All that you need to know about React Developer Tools
React is an incredible framework for frontend development. It also facilitates mobile app development for multiple platforms. React was a game-changer for mobile app development services across the world, and developers were thrilled when Facebook announced its launch. This post explores the features of React developer tools.
If you are into React development, you must have tried the official chrome React developer tools. This React devtools extension lets you debug your components and is available even as a standalone application. React developer tools help us smoothly create interactive UIs and React is able to reconcile changes to the DOM in a performant way.
The React Developer tool is undergoing constant development with new features added to it regularly. It is an essential instrument you can use to inspect a React application. This article lists out the features of React Developer Tools that you might like to try out and also discusses the best IDE for React.
Read more: React Native App Development – React Native Or Flutter – The Better Choice For Mobile App Development
Inspect and Debug
It is possible to use breakpoints, step-through, and logging to debug a React app. But it can become difficult especially if you have to debug an application that you haven’t seen before. By installing React developer tools, you can overcome some of these challenges.
Installing React Developer Tools
You can install React developer tools on the browser you are using to run the application. One of which is the chrome React developer tools extension. It is available in the appropriate extension store. Once it is installed, either as a browser developer tool or as a standalone application, two new tabs will become available: Components and Profiler.
The Components tab allows you to see the root React components that were rendered on the page and the subcomponents that they rendered. You can inspect and edit its current props and state in the panel by selecting one of the components in the tree. It allows you to inspect the selected component, the component that created it, and the component that created the second component and so on.
While inspecting a React element, switching over to the React tab will automatically select that element in the React tree.
Read more: Web Development Stacks – Top 6 Tech Stacks That Reign Software Development in 2020
Best IDE for React
A good IDE for React is a must to get started with the React ecosystem. Selecting the best IDE for React from among the many that are available out there can be a daunting task. This section will help you make a choice from both the free as well as the paid IDEs.
1. VS Code
VS Code is a Microsoft product and is available for free under open-source MIT license. You can download and set-up VS Code on Mac, Debian, Windows, Ubuntu, Red Hat, SUSE, and Fedora. It can be used for various programming needs. Being the most used free IDE, it is loaded with many useful features.
2. Reactide IDE
Reactide is comparatively new but is gaining popularity among the community of React web app developers. It focuses on web apps development. It is entirely dedicated to React-based application development. It is a one-click setup that installs and runs a custom browser simulator. It spares you from switching between code files and the browser to check the changes made. It is a cross-platform, open-source, free tool.
Atom is among the most popular open source text editors for modern programming. Built by GitHub, Atom comes with Git control and hence fits seamlessly in the GitHub ecosystem. It is a desktop-based application that is used for building apps using web technologies.
4. Rekit studio
Rekit studio is focused specifically for developing apps using React. It works both as an IDE and as a toolkit that can be used for developing scalable web apps using React Router, React, and Redux. Since Rekit has its own Rekit studio, things remain simple and controlled. It is a favorable solution for small scale developments.
These are some of the features that we hope you will find helpful. If you have any questions on React Developer Tools or want to see how this can benefit your business, please let us know.
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Robotics in Logistics: Dawn of a New Era
Since the advent of e-commerce, getting goods to the customer’s door or stores from the factories or warehouses has become a mammoth task for logistics companies. Forecasts say that “worldwide warehousing and logistics robot unit shipments will increase to an estimated 620,000 units annually by 2021.” The solution for this herculean task of transporting goods far and wide thus becomes apparent: the dawn of robotics in logistics. The use of robotics in logistics offers far greater levels of uptime over manual labor, bolstering productivity in a vast array of professional environments.
Retail giants like Amazon and Walmart that have already deployed robots in their warehouses and fulfillment centers will only expand their deployments, especially in the wake of current situations. Leveraging robotics in logistics cuts around 70% of warehouse labor costs and helps businesses function day and night with minimal costs. Want to find out how? This post will help you understand the importance of utilizing warehouse robotics in the supply chain.
A Surge in Warehouse Robotics in Supply Chain
The first robot in the supply chain was capable of moving material about a dozen feet. For several years, robots were used only in industrial manufacturing because it was not safe for people to be around them. However, over the last few decades, innovative logistic robotic companies have worked hard to mesh AI and machine learning, better sensors and response capabilities, warehouse management software or logistics management software.
