk agent
  • Social Media Integration – We have integrated our AIOPs platform with leading social media platforms such as Facebook@work, WhatsApp and Twitter to provide enhanced user experience. The end users can raise issues or service requests through Facebook, from any place or device, and they can automatically connect with Service Desk team
  • AI Voice Assistance – GAVS Virtual Assistant can handle customer requests from websites, mobile apps, consumer messaging apps and social networks like Facebook@work, WhatsApp and Twitter and resolve some of the repetitive service requests like unlocking accounts, resetting passwords, even complex tasks like providing access to folders.

By 2020, 20% of citizens in developed countries will use AI assistants to help them with an array of operational tasks”

Organizations report a reduction of up to 70 percent in call, chat and/or email inquiries after implementing a VCA, according to Gartner

  • AI Aided Chatbots – Our Chatbots will deliver next generation intelligent customer service. Our Chatbots will offer conversational experience using artificial intelligence and natural language processing and act like Human-like Advisor and resolve repetitive service requests. For example: It can understand questions and gives the user the most relevant answer

“By 2020, the average person will have more conversations a day with bots than they do with their spouse”

  • ZIF’s  custom developed Unified Dashboard offers 360° view offers view of the enterprise. It enables enterprises to view day-to-day functioning of IT operations, leading to improved transparency and setting expectations with users, to reduce negative CSAT.
  • Creates a knowledge base for faster remediation leveraging past experience
  • ZIF’s  custom developed Unified Dashboard offers 360° view offers view of the enterprise. It enables enterprises to view day-to-day functioning of IT operations, leading to improved transparency and setting expectations with users, to reduce negative CSAT.
  • Creates a knowledge base for faster remediation leveraging past experience

Implementation Approach

ZIF can be deployed as SaaS platform in Microsoft Azure or can be hosted locally within <Client> premise.

The decision of hosting the platform lies with you. The <client> should provide required compute resources (VM, OS, DB) and Network connectivity if hosted on-premises.

Service Desk Formula for Success

By Roman Kruglov

First, let me start with saying there is no magic formula of 1+1= success, but here are a few key points that will help you get there. It all starts with people; having the right team in place is essential, and knowing each person’s strength and weakness is a must. Develop the trust of your people and do not be a manager but be a leader instead. Get your hands dirty if needed, do not ask your team members to do things you are not willing to do yourself. Also, remember a simple thank you goes a long way. When the team members feel appreciated, they will work harder to achieve the common goal of making the customer happy. Having a weekly meeting helps to make sure that everyone is on the same page, in some cases that meeting may need to happen daily. At first, when you are trying to get things under control, you will want to assign tickets based on each person’s strength that will help you maximize the performance of the service desk to get the backlog under control. FCR- first call resolution is very important the more incidents you can resolve on the spot, the better it will be. Once you have a stable environment, you can take your time and work on the weak points. Keep in mind that each company and environment will require slightly different ingredients to accomplish success. Second, you must create service desk documentation: Standard Operating Procedure, Incident Management, Problem Management, Change Management, Service Desk Mission Statement, SLA Managements, and Service Desk Flow-Chart. Here is an example of the service desk flow, which can be different for each customer or business:

Those documents will need to be agreed upon with management and then distributed to all team members to follow. Documents should be updated as often as the business requires, and the changes should be communicated to everyone. Documents should also be made public on the company intranet for all employees to see. Communication plays a key role here to make sure everyone is on the same page and not just the service desk.

Third, this one can be tricky, but it does start with the right team, that we already talked about, if you have the right team in place, this should be easy to accomplish. We are talking about Service Desk Principals, the following list should be memorized and can apply to any business and any service desk, helpdesk or plain old service department. This list is how you accomplish trust and success with the customer:

Customer Obsession

Everything starts with the customer. Service Desk will work vigorously to earn and keep customer trust. Put yourself in the customer shoes.

Ownership

Think long term and don’t sacrifice long-term value for short-term results. Never say, “that’s not my job.”

Learn and Be Curious

Service Desk is never done learning and always seeks to improve themselves. They are curious about new possibilities and act to explore them.

Think Big

Thinking small is a self-fulfilling prophecy. Think differently and look around corners for ways to serve customers.

Bias for Action

Speed matters in business. Many decisions and actions are reversible and do not need extensive study.

Frugality

Accomplish more with less. Constraints breed resourcefulness, self-sufficiency, and invention.

