How to gain maximum value from technology investments for your business?
The slow economy stemmed from the COVID-19 pandemic is forcing organizations to identify and cut all unnecessary costs. Unfortunately, technology investments also fall prey to these budget cuts. It happens when businesses invest in technology without adequate planning.
According to a survey, 29.2% of respondents holistically examine their technology usage while searching for efficiencies. It may mean canceling or delaying new projects and purchases or reducing or canceling maintenance and support contracts for existing investments.
Research by Accenture reveals that while 47% of the companies are building their future growth strategies on mobility and technology, considering inefficient technology as one of the top hindrances to their growth. It is clear that IT-led innovation is the need of the hour, and 82% of companies are investing specifically in technology for improved growth.
Simply put, now, it is crucial to improve the return on investment of resources, optimize costs, and select the right solution when making sourcing decisions.
Here, we share a few tips to help you gain full value from your technology investments.
Ways to optimize costs
Gartner reveals that optimizing costs is essential for businesses and is one of the best ways to control spending and attain cost reduction while maximizing business value.
Optimizing costs should take into account:
- Automating and digitizing business operations
- Simplifying and standardizing applications, platforms, processes, and services
- Obtaining the best terms and pricing for business purchases
While this means ensuring that technology investments generate the maximum possible value, it also means cutting costs and considering how each technology investment drives business value.
Some technology may be expensive, but it doesn’t mean that it isn’t providing value to the organization. Expensive technology may already be optimized because of the value it generates, while inexpensive technology may be unused and wasted. Therefore, it is important to make the right decisions regarding purchasing hardware, software licenses, or cloud services contracts.
Once you have identified and mitigated what you do not need and what you need, there are no more costs to reduce. It is time to look at how to optimize technology assets.
Ways to get the most out of your tech investments
Despite the cutbacks and search for savings, many organizations continue to invest in technology projects and accelerate their digital transformation initiatives. However, even with the economic slowdown coupled with pandemic-related uncertainties, organizations that have performed well during 2020 are looking to increase resilience by reducing risks and demanding shorter ROI periods on investments.
That said, the key to maximize ROI is preparation. It is essential to know that you’ve selected the right solution and are ready for implementation. Several surveys done in the past suggest that the software chosen is rarely the reason for any IT project’s failure. And a few leaders even agree with this, revealing a lack of investment in preparation, project management, and implementation. Even the simplest of IT systems require some amount of work to install and configure. So, the more complex your environment is, the more careful you will have to be.
Key factors to consider while developing a technology strategy to improve corporate performance are:
Investment profile: Your management team must identify your IT investment percentage (allocated to build significant capabilities) versus the foundational investment. Ideally, foundational investments should not be more than 40% of the total annual investments.
Organization focus: You must identify whether a significant portion of your internal resources aims to drive innovation or growth. Also, find out if you have the proper operating processes in place to drive these investments.
Tenure: You will have to figure out if your workforce has the right experience and skills to achieve the target.
Investment economics: Move over traditional measures and instead identify newer ways to evaluate your projects and investments.
A few technologies worth investing
Following are some of the technologies worth investing in the present business scenario:
- Artificial Intelligence (AI)
- Internet-of-Things (IoT)
- Self-driving technology
- Streaming media
Tips for getting maximum value from technology investments
To get maximum value from your technology investments, you should:
- Be prepared with clear objectives and outcomes. You must ensure that your vision aligns with that of the new technology vendor.
- Ensure that you have people, processes, and governance for leveraging the technology when deployed, reducing the time to both value and ROI.
- Identify and assess your data sources’ quality to develop appropriate metrics for accuracy and completeness of data and check for any improvements.
- Invest in the implementation and system or process integrations to make sure they are carried out successfully. If you are using any third-party service provider for the implementation, ensure that you hire a reliable and trained team like Fingent.
- Identify users and key stakeholders and invest in their time to maintain the system.
- To reap benefits early in the project and demonstrate the value of initial investments, take a phased approach. Phasing could be by business unit, geography, or environment depending on the organizational structure and business goals. This will ensure that the project is manageable.
- Provide both initial and ongoing training in phases to allow end-users to familiarize themselves with the features and functionalities they have learned about before undergoing further training. That said, make sure the new users are also appropriately trained.
- Ensure that third-party consultants have completed their vendor training or certification programs before allowing them to use your tools. Also, check if you are using the latest version of the tool. If needed, arrange for additional training.
Be smart with your tech investments
With technology and digital transformation becoming more pervasive across all industries, technology investment can make a huge difference in winning or losing a business. By focusing on the tips discussed in this article, companies can maximize value from their technology investments.
Technology wins only if it can appease users. A bad customer experience forces the customer to switch from vendor A to vendor B. Not only should you identify and invest in the right technology, but make an emotional connection to craft human experiences that drive customer satisfaction and differentiate you from your rivals.
Fingent helps you make a fortune out of tech investments by helping you leverage the latest technology trends. Our business technology consulting services focus on helping businesses tackle technology problems, attain business objectives, and derive value from tech and IT investments. Chat with an expert to learn more.
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The post-COVID-19 business scenario will not look the same across industries or countries. It will pose challenges and opportunities to leaders.
Tips for Business Leaders to Attain Success in the New Normal
While traits like empathy, authenticity, clarity, and agility remain crucial during this uncertainty, leaders face challenges to maintain a sense of connection and togetherness within their teams. However, as businesses are beginning to get back on track, leaders will have to leverage new insights and advancements to rebuild the workplace rather than returning to it as usual.
This article discusses five best practices that business leaders can follow and prepare their organization for the future.
1. Have a clear purpose
There is a big difference between a “factor” and a “must-have.” A company that has a unique affirmation of its identity embodies everything the company stands for. This purpose helps future-ready companies to attract people to join the organization, stay and thrive. Also, investors understand why it is valuable.
According to a survey, 82% of companies in the U.S said that organizational purpose is essential, but only half of these companies said their purpose drove impact. So, what can bridge the gap?
Leaders can set the purpose in motion and make it real for people. This can be achieved when employees identify and feel connected to their organization’s purpose. For example, Amazon leaves a chair vacant during meetings to represent the customer’s role in decisions. CVS Health stopped selling tobacco products to achieve the purpose of helping people to attain better health.