Recently, warehouse robotics in the supply chain has picked up pace exponentially. There has been huge funding and investment in the industry. For example, Alibaba invested $15 billion into robotic logistics infrastructure and Google invested $500 million into automated logistics for JD. It is also estimated that the global market for warehouse robotics in the supply chain is projected to reach a market value of $22.4 billion by the end of 2021.
Evidently, the dawn of robotic logistics is right here now!
What is Robotic Logistics?
The logistics industry is what is holding our modern world together. It includes a huge amount of different processes. Ordering, transportation, warehousing, picking, packing, delivery, inventory, and routing are just a few of those processes.
So, robotic logistics means the application of robotics to one or more of these processes. A few common robotic applications are robotic palletizing, robotic packaging, robotic picking commonly used in warehousing or any other logistics software solutions.
So, what kind of robots could be useful for your warehouse?
Warehouse Robotics in Supply Chain
1. Autonomous Mobile Robots (AMR)
AMRs use sophisticated sensor technology to deliver inventory all over the warehouse. They do not require a set track between locations. They can understand and interpret their environment through the use of maps, computers, and onboard sensors.
These warehouse robots are small and nimble with the ability to identify the information on each package and sort it with impeccable accuracy. They cut down on the redundant manual process which is prone to human error.
2. Aerial Drones
Aerial drones aid in optimizing warehouse inventory processes. They can quickly scan locations for automated inventory. They can scan inventory much faster than a human can and send an accurate count immediately to your warehouse inventory management software.
These drones do not need markers or lasers to guide them. They don’t take up valuable space in your warehouse. They can travel quickly and assist in hard-to-reach areas.
3. Automated Guided Vehicles
Automated guided vehicles and carts (AGVs and AGCs) transport inventory around your warehouse following a track laid in your warehouse. These warehouse robots are perfect for larger warehouses because it reduces the time spent by workers just moving from one area to the next.
4. Automated Storage and Retrieval System (AS and RS)
Automated Storage and Retrieval Systems are robot-aided systems that can place or retrieve loads from set storage locations. AS and RS differ depending on the system needed, the type of task, or the goods that they will be working with. They can be programmed to work as a craft that moves and works on a well-defined path or a crane that retrieves goods between aisles. There are also aisle climbing robots that retrieve customer orders.
These free up the time of workers who can then concentrate on more complicated processes such as packing and posting the goods.
What is Driving the Need for Collaborative Robots in Logistics?
Although there has been a boom in logistic robotics, there are two specific factors that are driving the current need for collaborative robots in logistics.
- The growth of e-commerce: When products are directly shipped to customers, there is a huge variety of different packing requirements.
- The lack of available workforce: Shortage of skilled workers can affect logistics.
What are the Benefits of Adopting Robotic Logistics?
The logistics industry can see many tangible and clear benefits of adopting robotic logistics.
- By reducing human errors, robotic logistics can bring in significant profits and can also reduce warehouse costs.
- Robotics can allow for workforce adaptability.
- Robotic logistics improve safety for workers by taking over dangerous jobs such as getting items from high racks or storage spaces.
- Reduced human error and increased delivery speed brought about by robotic automation will increase customer satisfaction.
Read more: Open source robotics process automation
Enjoy the Freedom To Do More
Robots are being used rather extensively in logistics. Due to the complexity of supply chain processes robots will be increasingly used for dull, dirty, and dangerous tasks freeing your workers for more complex tasks. This means cost-effective, fast, and error-free operations. If you want this for your business, get in touch with us immediately and let us fix your business up with robot power.
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Empowering CFOs to Derive Crucial Insights and Implement Strategic Decisions with Confidence
The role of the CFO is no longer restricted to fulfilling traditional financial duties. With advances in technology, the CFO’s responsibilities are also growing as today’s CEOs and boards demand the finance function provide real-time, data-enabled decision support. The present-day CFOs and their teams serve as gatekeepers to critical data that is required to generate forecasts and support business leaders to make strategic decisions that have a lasting impact.
With that said, what are the challenging areas for CFOs where they can perform better with the integration of the right technology? We’ve tried to list out a few here.