Earn Trust

Listen attentively, speak candidly, and treat others respectfully. It takes times to build trust

Dive Deep

Operate at all levels, stay connected to the details. No task is beneath us.

Deliver Results

Focus on the key inputs for the business and deliver the right quality and in a timely fashion. Rise to the occasion and never settle.

To summarize, all of the above is just a framework that will need to be adjusted and changed based on the requirements and the environment you are in. Be prepared to change things on the fly and do not be afraid of the change, as the business grows and the requirements change, what worked in the past may not work in the future, you have continually look at the environment and adjust accordingly.

Bonus Round: 2 things that will help streamline things:

  1. Eliminating Common incidents by finding the root cause
  2. Automating by using tools such as self-service, knowledge management, zMan by Gavs

About the Author:

Roman Kruglov was born in Moscow but has lived in New York City where he is constantly shooting pictures when not working as Service Desk Manager with over 22 years of experience Implementing, managing and delivering IT services to drive company growth and technical innovation.

His love for photography came at an early age. He says, “ I remember the dark room and watching the pictures magically come to life.”  He says he tries to photograph every day and his camera goes with him everywhere he goes. The inspiration for his photos come from seeing them develop on the screen much like they used to develop in the darkroom and then being able to share those developed pictures.

Roman’s work has been published in Dodho Magazine, Popular Photography June 2014, Bloomberg, Popular Science, Business Insider and a book called “How to Photograph Everything.”

Role of a Business Analyst in the Agile World

By Chandrababu Mandadi

Agile is defined as collaboration among stakeholders to deliver value to customers in frequent increments with consistent         reflection and adoption. This definition focuses on the characteristics that exist in all agile environments.

Collaboration refers to thepeople involved in the effort work together which includes both the delivery team and project stakeholders.

Deliver value implies thetrue purpose of efforts which provide value to customers, whether that is through new software, more efficient processes or new products.

Frequent increments – the  team delivers value every few days, weeks, or months rather than once at the end of a project.

Consistent reflection and adaptation – theproject team reflects on their approach and the product on a regular basis and adjusts accordingly.

Agile Roles –  There are four primary roles included in an agile project.

The Product Owner is the ultimate decision maker for the product. This role is responsible for defining the product vision, prioritizing features according to business value, and answering team questions.

Business Analyst (BA) as a Business Advisor approach has a specific role to represent the ultimate business decision maker, such as the role titled product owner. The product owner sets the product vision and is responsible for understanding and representing the needs of the business and user stakeholders. The product owner determines which requirements are most important prior to the start of each iteration and determines how to release value incrementally to best satisfy the needs of the product stakeholders.

A BA does not always have the decision-making authority necessary to be an effective product owner, but they can become indispensable by supplementing a product owner’s lack of time or business analysis skill sets.

A BA supports a product owner by helping them analyze the business domain, stocking the product backlog, and grooming the product backlog.

Analyze the Business Domain – TheBA helps the team and product owner to understand and describe the business domain and problem to be solved by facilitating the discussion that explores the following questions:

  • What business processes need to be revised, created or eliminated?
  • What information do we want to know about and track about various entities?
  • What stakeholders (such as customers, suppliers, vendors) and systems are involved in the effort?
  • What policies and rules guide business behavior and decision?

The BA helps the team decide if the requirement models are useful beyond the life of the project. Factors to include in the decision are the effort required to keep the model up to date and the value of the model after the code.

Stock the Product Backlog to establish a list of user stories that represent the overall scope of the project. A user story briefly describes functionality or a feature valuable to either a user or customer of a system or a solution.

The BA helps the product owner, stakeholders, and the team to create stories as a reminder to deliver some functionality represented by the models or discussed in a conversation. Stories can be delivered from requirements models such as data models, process flows, workflow diagrams, use cases, business rules and user interface diagrams.

Stories can be delivered from requirement models such as data models, process flows, workflow diagram, use cases, business rules and user interface diagrams.

Groom the Product Backlog to maintain the product backlog so that it remains a tool for the product owner and team and not a burden.

The BA helps the product owner groom the product backlog by considering purpose, prioritizing the stories, operating the stories, splitting epics into user stories, and ensure a complete description of the solution.

He can help the product owner, order the product backlog by providing information on stakeholder’s perceived value of the various items in the product backlog. The model does not provide guidance on priority, but there are other techniques used to gather priority information from multiple stakeholders. Two of these techniques are value points and buying features.