Research reveals that people who live their purpose at work are four times more likely to report better engagement levels than those who do not.
Simply put, purpose inspires commitment, reveals the untapped market potential, and even navigates uncertainty. So, companies must articulate what they stand for and use their purpose to connect employees and stakeholders in ways that justify their business choice.
2. Create a value agenda
An organization must create a value plan that helps convert its ambitions and targets into tangible elements such as business units, product lines, regions, and capabilities. This allows companies to articulate where value is created and set it apart to drive future success.
Organizations must use the value agenda to focus their efforts and enable their employees to understand what matters. If this is achieved, the results can be significant and hard to replicate.
For instance, Apple ensures it provides the best user experience. The company gives importance to not just the product design but also the product packaging. Apple has a dedicated packaging team to ensure users elicit the right emotional response while unboxing.
Having a clear value agenda will help a company devise better strategic priorities and become agile to shift resources as priorities change.
3. Distinct culture
Future-ready companies need to have a distinct culture that can help them distinguish themselves from others. Culture includes rituals, symbols, behaviors, and experiences that describe how an organization works.
For example, Amazon enforces its “two-pizza rule,” according to which every internal team should be small enough to be fed with two pizzas. This rule supports the company’s approach to meetings: no PowerPoint, shorter meetings, and start with silence to allow participants to go through the pre-meeting memo. These approaches may sound silly, but in reality, it enables the company to reach better decisions faster.
For successful companies, culture forms the backbone and fuels sustained excellence in performance over time. Studies show that companies with strong cultures are three times more likely to achieve higher total returns to shareholders than those without a healthy culture.
Leaders have to consider specific behaviors that employees at all levels adhere to create a robust performance culture.
4. Flatten structure
In recent years, the business environment has become more complex and interconnected. Many companies have adapted to these changes and created a more sophisticated matrix expecting it to solve market complexity. However, this is not how it should be.
Future-ready organizations must prepare themselves to become fitter, faster, flatter, and better at unlocking considerable value. The goal should not be to eliminate hierarchy but to flatten the organization, adopt the most uncomplicated profit and loss management structure, and reinforce business objectives with robust performance management and other mechanisms.
For example, Haier, a China-based company of appliances and electronics, adopted emergent and agile teams instead of the traditional hierarchy. The multinational company has no layers, no conventional bosses, and no middle management.
Another example to consider is Google. It follows a “non-zero-sum” management approach that emphasizes developing a communication line running in all directions rather than reporting relationships. It brings together cross-functional and professional skills while avoiding hierarchical mindsets. Such teams can act fast because they are flexible, are ready to learn from mistakes, and try new approaches.
In simple words, the future-ready organization must include models that are designed around people and activities. As technology advances, bosses will become coaches and enablers rather than micromanagers. When organizations set their priorities and ways of working, responsibilities, and transparent decisions, they can empower their frontline staff to make decisions.
5. Prioritize data-rich tech platforms
Data is of utmost importance, and future-ready companies need to take it seriously. For example, Netflix transformed from a small DVD-provider to a multifaceted global OTT content platform and media production company by leveraging insights from its user data through powerful algorithms.
So, future-ready companies need to understand that data can empower decisions, and the value agenda provides unexpected yet promising opportunities.
To get maximum benefits from the data, future-ready companies must create practical approaches to data governance, redesign processes in a modular fashion, and leverage cloud-based technology by dynamically reallocating their budgets. By utilizing the data effectively, companies can develop new products, services, and even LOBs.
There’s no denying that the COVID-19 pandemic has left many businesses in grief and economic dislocation. Business leaders must lead with empathy and compassion as they start to re-energize and revitalize their teams. The best leaders establish and reinforce behaviors that can support their organization during this crisis and after.
Contact us to know more about how Fingent’s leadership supports customers to ensure business continuity and enables employees to engage effectively during the current pandemic.
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Knowledge Representation Models in Artificial Intelligence
Knowledge representation plays a crucial role in artificial intelligence. It has to do with the ‘thinking’ of AI systems and contributes to its intelligent behavior. Knowledge Representation is a radical and new approach in AI that is changing the world. Let’s look into what it is and its applications.
Understanding Knowledge Representation and its Use
Knowledge Representation is a field of artificial intelligence that is concerned with presenting real-world information in a form that the computer can ‘understand’ and use to ‘solve’ real-life problems or ‘handle’ real-life tasks.
The ability of machines to think and act like humans such as understanding, interpreting and reasoning constitute knowledge representation. It is related to designing agents that can think and ensure that such thinking can constructively contribute to the agent’s behavior.
In simple words, knowledge representation allows machines to behave like humans by empowering an AI machine to learn from available information, experience or experts. However, it is important to choose the right type of knowledge representation if you want to ensure business success with AI.
Four Fundamental Types of Knowledge Representation
In artificial intelligence, knowledge can be represented in various ways depending on the structure of the knowledge or the perspective of the designer or even the type of internal structure used. An effective knowledge representation should be rich enough to include the knowledge required to solve the problem. It should be natural, compact and maintainable.
Related Reading: 6 Ways Artificial Intelligence Is Driving Decision Making
Here are the four fundamental types of knowledge representation techniques:
1. Logical Representation
Knowledge and logical reasoning play a huge role in artificial intelligence. However, you often require more than just general and powerful methods to ensure intelligent behavior. Formal logic is the most helpful tool in this area. It is a language with unambiguous representation guided by certain concrete rules. Knowledge representation relies heavily not so much on what logic is used but the method of logic used to understand or decode knowledge.
It allows designers to lay down certain vital communication rules to give and acquire information from agents with minimum errors in communication. Different rules of logic allow you to represent different things resulting in an efficient inference. Hence, the knowledge acquired by logical agents will be definite which means it will either be true or false.
Although working with logical representation is challenging, it forms the basis for programming languages and enables you to construct logical reasoning.
2. Semantic Network
A semantic network allows you to store knowledge in the form of a graphic network with nodes and arcs representing objects and their relationships. It could represent physical objects or concepts or even situations. A semantic network is generally used to represent data or reveal structure. It is also used to support conceptual editing and navigation.