Key Challenges Faced by CFOs
- Acquiring self-service analytical capabilities to garner strategic and operational insights for reliably enabling key decisions and enhancing visibility through the board-room to the shop floor.
- Addressing big data requirements is another challenge. Embedded data analytics that connects transaction executions with immediate insights and analyses is a must-have weapon in the CFO’s armor. With automatic matching capabilities, finance professionals can reduce the time taken to gather data.
- Predictive insights are essential to assess future outcomes. CFOs equipped with predictive analytics capabilities empower organizations through powerful budgeting, planning, and forecasting that will drive the business on the right path.
2. Ensure agility to respond, adapt and survive
- It’s always at the top of a CFO’s agenda to optimize risk management and establish a sustainable cost-effective control environment. A sustainable compliance program (compliance-first approach) can free up to 30% of the function’s capacity while keeping the risks low.
- Structure finance to make the most of tight budgets and provide financial support for corporate initiatives by ensuring discretionary expense management and operational costing optimization.
- Increasing adoption of “Shared Services model” (service delivery models under centralized and decentralized structures) for enterprise operations allows businesses to expand to several domains, customers, products, geographies, and channels. For CFOs, this translates to more challenges w.r.t. strategic pricing, customer and product profitability modeling, and profitable growth target setting. CFOs also need to cater to multiple businesses and stakeholders while supporting all the current and evolving business models.
- Embedded localization requirements to best-balance the risk and efficiency and implement best practices supporting operations across segments, industries, and geographies.
- Flexible deployment models allowing the optimal combination of cloud and on-premise solutions.
3. Optimize costs, digitize finance, and other functions
- CFO and other finance professionals are expected to offer more value-add solutions that provide strategic direction for the enterprise. Automation of repetitive, rule-based finance functions enables CFOs and financial professionals to focus more strategically.
- CFOs need to gain improved visibility across all cost components that allow them to take quick actions such as cutting unwanted costs and justifying new costs in a tangible way.
- Integrate and unify all corporate processes allowing for a higher level of standardization. This can only be achieved with an intelligent enterprise technology like SAP S/4HANA.
Why is SAP S/4 HANA ideal for CFOs?
Traditional ERP systems store data in many different tables. As a result, financial teams struggle with isolated and inconsistent information from many sources. They end up spending hours sifting through data and compiling reports manually. Despite this, they are unable to provide the desired financial insights. On the other hand, SAP S/4 HANA stores all financial information in a single Universal Journal. It is a powerful concept that eliminates redundancy and creates a single source of truth. This gives you easy access to accurate, timely, and qualitative information. Your business processes become transparent and reliable.
The broad portfolio of new technologies and innovations in SAP S/4 HANA Finance empowers CFOs with responsive decision-making tools. These tools give you instant insights into all the company’s data and systems. You can perform end-to-end analyses right from the boardroom to the shop floor.
(Click to enlarge the image) Source: SAP
Organizations using ERP systems have always found that while it’s easy to enter data into the system, getting interesting information from it is tedious. SAP S/4 HANA Finance enables direct reporting without the need for a data warehouse for specific analytic requirements. This is possible because of the Universal Journal. However, this alone does not deliver the right insights. This is where Embedded Analytics in S/4 HANA comes in.
Embedded Analytics allows not only the intuitive navigation through graphical views but also the close integration of analysis capabilities within the operational transactions. This makes it easy to act directly on the right information without having to switch between screens or systems. It has business planning, consolidation, and forecasting capabilities which can help you gain new insights from different perspectives.
The embedded analytics in S/4 HANA is also helpful to determine the best course of action when unprecedented disruptions occur. Thus, the role of the Office of Finance transforms from mere historical reporting to analyzing business performance.
Organizations need accurate financial insights to steer their business in the best path. In the past, decision-makers requested information through month-end reporting. That practice is long gone. Today, continuous delivery of relevant information is the minimum requirement. More insights are requested on what the future would bring. This is where Predictive Accounting can help.