In the value points approach, stakeholders are asked to get together as a group and indicate the relative value of stories in comparison to other stories in an approach similar to planning poker.

Business Analyst as Business Coach During iteration, the business analyst interacts with the team, acting as the analysis specialist in the team. Some of the activities the business analyst performs or provides coaching to the team during iteration include facilitating collaboration, generating examples, transferring knowledge, and being a good team member.

Facilitate Collaboration – within the team and between the team and team and stakeholders is vital for project success. Business analysts facilitate collaboration through helping with stakeholder analysis and acting as a language coach.

The BA has clear understanding of the stakeholders involved in the project so they can provide suggestions about which stakeholders that team member should talk to, for relevant information. Once they have helped their teammates identify the appropriate stakeholders to talk to, business analysts turn their experience translating “business speak” into “technical speak” and vice versa by helping team members from different backgrounds and team members and stakeholders “speak the same language”.

Generate Examples – Teams in an agile environment use examples to clearly communicate business intent, provide more detail about stories, and to confirm those stories were delivered properly. Examples are a good technique for remembering the information discussed during conversations, communicating that information to the team members who will deliver the user story, and for confirming the user story was delivered properly.

Transfer Knowledge – The BA along with the product owner have the best grasp of the big picture of the project and where it fits within the organization strategy. They spend a considerable amount of time during the work of the iteration transferring to the other team members the information gained while they were acting as a business advisor.

The best way to transfer that knowledge is to involve the team members in the analysis of the business domain and the stocking and grooming of the backlog.

Be a Good Team Member – B  BA gets the opportunity to help their teammates clear bottlenecks. Doing this improves relationships with the other team members and gives the BA an opportunity to expand their toolkit and learn new skillset through performing tasks.

Key BA Skills for Agile Projects – high-performance business analysis professional in the team increases the likelihood that the resulting product meets true business needs and fits in well with the current business environment.

Key business analyst skills that an agile project needs are;

  • Understanding of the business that the project is involved with
  • Ability to see the big picture and provide solutions
  • Outstanding verbal and non-verbal communication skills
  • Ability to multi-task
  • Ability to facilitate a team to consensus on scope, design decision, and implementation
  • Ability to ask strong questions to help team
  • Ability to document requirements
  • Understanding of the agile development process
  • Ability to lead the team for project completion

About the Author:

Chandrababu Mandadi is a Lead Consultant @ GAVS. An accomplished, result-driven and highly analytical professional with expertise in driving client and software development life cycle in Agile and Waterfall methodologies across US Healthcare and Life Insurance domain.

Passionate about:

  • Leadership and client management.
  • Data Analytics.
  • New Technologies.
  • Interacting with Businesspeople to understand and help them on their Business obstacles.

“Why” of GAVS, Our humble effort to make GAVS an aspirational company, GAVS DRHM2019

By Sumit Ganguli, CEO, GAVS Technologies

We were humbled to be associated with the GAVS Dream Runners Half Marathon 2019 that was held on July 21st Sunday in Chennai, and its moniker is We run so they can walk.  GAVS has been involved with the Dream Runners Half Marathon for the last 4 years and along with the Dr. Sunder and the ‘Freedom Trust’, this event raises funds for the prosthetic limbs for some of the under privileged. This year, we distributed 180 prosthetic limbs to some of the recipients and it was so gratifying that some of them ran a short distance with us after the run.

Subaja, 27 years, is from the small hamlet of Nagercoil in the South of India, she lost both her legs below the knee in a train accident 13 years ago. She couldn’t afford prosthetics and was entirely dependent on her family to help her with her daily chores. She soon lost her parents and was turned out by her brothers due to their poor financial condition.  Moving away from her home, alone in a new city, Subaja found a job that paid her a paltry sum of Rs.  5,000 (under 75 dollars a month),  by filling applications for visitors outside the local District Collector’s Office. Subaja is now a wheelchair basketball player and a national champion. GAVS DRHM along with ‘Freedom Trust’ fitted her with blade prosthetics and she ran at the recent GAVS DRHM held on July 21, 2019. When she says “never give up, keep trying till the end”, we at GAVS are inspired by Subaja.