A semantic network is simple and easy to implement and understand. It is more natural than logical representation. It allows you to categorize objects in various forms and then link those objects. It also has greater expressiveness than logic representation.
Related Reading: Understanding The Different Types Of Artificial Intelligence
3. Frame Representation
A frame is a collection of attributes and its associated values, which describes an entity in the real world. It is a record like structure consisting of slots and its values. Slots could be of varying sizes and types. These slots have names and values. Or they could have subfields named as facets. They allow you to put constraints on the frames.
There is no restraint or limit on the value of facets a slot could have, or the number of facets a slot could have or the number of slots a frame could have. Since a single frame is not very useful, building a frame system by collecting frames that are connected to each other will be more beneficial. It is flexible and can be used by various AI applications.
4. Production Rules
Production rule-based representation has many properties essential for knowledge representation. It consists of production rules, working memory, and recognize-act-cycle. It is also called condition-action rules. According to the current database, if the condition of a rule is true, the action associated with the rule is performed.
Although production rules lack precise semantics for the rules and are not always efficient, the rules lead to a higher degree of modularity. And it is the most expressive knowledge representation system.
Gain the Benefits of Knowledge Representation
Used properly, knowledge representation enables artificial intelligence systems to function with near-human intelligence, even handling tasks that require a huge amount of knowledge. The increasing use of natural language also makes it human-like in its responses. Making the right choice in the type of knowledge representation you must incorporate is crucial and will ensure that you get the best out of your artificial intelligence system. If you need help with this, we’re here. Please reach out to us.
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Most Common Mistakes To Avoid While Implementing IoT
There are many pressing concerns about the possibilities of IoT in businesses. The most common is probably the question, “Is my business too small to adopt IoT practices?” However, as per the available statistics, the global IoT market is expected to reach $1.7T by the end of 2019. It is surely not unnoticed that IoT implementation has helped businesses both big and small to drive growth and innovation.
Making key errors while implementing IoT can however cause the entire business system to halt. These issues can be those related to device management, data flow across the organization, various partnerships involved, and so on. Security, scalability, cost involved, and the complexity of the system are other key factors.
Let us walk through the most common mistakes made while adopting IoT.
1. Security Concerns Associated With Technology Implementation
More than 80% of the senior executives in industries across the globe suggest that IoT implementation is crucial for positive business outcomes. Since more and more devices are connected to the global network, the highly sensitive data and applications require access restrictions to avoid any malpractices. For instance, the security scope needs to be end-to-end to support connected devices.
An IoT implemented framework needs to be secure. The security concerns could be any of the following:
- An Insecure Web Interface
- Improper Authorization Techniques
- Privacy Issues
- Cloud Interface Insecurity
- Insecurity In The Mobile Interface
- Insecurity In-Network Services
- Software Or Firmware Issues
- Lack Of Physical Security
- Lack Of Transport Encryption
- Issues In the Security Configuration
Poorly secured IoT devices and software make the IoT prone to cyber-attacks. End-to-end security is thus crucial for any IoT deployment. For instance, consider an Internet-connected car wash. Such devices use a default password. In this case, when a security concern arises, it also leads to a safety concern.
The solution here is an external security audit of the implemented IoT device. This builds confidence to perform new IoT implementations as well.
2. Not Being Aware Of The Critical Data Flow Forecasts
Not being able to forecast data volume can be one of the major mistakes in IoT implementation of devices and applications. According to EMC Research, the rate at which data is growing is exponential. It states that the volume of this data would be equivalent to 6.6 stacks of 128gb i-Pads which are fully-loaded, and will stretch from the Earth to the Moon!
Moreover, many businesses think that the more data they extract, the better it is for their business. Many a time, this misconception can lead to storage swelling of both structured as well as unstructured data.
The solution is to ensure the proper working of the right IoT big data business strategy with a clear forecast on different factors. The factors could be the amount of network traffic, storage requirements, and so on.
In case of an already existing functional data system, edge computing can be implemented to ensure intelligent pre-processing of data.
3. Cost Factors Involved In Decision-Making Of IoT Implementation
According to recent statistics, cost savings have turned out to be the major IoT adoption criteria for over 54% of enterprises. Taking into account just the cost factor while deciding to implement IoT might turn out to be another major mistake. Various factors affect the cost of implementing IoT projects. Starting from the number of connections to the device, the type of technology used, to the type and features of the application to be loaded, there are many more.
Hardware, let us say, is a major factor that affects the cost of IoT implementation. The cost of the IoT application is directly proportional to the number of devices used in the connection. Likewise, Infrastructure is another major factor that influences the cost of IoT projects. The infrastructure used could be wireless, middleware, or cloud-based.
4. Lack Of Proper Plans For Device Updates And Replacements
A proper IoT device management is critical to ensure core compatibility of the IoT platform. Device reliability is the most important requirements to ensure an enterprise-ready platform. Device management operations include network, power states, device geolocation, and so on.
Large volumes of data collection, transfer, storage, and utilization can result in malfunctioning of connected devices in the IoT ecosystem. Implementing an IoT platform enhances the integrity of connected devices.
The solution to the pressing concern of planning can be solved through regular monitoring, diagnostics, software updates, and maintenance. Performing frequent OTA (Over-The-Air) updates helps the IoT platform in monitoring and maintaining the device software, fixing bugs, managing firmware, and in customizing the connected devices. This ensures in-depth device protection.
Related Reading: Check out more about IoT – Where and Why should you invest!
In addition to the above-mentioned common mistakes, the following are a few other factors that can lead to IoT errors:
- Lack of setting a realistic timeline for IoT implementation – Achieving a realistic idea on the timeline of IoT implementation is necessary for a positive outcome.
- No Tolerance For Possible Failures – Implementing IoT without having a clear picture of your IoT project can be a big mistake. Leave room for scaling up new ideas.
- Relying Only On Existing Charts – IoT implementation requires dedicated decision-makers instead of relying only on existing organizational charts and decisions.