For example, when a sales order is confirmed in the system, it is not recorded in accounting until you deliver the goods and send an invoice. With Predictive functionality based on the sales order, a predictive invoice is registered. When the actual invoice is sent out, the predictive posting is back-posted, reducing the predicted amounts. This predictive accounting logic can help you simulate financial postings based on the confirmed incoming sales orders. You end up getting an accurate and futuristic view on your margin.
Transforming Finance into an Intelligent Portfolio
The S/4 HANA digital core offers predictive analytics combined with machine learning across various lines of businesses (LoBs). SAP Cash Application is the first Lighthouse application that is based on SAP Leonardo Machine Learning. It analyzes the customer’s historical data, learns which matching criteria are important, how to prioritize them, and how to best apply them using machine learning. This helps to intelligently match payments to open receivables and automatically clear those items minimizing manual effort. Thus, we process cash faster, improving the days of sales outstanding.
In other words, finance teams can scale as the business grows and save time to focus on strategic business tasks like growth and planning. The machine learning application is cloud-based and non-disruptive to the system-of-record. As it is tightly integrated with SAP S/4HANA, you can easily adapt innovations without having to resort to costly and time-consuming IT projects or any risky activities in your back-end system.
(Click to enlarge the image) Source: SAP
Take Your Next Step with Fingent
SAP S/4 HANA supports CFOs by using business processes that are already available within the S/4 HANA environment. As CFOs grapple with new disruptive business models, SAP S/4 HANA Finance can help them in their decision-making process at a tactical and strategic level. Leveraging these technologies can enhance the organization’s ability to pivot quickly and adapt to dynamic business scenarios.
Making this big leap is definitely challenging, but Fingent’s extensive knowledge and expertise on SAP S/4 HANA Finance can get you going. Connect with our SAP expert to learn more.
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A Head-to-head Comparison of Odoo CRM vs. Salesforce
The race for business success is tough. Mimicking your competitors in what is working for them might seem like a good idea, but it will get you nowhere in the long run. Success comes only when you find that perfect recipe that is unique to your organization and gets you a notch above everyone else. This is particularly true when it comes to your CRM software. You must choose the right software that fits your sales teams’ unique and complex needs perfectly.
The quest for that perfect CRM software requires analyzing various crucial factors. Making the right choice can radically impact the effectiveness of your daily operations and boost the productivity of your sales team. The factors you need to consider are vendor reliability, real total implementation cost, pros and cons, full list of features, and user reviews. In this article, we provide a comparison of Odoo CRM and Salesforce CRM against six key criteria. We hope this helps you in making an informed decision.
What is the Difference?
Salesforce is often described as “the world’s #1 CRM sales app.” It claims to put everything you need at your fingertips – accessible from anywhere. It makes collaboration across your global organization easier and gets your deals done faster.
Odoo, on the other hand, is often described as “the open-source ERP and CRM.” It is a business management software that includes CRM, e-commerce, accounting, billing, warehouse, manufacturing, project management, and inventory management.
So, here we’re comparing these two popular CRMs against these 6 criteria:
1. Marketing automation comparison
One of the proven strategies to generate sales by any enterprise around the globe is being able to send messages to customers at exactly the right time. In this regard, both Odoo and Salesforce have great marketing automation features.
- Salesforce allows you to send a customized email to your customer through web personalization.
- Odoo kicks it up a notch, allowing you to design an entire workflow for your enterprise. You can automate your action depending on the customer’s reaction to your email which might include replying to your email or deleting it.
2. Cost comparison
The actual cost of CRM software includes the subscription fee, software license, software training, and customization cost, hardware, and the cost of other services such as support and maintenance. It is crucial that you account for all the costs involved to understand the system’s “total cost of ownership.”
- Salesforce CRM starts at $25 per user/month. They also offer a yearly plan. Apart from this, you will have to make additional payments for integrations that you will add to your software.
- Odoo CRM too starts at $25 per user/month but offers a free plan which is helpful for startup companies. Although integrating paid apps incurs charges, the Odoo Community Edition is free.
3. Integration comparison
Your software serviceability requires powerful integrations.
- Salesforce can integrate with a variety of apps making it suitable for all businesses.
- Being an open-source software Odoo provides free apps that can be integrated into any kind of business.
4. Contact management comparison
One of the key capabilities that businesses require is the ability to view and manage contacts.