Sumith, aged 10, from an extremely small village in Tamil Nadu,  was born with a congenital disorder, with an uneven lower right leg.  He is a Class 6 student and in need of prosthetics which his father could not afford.  GAVS DRHM and ‘Freedom Trust’ made it possible for him to be fitted with customized above-knee prosthesis.  Sumith was full of smiles as he walked with his new leg at the recent marathon. It was heart-warming to see the tears in his father’s eyes as he said “my son will not have any more difficulties to go to school…”

We are happy and proud to see that GAVS DRHM has transformed running, an individual’s sport into the huge mass phenomenon in Chennai. It starts at 4 am in the morning on Sunday. Highly disciplined and effusive volunteers, not a single wayward participant, very clean conscious runners and officials, the police force that comes out in droves, the drummers,  the cheering crew, all represent  the best Chennai has to offer.

It provides GAVS with a higher purpose and it is our endeavour to make GAVS an aspirational company. We look forward to your mentorship and counsel and took the liberty of sharing this with you.

Video links

https://youtu.be/exYTR5vECJQ

https://youtu.be/-kc-f8U_tSQ

Why Scala for Big data and Machine Learning?

By Bargunan Somasundaram

Before delving into why scala for the Big Data and Machine learning, lets me address what are these jargons and how they are interrelated?

Big data, machine learning, statistics, statistical machine learning are the terms that are surfacing the IT world recently. We are in the new era of huge data being generated each second. According to forbes.com, at our current pace, 2.5 quintillion bytes of data created each day, with the growth of IOT. From these data, the insights are generated to lead new business. The process of analyzing and extracting information to generate insights from this big amount of structured, semi-structured, unstructured data is called big data. 

Now with the help of Artificial Intelligence and algorithms if the system is able to automatically learn and improve to generate insights from data, without any explicit intervention or rule-based programming, then it’s called machine learning. 

We are in the midst of a data revolution, and this has given rise to completely new data formats and databases of unprecedented scale. This humongous rise in the data and the ability to analyze extract and generate from insights has related big data with machine learning. 

As a rule of thumb, the accuracy of pattern finding or data mining or a knowledge discovery of the machine learning algorithm depends on the volume of the data that the algorithm has processed. So more the data, more the learning. 
Python and R are the prominent programming languages for machine learning and data sciences. Now scala is climbing the ladder fast due to the rise in usage of Apache Spark. 

Scala as Language for Frameworks. 

Some of the frameworks that rule the roost in the Big data world are  

  • Apache Spark is a unified analytics engine for big data processing with lot more features like SQL and DataFrames, MLlib for machine learning, GraphX, and Spark Streaming.

 Apache Spark, built on Scala has gained a lot of recognition and is being used widely in productions. Resilient Distributed Datasets (RDD) is a fundamental data structure of Spark. Immutable, distributed, lazily evaluated, catchable are its common properties. 

  • Apache Kafka - a distributed streaming platform for handling real-time data feeds. 

Written in Java and Scala, Kafka is a fast, scalable, durable, and fault-tolerant publish-subscribe messaging system. It works in combination with Apache Storm, Apache HBase and Apache Spark for real-time analysis and rendering of streaming data. 

  • Apache Samza a stream processing framework developed in scala. 

Apache Samza uses Apache Kafka for messaging, and Apache Hadoop YARN to provide fault tolerance, processor isolation, security, and resource management. Samza is similar to Apache Storm while it is easier to operate. Samza stream processing job were written in Scala. 

  • Apache scalding a Scala API for the Cascading, an abstraction of MapReduce 

Built on top of Cascading, a Java library that abstracts Hadoop MapReduce, Scalding simplifies writing the MapReduce jobs in Scala. Scalding is comparable to Pig, while offering tight integration with Scala 

  • Apache Flink — a framework for distributed stream and batch data processing 

Flink’s core is a hybrid (Real-Time Streaming + Batch) distributed data processing engine written in Java and Scala. Flink contains several APIs for batch processing (DataSet API), real-time streaming (DataStream API) and relational queries (Table API) and also domain-specific libraries for machine learning (FlinkML — pure Scala), complex event processing (CEP) and graph processing (Gelly). 

  • Akka — a concurrent framework for building distributed applications 

Akka is an actor-based message-driven runtime for managing concurrency, elasticity and resilience on the JVM that supports Java and Scala. Akka uses Actor Model that is an ideal model for highly scalable and concurrent systems. 

Scala packs the punch of both Functional and object-oriented programming. 

Not to mention that scala is one of the JVM language and its biggest advantages is its support for both object-oriented and functional programming. Both programming approaches aim to create readable, bug-free code, but they go about it in very different ways. Where object-oriented programming combines data structures with the actions you want to perform on them, functional programming keeps both separate. 