- Lack Of Technical Expertise – When every part of the IoT project is either reinvented or being contracted out, you are unsure of the third-party development and deployment teams. Technical expertise is the key to a successful IoT project.
Are you looking for an efficient technology partner to help you adopt IoT the best possible way? Get in touch with our experts today for a streamlined and error-free IoT implementation for your business.
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What Is Robotic Process Automation?
Robotic Process Automation is the process of applying automation to perform tedious business tasks of the workforce, such as data manipulation, response triggering, transaction processing, and other redundant tasks. According to a recent study by Snaplogic, 90% of the workforce are burdened with redundant tasks. This not only reduces their productivity but also consumes significant amounts of time with which they could perform higher-value tasks.
The Role Of RPA: Features That Enhance Business Process
Once your enterprise has decided to implement RPA, it is time for you to choose the right robotic process automation solution.
Traditional RPA software bots are known to handle only a specific task at a given time. When it comes to addressing high volumes, there is a necessity to clone these bots and run them simultaneously. RPA providers usually charge users for each concurrent process. This can become a costly affair for enterprises, especially during volume spikes. Thus, undue extra costs are a key factor to consider while choosing an RPA solution for your business.
RPA works as a virtual assistant and can handle complex processes starting from performing complicated calculations, data capturing to maintaining records.
In addition to prioritized work queues, user-friendly features, data analytics, and non-disruptive nature, the following are crucial features that enhance business processes:
- Non-disruptive nature: An enterprise can easily implement RPA into their workflows without having to disrupt or change the existing structure or risks.
- Data analytics: Gathering critical data from multiple sources, analyzing and storing the data, and creating reports have brought digital transformation to businesses with RPA. This enables accurate forecasts of sales data along with other Key Performance Indicators (KPIs).
- Prioritization of Internal Work Queues: Every RPA software consists of internal work queues. These work queues are used to extract data derived from various transactions for analysis. The extracted data is then stored on a cloud server and made available for access by the bots.
- User-friendliness: Employees can operate on the robots without any extra RPA knowledge. They only need to learn how the systems work.
- Scalability: With RPA, it is possible to upscale and downscale various robotic operations.
Types Of Robotic Process Automation Tools
RPA enhances robotic performance in different ways. The three major categories include Working Robots that are commonly used for Data Collection and Project Planning. Monitoring Robots detect faults and breakdowns, whereas Screen Scraping Robots provide data migration tasks for enterprises.
Robotic Process Automation tools come in varying sizes and shapes. Analyzing your business objectives is the most critical factor before deciding to choose a specific RPA tool for your business. A few of the major RPA tools are as follows:
- Attended Or Robotic Desktop Automation Tools
This type of automation always starts with the user via the user’s desktop. The user first launches the RPA code to perform required operations rather than waiting for the workforce to perform.
- Unattended Automation Tools
This type of automation completes business processes in the background and is used mainly to perform back-end tasks.
- Hybrid Automation Tools
This type of automation combines both attended and unattended automation tools to perform start to end operations.
How To Choose The Right RPA For Your Business
A clear set of objectives form the primary goal before opting a specific RPA tool for your business. The following are the key factors you need to consider before selecting an RPA tool for your business:
1. Easy-to-use Interface
Simple user experience is a major criterion for choosing the right RPA tool for your business processes. A simple user interface will ensure all employees work efficiently.
2. Proper Deployment
An RPA tool that can be quickly deployed with the existing technology stack is what is required.
Replacing tedious tasks performed by the human workforce is largely replaced by the bots. This process of automation saves costs. Employees can focus on their core tasks and spend time and effort on their skills rather than performing redundant and tedious tasks with the help of RPA tools. Purchasing an RPA software tool involves associated costs, such as cost of individual licenses, cost of the software, and other overheads.
Implementing an effective RPA tool enhances the business processes and leads to the growth of the enterprise. This growth is accompanied by hiring more resources. Thus an RPA tool can enhance the scalability of a business in the long run.
Data analytics, compliance, and financial transactions require a highly secure environment. A great RPA software tool ensures a secure solution for all business processes and updates as well.
The architecture of the RPA depends on where you plan on employing your RPA tool. The deployment and maintenance of an RPA tool depend on factors such as layered design, component reusability, robust delivery, popular language support system, easy accessibility, and so on.
Choosing an RPA suite that consists of solid inbuilt features is critical. Flexibility, scope, availability of wizards and GUIs, other extendable commands and supports are some of the features to consider.
8. Exception Handling Support
A robust RPA solution can detect errors during automation and automatically resolve without human assistance. In other cases where human intervention is required, an effective RPA tool must be able to send error messages.
9. Extended Support
Different vendors offer different support. A dedicated support team is necessary to ensure strong maintenance and support.
To make the best decision on choosing the right RPA solution for your business and access the full potential of RPA tools, get in touch with our experts today!
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How Face Recognition Apps Are Defining The Future Of Competitive Industries?
There has been a lot of talk about Face Recognition Apps recently. It has received accolades for its use in enhancing security as well as flak over privacy concerns. Speculations aside, there is no denying that face recognition software has revolutionized the way we perceive technology. It is no longer a faraway concept as it finds a place in our pockets through mobile technology.
In this blog, we will look at the technology behind face recognition software, what makes it tick and how it has found application across industries.
What Is A Face Recognition App?
Face recognition is a biometric technology that creates a face print of an individual by mapping out his or her facial features mathematically. This face print is stored and used to compare a digital image of a person verifying their identity.
This mapping is done by identifying 80 nodal points on a human face. These nodal points are used to measure different variables of the face. The width of the forehead, the length of the nose, the shape of the eyes – these measurements are captured on a digital image of the person’s face and stored as a face print. Deep learning algorithms are then used to identify a person in comparison with the face print.
This technology has been used in various ways from automatic photo tagging by apps like Facebook for authentication and identification by Apple’s iPhone X. The way in which Apple has used this technology is interesting. Face ID technology, which allows users to unlock their phones using the stored face print, is designed with 3-D modeling. The software compares over 30,000 variables to fine-tune recognition capabilities. This face print or Face ID can be used as authentication for purchases done with Apple Pay and other Apple stores. Amazon Rekognition, Google Cloud Vision API and other image analysis APIs can be now used to add facial recognition capabilities to other applications.