- Since Salesforce is a cloud-based CRM, it can obtain certain missing details of your contacts from other sources in the cloud. Also, it can analyze the interactions between the contacts over various social media platforms which can be a great help to your business in generating leads.
- Odoo gives you complete access to the history of business interactions for each customer. This allows you to adjust your business strategies according to the purchasing habits of your customers. You can also synchronize Odoo with your Google Calendar so you can keep track of your meetings and additional follow-ups.
5. Dashboards and reports comparison
While dashboards assist you in presenting and viewing your business performance, reports help you audit sales and gauge work performance. Dashboards and reports help you make smart business decisions.
- Salesforce allows you to build a customized dashboard according to your business requirements.
- Odoo offers free apps to create customized dashboards allowing you to create a variety of reports, balance sheets, tax reports, and bank reconciliation.
6. Vendor comparison
- Salesforce is a global software company best known for its cloud-based CRM. In 2012, Fortune ranked Salesforce 27 in its 100 best companies to work for. It was also listed in the New York Stock Exchange.
- The Odoo community has 1,500 active members and has contributed over 4,500 modules. It has a network of certified partners established in over 100 countries. Odoo is one of the most frequently installed business suites with more than 1,500 downloads per day.
Read more: A 3-day Odoo CRM implementation story!
Make An Informed Decision
While taking a decision, remember to compare the features of Salesforce and Odoo through the lens of usability, flexibility, and the unique needs of your employees and business. The highly modular and customizable solution provided by Odoo CRM is designed specifically for cost-effective and high-performance scalability and growth.
Although Odoo is newer to the market when compared to Salesforce, this open-source CRM is used by certain popular names such as Hyundai, Toyota, and Alta Motors. There is no denying that Odoo has gained the trust of many users and is highly coveted by businesses of all sizes including SMEs/ SMBs.
Read more: Meeting the HR Requirements With Odoo
Fingent is an Official Partner of Odoo and has hands-on expertise in the consulting, implementation, and customization of Odoo for clients across several industries. If you need further help in making your decision or want to get started with Odoo, give us a call right away.
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10 Services Offered by Fingent to Prepare Your Business for the Future of Digital Innovation
- Robotic Process Automation
- Business Continuity Planning
- Contactless Services
- Custom LMS | eLearning
- Business Process Re-engineering
- Reality Technologies
- Data Analytics
- Internet of Things
- Mobile Technologies
- Cloud Computing
- Innovation beyond digital transformation
It’s been more than half a year since we started battling the global pandemic COVID-19. While it shows no sign of waning and continues to dwindle economies, business leaders are still exhibiting a streak of optimism. Thanks to digital technology and infrastructure!
The American management consulting firm McKinsey states that business executives expect profits and consumer demands to rise within the next six months. However, households across the globe have reduced their spending due to low income and savings. This poses a challenge for business sectors such as banking, retail, telecom, healthcare, and utilities. The organizations belonging to these sectors have to find new ways to support customers as well as preserve shareholder value in these ambivalent times.
In spite of several unsuccessful attempts to curb the virus spread, promising vaccine tests give us hope. The good news along with it is that businesses are managing to meet their urgent requirements and are optimistic for a time when all employees can return to work safely. Business leaders need to focus on supporting their employees by building up trust and providing clear communication.
If not anything, the pandemic has taught us the necessity of digital innovation and management. The business-as-usual approach is bound to fail in these difficult times. Business leaders have to make fast decisions, use technology in new and different ways to improve productivity and accelerate digital innovation. Organizations that embrace technology and new tools to reinvent business processes will see better results. This blog enlists 10 ways by which Fingent can help you re-engineer your business processes and overcome the challenges efficiently.
1. Robotic Process Automation
In light of what’s happening, the demand for automation has fundamentally increased simply because the business dynamics have changed in various industries. Since most employees have to work from home, repetitive and data-intensive processes could be handed over to Robotic Process Automation. Once employees are freed up from performing mundane tasks, they can concentrate on other important operations that require cognitive skills.
The payroll, onboarding and offboarding processes in HR can be automated using RPA technology. In the banking sector too, RPA bots can fasten activities such as loan application processing, account opening and make them error-free.