Each approach has its advantages. For many people, the object-oriented paradigm makes intuitive sense, and combining behaviors with the data structures they’ll interact with can make it easy to figure out what’s going on in an unfamiliar codebase. At the same time, functional programming’s preference for cleanly separated and immutable data structures and discrete behaviors often allows you to do more with less code. Functional programming aims at the usage of Lambda Expressions. The point of all lambdas is deferred execution. After all, if you wanted to execute some code right now, you’d do that, without wrapping it inside a lambda.

There are many reasons for executing code later, such as

  • Running the code in a separate thread
  • Running the code multiple times
  • Running the code at the right point in an algorithm (for example, the comparison operation in sorting)
  • Running the code when something happens (a button was clicked, data has arrived, and so on)
  • Running the code only when necessary

It is a good idea to think through what you want to achieve when you set out programming with lambdas. Let us look at a simple example. Suppose you log an event:

logger.info(“x: ” + x + “, y: ” + y);

What happens if the log level is set to suppress INFO messages? The message string is computed and passed to the info method, which then decides to throw it away. Wouldn’t it be nicer if the string concatenation only happened when necessary? Running code only when necessary is a use case for lambdas

Scala is a fully-fledged OOP language, and it’s possible to write highly elegant and expressive programs without even touching its functional attributes. But for those who are curious about functional programming, Scala provides a rich set of collection operations (like map and reduce), higher-order functions, and a strong static typing system. 

About that static typing system:

Where many other modern programming languages are dynamically typed, Scala checks types at compile time, meaning that many trivial but costly bugs can be caught at compile time rather than in production. At the same time, Scala has a highly sophisticated type system, meaning that developers can enjoy the security of compile-time type-checking without having to worry about specifying every type every time. 

Concise programming with scala 

  1. Scala programming language is concise. Several loops can be replaced by a single word that makes it significantly less verbose than standard Java. In addition, its statically typed and functional nature makes it type-safe.  

Eg In java code to reverse a list. 

    List<String> reversedValues = new ArrayList<String>();

    for (String n : nameList)

     {

      reversedValues .add(n.reverse());

  }

return reversedValues ;

Scala equivalent of reversing the list.

  for (n <- nameList) yield n.reverse or nameList.map(_.reverse)

  • Pattern matching mechanism — the second most used feature of Scala, which allows to match on any sort of data with a first-match policy.  
  • The ability to use functions as variables and reusing utility functions  

Streams processing in real-time 

While the Hadoop MapReduce can process and generate large datasets in-parallel, it has been criticized for the inability to handle real-time stream processing. Spark gives Scala an edge over other programming languages to process streams in real-time. It has made Scala the computational engine for the fast data processing. 

Plethora of Machine learning Libraries and evolving communities 

Even though Scala’s libraries are not as comprehensive as Python or R libraries, they provide a solid foundation for big data projects. Awesome Machine Learning which is a curated list of machine learning frameworks, libraries and software (covering several languages), presents a list of useful Scala libraries and tools for Machine Learning, data analysis, data visualization, and NLP. In addition, Typelevel provides several helpful libraries and extensions to Scala. 

Following libraries are few of the most used machine learning and data analysis libraries: 

  1. Saddle — a high-performance data manipulation library (strongly influenced by the pandas library for Python) 
  2. ScalaNLP — a suite of different libraries, including Breeze (set of libraries for machine learning and numerical computing) and Epic (high-performance statistical parser and structured prediction library). 
  3. Apache Spark MLlib — machine learning library for Scala, Java, Python, and R 
  4. Apache PredictionIO — a machine learning server based on Apache Spark, HBase and Spray that can be installed as a full machine learning stack 
  5. DEEPLEARNING4J — a distributed deep-learning library for Java and Scala 
  6. Scala-datatable and Framian — for data frames and data tables 

Scala has an active community that is expanding rapidly. According to the KDnuggets Analytics/Data Science 2016 Software Poll, Scala was among the tools with the highest growth. 

Scala has an active community on Stack Overflow, in addition to its large community on GitHub and Reddit

About the Author: I’m an open source lover and a Java enthusiast. It’s my passion to share my knowledge by writing my experience about them. I believe “Gaining knowledge is the first step to wisdom and sharing it is the first step to humanity. “

Best Practices in the Airline Industry

By Srinivasan Radhakrishnan

The Airlines Industry is one of the most scrutinized  sectors where customer experience creates international headlines while the capital expenditure pressures and the revenues follow the cycles of the very expensive flight fuel and can take a company to bankruptcy in a couple of quarters. In the midst of all of this the airline sector has to really innovate in every small way possible for the best of the customer experience and the enhanced bottom lines. In my own small way, I bring out the some of the approaches taken that have been trendsetting in the airlines sectors.