The inclusion of technologies like augmented reality, mixed reality and more have made face recognition software a powerful force. At Fingent, we developed a mixed reality application using Microsoft Hololens. This application helps in the identification of a person and also links the face print to the biodata of the person. It will also be able to capture images and compute similarities between the captured image and all the other images in a secure database.
The Role of Face Recognition Apps in Safety and Protection
According to a Javelin Strategy and Research study, identity fraud hit a record high with 15.4 million U.S. Victims in 2016 and an increase of 16 percent from previous years. In a connected world where such vulnerabilities exist, face recognition software is proving to be an invaluable asset. The software is helping law enforcement and corporate to put a name to the faces of criminals who have been playing havoc with stolen identities. Some applications of face recognition software in ensuring safety are:
- Identity validation at ATMs and prevention of identity theft with photo IDs.
- Face recognition surveillance systems in schools to protect students from expelled students or parents who have been flagged as dangerous.
- Equipping law enforcement personnel with identification of criminals and contextual data to warn them of dangerous persons before they approach offenders.
- Automated facial recognition (known as AFR) helps in forensic investigations by identifying individuals on surveillance cameras and videos, as well as in recognition of dead/unconscious individuals at crime scenes.
- Protecting retailers from shoplifters by warning security personnel of known criminals with a record. It also helps them avoid potential violence in the store by warning them when dangerous criminals or disgruntled former employees enter.
How Various Industries Can Benefit from Face Recognition Apps
Apart from ensuring safety and prevention of identity theft, face recognition software has many commercial applications as well. Many organizations across industries are recognizing the vast potential of face recognition apps and exploring different ways to capitalize on its features. Let us look at the Healthcare and Retail industries as an example.
Healthcare is constantly making giant strides with technology and facial recognition is contributing in unexpected ways. Researchers from the National Human Genome Research Institute (NHGRI) in the United States have come up with a face recognition system, which can diagnose a rare genetic disease called DiGeorge syndrome. People with this syndrome exhibit particular facial anomalies, which give them characteristic expressions that can be detected by facial recognition software. Despite the many challenges associated with effective detection, the team has developed software with an accuracy of 96.6%.
Another example of face detection software being used in healthcare is the facial recognition app developed by Listerine. This app enables a blind person to detect when somebody is smiling at them, by setting off vibrations when the face recognition app detects a smile. This helps the blind respond better in social situations, thus contributing to their quality of life.
Speaking about the further possibilities that technology can bring to healthcare, Christoffer Nellaker, of the Medical Research Foundation’s Functional Genomics Unit at Oxford says: “A doctor should in the future, anywhere in the world, be able to take a smartphone picture of a patient and run the computer analysis to quickly find out which genetic disorder the person might have”. This is already coming true with the help of face recognition.
Related Reading: Check out how modern healthcare is revolutionizing with automation.
Retailers have been using augmented reality to improve the customer experience for a while now. The retail giant Sephora has gone one step further and added a live 3D facial recognition feature to its Virtual Artist application. This enables a more accurate facial tracking and rendering, allowing users to virtually try on Sephora’s various products while they are moving in real time. Parham Aarabi, CEO of ModiFace, which is the developer of this function for Sephora says: “We believe the ability to see yourself with products can impact sales online … and thus the integration on Sephora will, based on our expectation, result in increased conversions and user engagement.” The goal with this move is to enable customers to try on their products in a fun and more interactive way. The accuracy enabled by this technology will go a long way in enhancing the customer’s experience and boosting sales.
By using face recognition software in making educated guesses about a potential customer’s gender, age, etc., big retail giants are optimizing their ad campaigns to specific target audiences. Such advertisements are more effective as they help deliver a targeted message that has a powerful effect on consumers. An example is the “Because I’m a Girl” campaign rolled out by children’s charity Plan the UK. The charity created bus billboards, which would scan the viewer’s face and display an ad depending on the viewer’s gender. This was done to highlight the plight of women who are denied rights based on their sex. Brands like Virgin Mobile, Nike and others have also used face recognition software to create a more immersive ad experience for their customers.
Implementing Face Recognition Technology
Face recognition software is closer to home than we think, and it is apt to look at ways in which your company can capitalize on its capabilities. Talk to us and let’s discuss how.
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In today’s age of hyper-competition, businesses need to focus their systems on the customer. A critical area of focus is business software. Much of business software hitherto focused on internal efficiency. However, competitive pressure mandate a realign, with the focus on the customer, and specifically customer support.
Businesses Need to Roll Out Mobile Solutions
Nowadays, the basic support for customer commerce is through customer-facing mobile apps. About 80% of shoppers use their mobile phones for product reviews, to compare prices, and find store locations. A good chunk of these customers completes the purchase process online as well. About 54% of Millennials and 49% of Non-Millennials prefer shopping online. Businesses need to roll out customer-facing mobile apps and responsive websites, to facilitate e-commerce and other customer interactions.
The Rise of Virtual Reality (VR) and Augmented Reality (AR)
E-commerce websites offer a world of convenience to the customer. It brings the shopping experience anywhere, from home to office, and from the boardroom to the bathroom. However, such convenience comes without the “touch-and-feel” experience of physical stores. Virtual Reality (VR) and Augmented Reality (VTR) technologies bridge the shortcoming and offer the best of both worlds.
Cases of retailers supporting customer commerce through VR and AR-based software abound.
- Swedish furniture giant IKEA’s VR app allows customers to view different kitchen decors. Customers can walk around IKEA kitchens virtually, using a VR headset and app.
- Sephora’s app allows users to take selfies and apply the brand’s cosmetic products to their images. Customers can get conclusive proof of whether a shade of lipstick will look good on them, rather than debate endlessly or speculate.
Artificial Intelligence Systems Facilitate Personalization
Personalization is the order of the day.
Most businesses already use Google Analytics tool to segment customers. They target segmented groups with different discounts and deals. Marketers also use various other predictive analytics tools to analyze historical data. Advanced solutions deliver accurate predictions about demand. Enterprises could focus their efforts on products having the greatest potential for profits.