Fingent combines technologies like Machine Learning and AI with RPA to design smarter processes for businesses. Our focus is on utilizing RPA software bots to enhance the cost-effectiveness and efficiency of business processes. We help companies to automate business processes by identifying areas that require automation, deploy the most appropriate tools, and provide the necessary maintenance and support.
2. Business Continuity Planning
A business continuity plan is crucial to ensure the effective recovery of organizations from a disaster. From conducting virtual site inspections to document collaboration to human resources and payroll management, Business Continuity Planning helps keep track of all your crucial tasks.
Fingent utilizes a wide range of technological frameworks like SAP, AWS, Microsoft technologies, public cloud services, and custom software solutions to help you come up with a strong business continuity plan. Our Business Continuity Planning (BCP) services enable you to make faster decisions, reduce costs, and retain customers. We help you create and implement a sustainable business model that allows you to keep pace with the rising customer demands.
3. Contactless Services
COVID-19 has changed customer behavior w.r.t what and how they buy. This shift has given rise to a demand for contactless services. The demand for smart deliveries, self-service facilities, and other technologies such as QR codes, mobile payments, tap-and-go are expected to rise.
Maneuvering these challenging times may seem daunting. But Fingent can help you turn the tables with our innovation capabilities and technology consulting. We guide organizations to expand their existing set of offerings and capture new markets.
Fingent helps you bring your brick-and-mortar store online by developing highly responsive, secure, and scalable ecommerce CRM solutions, customize your existing application to integrate contactless payment features, configure new offers or discount codes and also helps you leverage AR/VR technologies that allow customers to view your project sites or prototypes.
4. Custom LMS Development | eLearning
According to a recent study, 42% of organizations in the US have increased their ROI through eLearning. Over 90% of students say that they prefer eLearning to classroom training- a trend created by the COVID-19 forced lockdowns. eLearning systems are highly beneficial in times of a global pandemic like COVID-19 to ensure uninterrupted learning.
Fingent helps schools, universities, colleges, educational institutions, NGOs, and training centers to develop customized LMS platforms that come with aptitude-based smart learning tools.
5. Business Process Re-engineering
Business process re-engineering involves the fundamental rethinking and redesigning of processes to achieve significant improvements in performance, efficiency, and alignment of processes with organizational strategy. Fingent’s BPR services enable enterprises to revamp existing business processes to improve productivity, quality, and cycle time, especially during a crisis.
Here’s the difference that Fingent’s BPR brings to your table:
- Re-engineer and optimize your processes from the ground up
- Eliminate redundant processes and enhance workflow efficiency
- Coordinate and integrate multiple functions/ teams quickly
Business process reengineering offers nearly all benefits- increased revenue, improved customer service, reduced cost, higher employee retention, faster processing time. Though the risks are considerable, the crisis presents an opportunity for your business to build resilience and reshape your future roadmap by leveraging BPR.
6. Reality Technologies
The latest advancements in Augmented Reality and Virtual Reality technologies are helping businesses explore new ways to reach customers and take their innovation efforts to the next level. Perkins Coie LLP reports healthcare and medical devices as one of the top potential growth areas for AR and VR technologies. Visual-based immersive learning experiences, virtual events and conferences, virtual showings and site tours, etc. ensure sustainability, safety, and remote collaboration.
Read our case study: The Future of Communication and Security Using Augmented Reality
7. Data Analytics
The COVID-19 pandemic has disrupted supply chains and has brought about dramatic changes in customer behavior. Given the current volatility, it is nearly impossible to track real-time changes in consumer mannerisms and aptly respond to them. Fingent offers Predictive Analytics from SAP as well as other data analytics solution providers that can help you detect hidden trends and make quick decisions.
Sectors such as healthcare, retail, sports, insurance use predictive analysis in various ways. Fingent’s data analytics services guide you towards increased ROI by turning data into valuable insights.
8. Internet of Things
Business executives believe that the disruption brought on by COVID-19 will cause an increase in the demand for IoT devices. Robust 5G networks are necessary to realize the power of IoT. Join forces with Fingent to leverage the benefits of IoT in your business. Gear up for IoT with our vast portfolio of technologies that can help you create new IoT processes and manage your devices. We provide customized IoT services to meet your unique business needs. Our cloud-based IoT data management solutions help you gather insights from your IoT data.