Improving Passenger’s onboard experience on In-Flight Entertainment (IFE)

Following the success of the deployment of virtual reality (VR) headsets on air routes in the United States, FlixBus also partnered with Inflight VR to offer immersive entertainment to its passengers on the routes. Their aim is to make today’s most emerging technology work, and thorough approach addresses all technical, logistic, usability and rights management aspects to make this a seamless way for FlixBus to amaze their passengers and build a closer relationship to their brand.

The VR-powered IFE platform allows for many different third-party application integrations ranging from VR storytelling to destination-based content, such as sightseeing tours or tourist shopping. The platform has the potential to be an entirely new form of IFE that can generate revenue for airlines.

Increasing accountability of Revenue Management

Airlines always track the volume of sales its reservations agents make and also track time taken for a ramp services team to unload an aircraft full of bags. But what does a revenue management analyst bring to the table?  The models of revenue management and optimization enables most of the decisions. But it is about increasing the accountability of the analyst.

There are various metrics that can showcase it. There are metrics that can calculate both the total forecast accuracy and forecast the extra value add brought by the analyst (how much his/her interventions in accuracy improvement). A “revenue opportunity” model calculates missed opportunities- e.g.- seats went out empty or alternatively too many low fare seats were sold.

Other metrics, in addition to unit revenue changes, include frequency, and documented logic for model interventions. More qualitative measures include increased expertise in analytics and participation in group and interdepartmental discussions.

Using Available Seat Miles and Load Factor

 Available Seat Miles (ASM) may make load factor more understandable. The ASM of an airline measures how many passenger travel miles are available at a given time which is used to express the capacity of the airline. Higher load factor values make the airline more profitable by spreading fixed costs across the passengers.

Using the ASM and load factor, investors can determine the revenue gained when planes are filled to a particular level.  Airlines typically have thin profit margins and must have high load factors to stay profitable.

Strategic planning entails the use of Break-even load factors.  Budget airlines focus on high load factors. While the premium players charge more for their services and stay afloat even with lower load factors.

Monitor and Control Risk in Aviation Hazard Management

Best practices dictate that risk is minimized to as low as reasonably practical with the implementation of “controls in depth.” Implementing “controls in depth” means that there will always be redundancy, or a failover mechanism should a hazard manifest itself and the primary risk control strategy fails.

The cost of controlling hazards’ risks is always considered whenever determining what is “reasonably practicable.” Cost really jumps to the forefront of any risk management discussion whenever costs are grossly disproportionate to the risk. For example, implementing expensive risk controls may not be required for managing low level risk hazards.

Short term corrective and preventive actions often play important roles in mitigating risk until the operator has sufficient time and resources for a long-term solution. Risk control are not always of the corrective or preventive nature. Another very important type of risk control in aviation SMS is the “detective risk control.” Detective risk controls are designed to alert either users or monitoring equipment that a hazard is developing. It is highly likely that your risk management processes have a combination of all three types of risk controls.

Improve Customer Services

The basic rules of airline customer services are follows:

  1. Offer the lowest fare available.
  2.  Notify customers of known delays, cancellations, and diversions in proper way.
  3. Deliver baggage on time, and support an increase in the baggage liability limit.
  4. Allow reservations to be held or cancelled, and provide prompt ticket refunds.
  5. Properly accommodate disabled and special-needs passengers.
  6. Meeting customers’ essential needs during long, on-aircraft delays.
  7. Handling “bumped” passengers with fairness and consistency.
  8. Disclosing travel itinerary, cancellation policies, frequent flyer rules, and aircraft configuration.
  9. Ensuring good customer service interaction between code-share partners.
  10.  Make sure CRM team provides more effective responses to customer queries and concerns
  11.  Make sure IBE(Internet Booking Engines) provides nearby good hotels, Rental cars, holiday trips and Insurances  to enable easy access for customers
  12. Good relationships with travel aggregators

If these facets are covered airlines have a good chance to stay profitable and happy!