However, such a superficial approach will undergo a sea-change by 2018. More-and-more shoppers now leverage Artificial Intelligence, to source products, bargain prices, and pick up products. As a case in point, connected smart fridges detect when the stock of milk becomes low, and trigger an automatic reorder with a linked e-commerce store. Enterprises who can roll out business software to align with such smart systems, and leverage “A-Commerce” or Artificial Intelligence-based commerce, stands to gain big.
Adaptive Design Comes Centrestage
Customers’ needs are never set in stone. Smart businesses keep track of changing customer preferences and the underlying influencers of such change. Business software which connects with potential clients on a personal level, in real-time, is central to such efforts.
Use-cases abound for businesses leveraging technology, to adapting its products and services to serve real-time customer needs.
- Curve, a credit card company allows customers to switch cards even after completing the purchase. An executive purchasing a computer for the company with his personal card, to take advantage of a bargain, could later change the billing to the company card, after getting authorization.
- KLM’s new clip, attached to the traveler’s bag, offers real-time directions, suggestions, and alternatives. For instance, when a user is stuck in a long line at the Eiffel Tower, the clip suggests the nearby hot-air balloon at Parc André Citroën. The clip also directs users to specific in-house services, stealing customers away from the competition.
- Tesla recently increased the range of its electric vehicles for customers struck in places affected by Hurricane Irma. Range limitations in Tesla’s vehicles meant owners couldn’t evacuate the area.
Virtual Companions Become Mainstream
Most smart businesses now empower their workforce, especially support agents with virtual assistants. Such virtual assistants automate daily tasks in ways CRM can never enable.
Virtual assistants offer agents deep real-time insights on information hidden inside the company databases and other systems. Locating such information manually is a time-consuming task, in the absence of clear-cut information on where such information resides. The obvious benefit is a speedier resolution of consumer issues, leading to improved customer satisfaction and accelerated sales cycles.
Virtual assistants also take the shape of chatbots, replacing the manual assistant altogether. Technology has evolved considerably on this front, and businesses are co-opting it in a big way. In 2018, even the most basic bots will become more interactive than Siri and Alexia of today.
AI infused bots learn from users, to offer highly relevant insight and suggestions. It could open the database and pry a solution even before a manual agent has the chance to comprehend the question. Further, the technology to make bots understand emotional intelligence has arrived. Such Emotional Intelligence capable bots would know how exactly to respond to a frustrated customer. Going forward, bots would handle most normal queries, leaving human agents only with long-tail and complicated queries.
Social Media Rises in Importance
Social media caught on big-time, with estimates suggesting a 394% increase in social media use in recent years. The widespread popularity is mainly on account of the transparency, the social media delivers. The best businesses leverage such transparency to further their business model.
Traditionally, businesses had complete control over their products and services. The business model essentially boiled down to a “take-it-or-leave-it” approach. The transparency infused by social media has changed the power equations. Customers now have unprecedented choice and ability to gather real feedback from real users of any product or service. If something goes wrong, rest assured everyone will come to know about it.
Smart companies cope with such change by giving more power to its customers. They listen to the customer eagerly and align their business software to take feedback. This ensures that the business and the customer work together, for mutual benefit. Businesses roll out more collaborative systems and link it to their key product development and management channels.
Enterprises need not always go in search of new technologies. What is important is the way in which any technology, new or old is applied. Any business today needs to adapt and change its services and products to meet the changing needs of the customers. Customer focused business software is a major enabler in this direction.
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Training is a double-edged sword. While training is indispensable to eliminate the skill gap brought about by the introduction of new technologies, much of the training that takes place adds no value and is water down the drain. With the business environment getting tough, and top management seeking accountability for every dollar spend, business managers are now taking a long and hard look at their training strategies.
With conventional training methods failing to deliver the desired value, need to do something different becoming obvious, and among the various options, competency based learning is gaining traction.
What is Competency-Based Learning?
Competency Based Training is basically learning by doing. The trainee is given an opportunity to implement the acquired skills or knowledge, to confirm the training or the dissemination of knowledge was indeed effective. The evaluators prepare a set of criteria, to evaluate the ability, skills, and knowledge of the trainee, based on the observed evidence.
The proof of the pudding being the eating, if the trainee can perform the expected workplace role to satisfaction, training was indeed effective. Trainees are not expected to do better than others but simply do the task well enough to pass muster.
Does Competency Based Training Actually Work?
The very reason competency based training has gained traction is because it works. Empirical evidence reveals the application of competency based training being instrumental in the transformation of many employees, enabling them to perform individual tasks better, manage a range of different tasks, respond to contingencies effectively, seize the moment, and be more proactive.
Competency-based training measures the actual ability imparted by the training process, rather than the time spent on training. It delivers a fundamental shift in approach, by conducting training at the trainee’s pace rather than at the trainer’s pace. The training is complete only when the trainee demonstrates competency to do the job, regardless of the time taken.
Competency based training scores high on flexibility. Understanding the exact extent to which a person has the required skills, through life experiences, formal qualifications, natural talent, and other sources, makes it possible to customize the training program, without the individual having to waste time with others in a conventional training session, being thought what he already knows, to understand what he does not know. The positive impact such customization has on employee productivity and organizational efficiency is worth its weight in gold. The caveat, however, is a strong mechanism to measure skills accurately.
Competency based training puts the spotlight on defining the competencies, or the ROI. By making evaluation integral to the process, there is strict accountability and a clear evaluation of the extent to which training delivered the goods. The process of evaluation also gives accurate feedback on the extent of the gap that remains, and the additional skill-sets the trainee requires, to do the job satisfactorily.
Competency based training caters to the immediate requirements very well, so essential for today’s enterprise, where training aimed at long term goals are becoming increasingly irrelevant due to employee turnover and short shelf life of new technologies.
What about the Challenges?
Competency-based learning allows learners to attain mastery of each competency or skill at their own pace. A big practical concern such an approach raises is the severe time pressure faced by enterprises. Competency-based learning is, in essence, a sort of role-playing. Neither do today’s enterprises have the luxury of giving their workforce unlimited time to gain the required competency and nor can they afford to risk entrusting critical business processes to a potentially unprepared trainee, to see if he or she passes muster. The solution is a robust technology solution which makes sure the training takes place side-by-side with the job seamlessly, without being disruptive in nature.