9. Mobile Technologies
As stay-at-home and social distancing are the new norms, mobile technologies can keep business running. At Fingent, we utilize leading mobile technologies to support businesses. Being scalable and secure, our mobile solutions deliver value to your customers.
So you want to build an app, but don’t know how to get on with it? While finding the right mobile app development company may seem an obvious answer, you first need to get your requirements on paper. Fingent offers a mobile app specification template that can help you define the scope and functionalities of your app. This erases ambiguity in the development process and keeps all stakeholders on the same page.
10. Cloud Computing
The Cloud has proved to be a lifesaver for businesses whose offices are closed and employees are scattered across various locations. Those who were skeptical of the Cloud are now changing their opinions and have come to benefit from the flexibility that it offers.
Fingent’s expertise in cloud architecture models has helped many organizations realize their goals. With our proficiency in various cloud platforms such as AWS, Microsoft Azure, IBM, and Google we aim to make organizations flexible and agile. We also provide cost-effective cloud application development solutions that can be easily implemented in your current infrastructure and tailored to suit user requirements.
Innovation beyond digital transformation
As the pandemic seems to gather strength, organizations scramble to find ways to keep business running. Business leaders have to prepare for recovery by supporting their staff, establishing effective communication, and balancing costs. If nothing else, these turbulent times have brought to light the significance of digital transformation. By resorting to innovative digital technologies like the ones mentioned above, businesses can reinvent themselves and keep going.
We at Fingent focus on supporting businesses and ensuring business continuity by equipping them with these smart technologies. These technologies can also help you understand the pulse of your customers and make the necessary changes in your business models. It has become increasingly clear that given the serious health implications on people returning to work, creating a post-pandemic organization would take longer than earlier perceived. Companies have to seize this opportunity to build new capabilities like remote work environments, virtual collaboration, automation, eLearning, eCommerce, and so on.
Our business solutions have already helped various industrial sectors solve problems and eventually succeed. Fingent can help you capitalize on this opportunity to create a digital innovation strategy. Contact us to know more.
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How Time Series Analysis Enables Businesses to Improve Their Decision Making
- Definition of Time Series
- The 5 Most Effective Time Series Methods for Business Development
- Time Series Regression
- Time Series Analysis in Python
- Time Series in Relation to R
- Time Series Data Analysis
- Deep Learning for Time Series
- Benefits of Using Deep Learning to Analyze Your Time Series
- Time Series is Valuable for Business Development
Time series analysis is one of the most common data types encountered in daily life. Most companies use time series forecasting to help them develop business strategies. These methods have been used to monitor, clarify, and predict certain ‘cause and effect’ behaviours.
In a nutshell, time series analysis helps to understand how the past influences the future. Today, Artificial Intelligence (AI) and Big Data have redefined business forecasting methods. This article walks you through 5 specific time series methods.
Definition of Time Series
Time series is a sequence of time-based data points collected at specific intervals of a given phenomenon that undergoes changes over time. It is indexed according to time.
The four variations to time series are (1) Seasonal variations (2) Trend variations (3) Cyclical variations, and (4) Random variations.
Time Series Analysis is used to determine a good model that can be used to forecast business metrics such as stock market price, sales, turnover, and more. It allows management to understand timely patterns in data and analyze trends in business metrics. By tracking past data, the forecaster hopes to get a better than average view of the future. Time Series Analysis is a popular business forecasting method because it is inexpensive.
The 5 Most Effective Time Series Methods for Business Development
1. Time Series Regression
Time series regression is a statistical method used for predicting a future response based on the previous response history known as autoregressive dynamic. Time series regression helps predictors understand and predict the behaviour of dynamic systems from observations of data or experimental data. Time series data is often used for the modeling and forecasting of biological, financial, and economic business systems.
Predicting, modeling, and characterization are the three goals achieved by regression analysis. Logically, the order to achieve these three goals depends on the prime objective. Sometimes modeling is to get a better prediction, and other times it is just to understand and explain what is going on. Most often, the iterative process is used in predicting and modeling. To enable better control, predictors may choose to model in order to get predictions. But iteration and other special approaches could also be used to control problems in businesses.