Microservices based Digital Transformation

By Vasudevan Gopalan

Do we know the ABC of Digital Transformation? Well, here it is in simple terms:

A – API

B – Backend as Service

C – Customer Experience

Isn’t focussing on the above 3 tenets a smart way for any organization to kick-start their Digital Transformation journey? And that is exactly what Microservices brings to the forefront.

Why Microservices?

Monolithic architecture system used to previously get built as a single, autonomous unit. Whenever a slight modification or bug fix was needed, it often came with rebuilding and deploying an entirely new version of the application. With the implementation of microservices, processes are simplified, streamlined, easily scalable.

Some benefits listed here,

  1. Allows to change services as needed by Business, without much cost
  2. API based connectivity
  3. Loosely coupled and can communicate with other services using industry standards like HTTP, JSON
  4. Gives developers freedom to independently develop and deploy services
  5. Every service can be coded in different programming language (remember the stacks like MEAN, MERN?)
  6. Better scale up and fault tolerance
  7. Easily deployable and disposable, making possible even multiple releases within a day

What is Microservice Architecture?

Essentially, microservice architecture is a method of developing software applications as a suite of independently deployable, small, modular services in which each service runs a unique process and communicates through a well-defined, lightweight mechanism to serve a business goal.

Microservices is purely based on Domain Taxonomy i.e. business functionality oriented – for example, fetching balance for a given bank account, calculating tax component for a shopping cart checkout etc.

In case if we are wondering how different from Service Oriented Architecture (SoA),

Microservices SoA
Many small components Fewer more sophisticated components
Business logic lives inside single service domain Business logic could live across domains
Simple wire protocols (HTTP with XML/JSON) Enterprise Service Bus like layers between services
API driven with SDKs/Clients Middleware driven

Netflix, eBay, Amazon, Forward, Twitter, PayPal, Gilt, Bluemix, Soundcloud, The Guardian, and many other large-scale enterprises, websites and applications have all evolved from monolithic to microservices architecture. Let us get a peek into some of their transformation journeys.

Netflix is the king of microservices. In 2015, JAX unanimously selected Netflix for the Special Jury award, citing the developer team’s huge influence on innovation and IT. In order to keep up with booming demand, Netflix began to move a monolithic architecture to a cloud-based microservices architecture in 2009. At this time, the term microservices didn’t even exist. Operating on a monolithic architecture, Netflix was dealing with rapid growing pains and constant outages when Amazon’s servers went down. Thanks to microservices architecture and modern UI technology, Netflix engineers deploy code thousands of times per day. Today Netflix services 93.8 million users globally, streaming more than ten billion hours of movies and shows.

Amazon: Before, when amazon was on a monolithic server, it was hard to predict how to meet the fluctuating traffic demands. As a result, Amazon was bleeding money and most of the server capacity was wasted during downtimes. Moving to the Amazon Web Services (AWS) cloud allowed Amazon to scale up or down when necessary, reduce the number and duration of outages, and save money. Microservice architecture allowed Amazon to transition to continuous deployment, and now Amazon engineers deploy code every 11.7 seconds.

Ok now, how do we transition to Microservices?

There are 2 ways of doing this,

  1. Start new application with Microservices architecture right away
  2. Start with monolith and gradually split and migrate to Microservices

In either approach, below are the steps of importance in the journey,

  1. Domain Driven Design – Modularize the services based on business context
  2. Service Discovery – Ability to dynamically discover and access services in order to truly decouple and isolate them
  3. Containerize – Leverage container technologies like Docker, Kubernetes to offer flexibility to move individual services across multiple environments (development, test, production)
  4. Build API Gateway – This acts as the façade in a distributed environment such as this, and also becomes the single point of entry of Microservices for client interactions. Leverage this layer for also cross cutting concerns like Logging, Security, Audit trails etc.

Reference Architecture

To sum up, be it Cloud Adoption or Agile & DevOps based delivery or any digital transformation strategy for enterprises, Microservices are becoming indispensable value proposition.

And the next time when you go online to buy your favourite item, do remember that there are 1000+ microservices that come into the play whilst you happily wade through the landing page at amazon.com 😊

About the author:

Vasudevan Gopalan (Vasu) is a Digital Transformation Leader with rich experience in Engineering, Delivery, Transition, Program and Client Relationship Management with multiple tier-1 IT organizations, with focus in the BFSI domain

Digital Mindset: 5 Aspects that Drive Digital Transformation

Kerrie Hoffman

Strategic Advisor, GAVS, Partner at Get Digital Velocity, Business Coach at FocalPoint Business Coaching

Moving from a traditional business model and operations to a Digital Business is a massive undertaking that needs to be approached in bite size steps. There are many areas within talent, operations, and technology that will significantly change throughout the transformation. This article touches on one area of talent: digital transformation requires a digital mindset. 