Another often heard criticism regarding competency-based training is its ignoring social learning. Again, technology is the answer. A strong technology backbone, where the trainee is exposed to a collaborative learning atmosphere, and empowered with competency-based learning tools ensure a more engaged learning atmosphere, complete with open communication and full transparency among trainees, trainees, and the wider ecosystem.
Need for a Technological Backbone
Competency based training requires a strong technical backbone to ensure it works seamlessly, without being disruptive in nature. Technological solutions can be put to effective use to identify gaps during the actual course of work, measure the competency levels, and design appropriate training schedules. A good technology solution enables all these without having to waste time drawing up an elaborate exercise for it.
An effective technological solution also offers the following advantages:
- Automates the key tasks, sparing HR or other managers from taking the trouble to do so manually.
- Ensures the skill evaluation and gap identification exercise is carried out on a continuous basis, always updated to reflect the real-time situation, rather than as a one-time exercise which only reflects the situation at one point in time, and would become soon obsolete in a fast-paced world.
- Offers a unified repository of all training materials and resources, assigned to trainees on a need basis.
- Facilitates a collaborative learning atmosphere, offering a unified interface to draw in experts and other stakeholders to the training process.
- Facilitates record keeping, making it easy to track the progress of each employee, and draw the most relevant training solution, customized to individual requirements.
Up-Skill, a competency-based training platform offers the right mix of advanced technology, quality content, and expertise, empowering businesses to impart highly relevant and effective competency based training. The framework uses robust technology, comes with quality assurance, and encourages the creation of innovative solutions. Up-Skill’s advanced mobile app also ensures employees have the flexibility of accessing content and training material anywhere and at any time, catering to the needs of today’s workforce who require content anywhere, anytime, through the device of their choice.
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Last spring, we found ourselves working with a global media giant, to understand why their new high tech enterprise information sharing IT system was not being used by employees. As we plowed through the usual rigors of analyzing feedback from front-line staff, department managers and BU heads, we discovered something puzzling. While the new state-of-the-art system was hardly being used by anybody, few departments and teams used alternate custom-built IT systems to automate their processes. Most of these custom-built systems were rudimentary and offered poor user experience, and yet, every team member had adopted and used their system every day! Digging deeper, we discovered something even more surprising – The development and deployment of these systems were managed by the Line Manager (s) of these departments, who had little to no knowledge of IT or Software Development!
Why did an expensive, cutting-edge digital information system fail miserably, where a less sophisticated, custom built software succeeded with aplomb? How did non-technical line managers succeed in deploying technology effectively, where senior IT specialists failed?
Sure, deploying a new, large, complex, and organization-wide system across different locations is fraught with enormous technical challenges, but the real answer to these questions lies elsewhere.
The IT department, was attempting to solve a technology problem. However, none of the users had a technology problem. They had business problems.
Problems about information availability, sharing and communication in the context of how they got work done. Divisional, middle and operational managers, i.e. the Line Manager was in a much better position to understand these problems, since he knows the people in his teams and how they get work done. Direct involvement of the Line Manager enabled the building of IT tools which solved business problems that his/her teams faced.
In hindsight, the centralized top-down approach of IT system deployment was a mistake. The IT department never stood a chance.
Understanding the processes, practices, people and nuances of every team in a 6000 person global organization was an unrealistic expectation, especially under a tight budget and timeline. A decentralized approach to technology development and deployment, where the Line Manager was empowered to take technology decisions for his or her team, would have yielded better results.
Decentralization, as a management concept, has been around for a while. William B. Given Jr.’s book Bottom-Up Management, 1949 was probably the first to talk about Decentralization, while Drucker’s works over the last 50 years have often made the case for giving front-line managers greater control. However, it is only in the last decade that we saw an increased devolution of formerly centralized responsibilities (like human resource management, risk management, and strategic planning) to the Line Manager.
In this context, the decentralization of IT decisions is a natural step forward. Looking at our own portfolio of projects at Fingent, we see a steady increase in Line Managers successfully creating, customizing and deploying technology solutions for their departments. I believe that there are three key reasons why the Line Manager is successful in independently managing core information technology needs of his/her teams:
- Line Managers, especially those who are hands-on, are able to derive a good understanding of information architecture requirements
- A Line Manager understands of how the team gets work done, and
- A Line Manager’s ability to lead and manage changes to the ways of working.
The right information, at the right time
In relatively flat, multi-functional organizations, workers at every level have decision-making responsibilities. For such a knowledge worker, the ability to assimilate, interpret, arrange, sift and process relevant information is critical for the successful execution of day to day tasks.
Take the case of the failed digital-information IT system; asked to identify the single most important cause of failure, users across departments answered that the information necessary for work was either unavailable in the system, or was not available at the right time or in the right format. Each of the smaller systems that they were using daily was tailored to meet the specific needs of the team, providing different roles in these teams with the information they required to operate efficiently and effectively. Information was shared in the context of the tasks and stage of work, ensuring that it was available to the right person at the right time. These systems thus organized and structured information in a manner best suited to the team’s objectives. Or in other words, they had good information architectures.
Different departments/teams adding value to the organization in different ways need radically different information architectures. Information required for software developers to execute their day to day tasks is usually different from information necessary for a hardware engineer, HR personnel or Sales personnel. The IT department, which led the deployment of the failed solution, tried to create a system of compromises, and in doing so, compromised the critical needs of almost every department. This flawed approach resulted in a significant wastage of money and time.
A good information architecture secures that the right information is available to users; enabling a good technology system to use this information architecture for delivering the right information to the employee at the right time.Creating a good information architecture requires: the allocation of the right resources, interfacing with supplier and customer teams ( internal or external), a good understanding of current and desired processes, and a good understanding of the strategic and tactical objectives of the department. The Line Manager for the team/department is in the best position to take ownership of this activity and to use his resources to drive the creation of a good information architecture for his team or department.
There is one specific aspect of the information architecture where the Manager must be hands-on; performance measurement. Early measurement systems were top down, with KPIs being set by Senior Executives cascading down to the teams. However, with the greater empowerment of teams, we now see teams, designing their own measurement systems, in line with corporate strategy and measurement systems, to gauge own progress. The manager of a team is often responsible for the KPIs, its methodology and also the measurement. He should determine the level of access that different roles in his team, have to these measures.
Providing the right information, to the right person at the right time often provides the base for realizing the value added by technology. This “right information” is realized using the Information Architecture used by a team. Technology can then be deployed to use this Information Architecture to deliver information to employees in the context of their day to day work. The Line manager is in the best position to drive the creation of the information architecture for his team, while securing that it is aligned with organizational strategic goals and the team’s tactical objectives.
Processes and Practice: A Line Manager knows the difference between theory and application
In addition to a good information architecture, technology must also be aligned to systems used by the department, to add value to the organization. These systems are deployed via processes, and these days almost all self-respecting departments and teams of knowledge workers have documented processes. Whether the documented process meets practice is another story entirely. In the case of knowledge work, especially work that requires moderate to high degree of autonomous and creative thinking, tacit knowledge and improvisation trumps documented processes in practice.
When automating the change management system for the pharma enterprise, we discovered that different project coordinators had different approaches, planning, reporting, risk management and interdepartmental cooperation, which often resulted in significant deviations from the documented processes. For such a department to realize the benefits of automation, documented processes alone are insufficient. It is vital to consider the entire system as practiced and applied by the users, and in doing so, prioritizing the creation of tools to automate the desirable aspects of the system. It is the promise of predictability and stability in the way things get done using a system that often determines the effectiveness of deploying the software application. The Line Manager of the Department has a good view of the overall picture, people and the operational details; all of which are critical inputs to good decisions about balancing process and practice to achieve a stable system.
In the case of the pharma company, the Line/Department Manager was able to obtain the necessary strategic, operational and tactical perspective to determine specific processes and practices which were important to automate. Only he had sufficient authority and responsibility to ratify and take responsibility for these decisions. The IT department, or a 3rd party consultant, or even most people in his team would not be able to provide the unique perspective necessary to take these decisions.
The software solution we deployed for this department not only provides the benefits of automation, but also helps the team identify process deviations, enabling good decisions about the acceptance and mitigation of these deviations in day to day operations.
Often, the development of new tools and technologies is a trigger for teams to introspect and overhaul their existing systems. One of our clients, a property acquisition department at a national property management firm, re-architected their processes to take advantage of the benefits that a custom-built software application could provide. Their old system was built around the tools of pen-paper and a commodity desktop solution available then. During our early stages of pre-development analysis discussions, they realized that a custom software application, could free the department from the constraints of the commodity software, and open the doors to add value in new and innovative ways. Through mobile devices, real-time updates, and improved reporting, they could realize benefits that were not accessible to them before. They reinvented their property acquisition processes, providing significantly greater value and increasing the department’s strategic value to the organization. Such successful change was possible because the Line Manager was able to allocate a good team to work with the core process changes and technology upgrade, while he also worked with his peers and governance board, to plan and manage the delivery of business benefits.
Providing change leadership: Who better than the Line Manager?
IT deployment often makes some previously subjective measures objective and visible to all. Employees may be nervous to reveal more information than they used to do before. Then there is inertia, the reluctance to shift from comfortable routines and practices to a different way of working.
Supporting the team to see the change brought about by technology deployment is a leadership challenge. The Line Manager is in the best position to take up this challenge.
Leading such a change requires the active, consistent and continuous engagement of all employees who will ultimately be impacted by the change. It requires the creation of trust, so issues and concerns can be discussed and evaluated freely, together with the perceptions of value and benefits of the new system. This is an undertaking that requires significant effort, often at an interpersonal level. The Line Manager is the ideal candidate to lead such an effort. As organizations become flatter, the manager is a coach and a mentor to the individuals in his/her team. Alongside tactical directives, a Line Manager can use one-to-one meetings, coffee machine conversations and other informal discussions to evangelize the need for the new system and reinforce the benefits: a better work profile, reduced workload, skill upgrades and much more.
Leading such an effort also means assembling the right people, from the very start of the technology development initiative. These are people with the right skill set, organizational credibility and influence. Assembling such a team, and providing them with purpose, while leveraging their strengths and abilities at the right time can make a big difference to the progress and the success of a technology deployment project. Some team members may be good with early phase visioning, while others may be simulated by the challenges of training and change management. Choosing the right people for the right task, and giving them the ownership of creating and deploying the new system can increase interest levels in the entire team. This also leads to greater participation, and mitigating resistance during deployment. The Line Manager knows the strengths and weaknesses, the goals and aspirations of the individuals in his team. This enables him or her to make good decisions about mobilizing the right people for the project.
Leading this change, requires the management of day to day operations, while resources are devoted to the deployment of the new system, and while the department migrates from the old way of working to the new system. The Line Manager can secure minimal impact on ongoing operations, by allocating the necessary time (and backups) for those involved. And also providing the necessary time and support for the entire team to learn and use the new system. He can use his resources and forums to identify potential deployment blockers and mitigate such risks early. For example, staff meetings provide good opportunities to build cohesion and agreement about the new system and the deployment plan. It is also an effective way to source ideas and motivate volunteers for beta testing.
The choice of tools to execute a task requires combination of strategic, operational and tactical knowledge to make informed choices. The IT department in an organization, which services many lines, sections and departments, cannot be expected to have such an in-depth understanding.
The Line Manager is best positioned to have such an intimate understanding of the business and its operations. The Line Manager understands the formal and the informal processes, which gets the work done within his team. He/She knows the measures and indicators on his department’s scorecard, the data required for these and the processes which define these. He/She knows and often owns the processes that detail how his team interacts with other teams, within and outside the organization. The Line Manager understands a team’s suppliers and customers. And most importantly, the Line Manager understands the team today – the people who work for him today, their capability, their skillset and he/she understands the team required for business tomorrow – the capabilities and skill set required to keep up with a changing business environment. From an organizational perspective, giving ownership of technology to the people who will use it, empowers them with greater control and responsibility towards the outcomes expected from them.