There are 5 aspects of a Digital Mindset:

  • Behaviors and attitudes that see possibility in the digital era
  • A belief in the power of technology
  • An abundance mentality
  • Comfort with ambiguity
  • A growth outlook

Aspect #1: Individual & organizational behaviors and attitudes that see the possibility in the digital era. You must believe digital is within reach as a prerequisite to taking any action. An attitude that sees the possibility of digital as producing positive business outcomes is more likely to come up with ideas, test them and refine them until a superior outcome is achieved. Without the right attitude, no amount of knowledge and hard work will land a company in a better place.  Here’s a fun puzzle from one of my FocalPoint colleagues, Phil Gilkes:

Aspect #2: a belief in the power of technology to systematize, scale and speed up every interaction. We are all familiar with and are likely still using traditional technology that promised to make our lives easier and seems to constrain us in many ways. So, it’s hard to believe that a modernly architected Platform or Software as a Service (PaaS/SaaS), is really going to systemize, scale, and speed up every interaction. BUT IT WILL!  Modernly architected solutions are completely different than traditionally architected solutions. There are 3 technology accelerators that are the basis of the current exponential growth in technology: computer power, bandwidth and storage.  Traditional technology is built on early generations of these accelerators. To take advantage of the current generation of these accelerators, modern technology platforms have been re-architected to leverage the latest versions.  Believe in modernly architected solutions and you will find a plethora of examples through simple Google searches to substantiate your belief! These modernly architected solutions can be implemented in days and weeks, and will dramatically improve business operations. You can’t get to digital with traditional technology (and a whole new way of working).

Aspect #3: An abundance mentality is collaborative, open, thankful, appreciative, and trusting. The traditional business world is built on a mentality of scarcity.  This drives the need to keep IP a secret, beat your competitors and fight the war to get the best talent. We are now living in a world where the pace of business continues to accelerate at a rapid pace.  Long standing traditional businesses that learn to move 10-50 times faster than they have in the past are the ones that will keep up. We often see Natively Digital companies being founded by people that were frustrated with the pace of taking new ideas to market in those traditional companies. Digital companies have an abundance mentality.  They share and actively collaborate with universities, partners and even competitors to create new IP. They believe there is space for all companies to grow, and competition is minimal if they continue to focus on their customer and evolve their solutions at a rapid pace. And they get beyond the war for talent by leveraging alternate talent sources such as freelancers, the gig society, crowd sourcing, partners and interns.

Aspect #4: Comfort with ambiguity is necessary as there is simply a lot of ambiguity during any transformation.  According to The Business Dictionary, the word transformation is defined as a process of profound and radical change that orients an organization in a new direction and takes it to an entirely different level of effectiveness.1  This magnitude of change requires people to let go of their comfortable way of doing things, have faith that the messy path to doing things differently will pan out, and unlearn things they knew to be true in the past.  Even though the path is ambiguous, apply new ways of working such as agile to quickly define, build and test solutions that can be adjusted along the road to getting to a final outcome.

Aspect #5: Having a growth outlook in the digital age means you are an explorer, have agility, adjust to change, thrive in diversity, and seek resources & answers.  I could go on.  It’s a great culmination of Aspects 1-4.  Using the preceding aspects of mindset with a growth outlook is what enables people and companies to find new solutions, products and ways of working, that are aligned with their customers and worthy of some rapid prototyping and testing.  The desire and ability to continuously grow, requires that you are also continuously transforming.  And at the rate of digital business and the exponential growth in technology, digital transformation is here to stay.

Embrace this digital mindset to stay on the path of digital tranformation: behaviors and attitudes that see possibility in the digital era; a belief in the power of technology; an abundance mentality; comfort with ambiguity; and a growth outlook.

Sources

Definition of Transformation http://www.businessdictionary.com/definition/transformation.html

About the Author:

Kerrie Hoffman is a serial entrepreneur and freelancer specializing in business growth and Digital business.  She is Co-founder and principal for Get Digital Velocity, and owner of a FocalPoint Business Coaching Practice.  As a freelancer, Kerrie is Lead Strategist for The Congruity Group and speaker at Industry venues.