The process could be divided into three parts: planning, development, and maintenance.
- Define the problem, select a response, and then suggest variables.
- Ordinary regression analysis is conditioned on errors present in the independent data set.
- Check if the problem is solvable.
- Find the correlation matrix, first regression runs, basic statistics, and correlation matrix.
- Establish a goal, prepare a budget, and make a schedule.
- Confirm the goals and the budget with the company.
- Collect and check the quality of the date. Plot and try those models and regression conditions.
- Consult experts.
- Find the best models.
- Check if the parameters are stable.
- Check if the coefficients are reasonable, if any variables are missing, and if the equation is usable for prediction.
- Check the model periodically using statistical techniques.
2. Time Series Analysis in Python
The world of Python has a number of available representations of times, dates, deltas, and timespans. It is helpful to see how Pandas relate to other packages in Python. Pandas software library (written for Python) was developed largely for the financial sector, so it includes very specific tools for financial data to ensure business growth.
Understanding Date and Time Data:
- Time Stamps: Refers to particular moments in time.
- Time intervals and periods: Refers to a length of time between a particular beginning and its endpoint.
- Time deltas or durations: Refers to an exact length of time.
Native Python dates and times:
Python’s basic objects for working with dates and times are in the built-in module. Scientists could use these modules along with a third-party module, and perform a host of useful functionalities on dates and times quickly. Or, you could use the module to parse dates from a variety of string formats.
Best of Both Worlds: Dates and Times
Pandas provide a timestamp object that combines the ease-of-use of datetime and dateutil with vectorized interface and storage. From these objects, pandas can construct datetimeIndex that can be used to index data in dataframe.
Fundamental Pandas Data Structures to Work with Time Series Data:
The most fundamental of these objects are timetstamp and datatimeIndex objects.
- Time Stamps type: It is based on the more efficient numpy.datetime64 datatype.
- Time Periods type: It encodes a fixed-frequency interval based on numpy.datetime64.
- Time deltas type: It is based on numpy.timedelta64 with TimedeltaIndex as the associated index structure.
3. Time Series in Relation To R
R is a popular programming language and free software environment used by statisticians and data miners to develop data analysis. It is made up of a collection of libraries specifically designed for data science.
R offers one of the richest ecosystems to perform data analysis. Since there are 12,000 packages in the open-source repository, it is easy to find a library for any required analysis. Business managers will find that its rich library makes R the best choice for statistical analysis, particularly for specialized analytical work.
R provides fantastic features to communicate the findings with presentation or documentation tools that make it much easier to explain analysis to the team. It provides qualities and formal equations for time series models such as random walk, white noise, autoregression, and simple moving average. There are a variety of R functions for time series data that include simulating, modeling, and forecasting time series trends.
Since R is developed by academicians and scientists, it is designed to answer statistical problems. It is equipped to perform time series analysis. It is the best tool for business forecasting.
4. Time Series Data Analysis
Time series data analysis is performed by collecting data at different points in time. This is in contrast to the cross-sectional data that observes companies at a single point in time. Since data points are gathered at adjacent time periods, there could be a correlation between observations in Time Series Data Analysis.
Time series data can be found in:
- Economics: GDP, CPI, unemployment rates, and more.
- Social sciences: Population, birth rates, migration data, and political indicators.
- Epidemiology: Mosquito population, disease rates, and mortality rates.
- Medicine: Weight tracking, cholesterol measurements, heart rate monitoring, and BP tracking.
- Physical sciences: Monthly sunspot observations, global temperatures, pollution levels.
Seasonality is one of the main characteristics of time series data. It occurs when the time series exhibits predictable yet regular patterns at time intervals that are smaller than a year. The best example of a time series data with seasonality is retail sales that increase between September to December and decrease between January and February.
Most often, time-series data shows a sudden change in behaviour at a certain point in time. Such sudden changes are referred to as structural breaks. They can cause instability in the parameters of a model, which in turn can diminish the reliability and validity of that model. Time series plots can help identify structural breaks in data.
5. Deep Learning for Time Series
Time series forecasting is especially challenging when working with long sequences, multi-step forecasts, noisy data, and multiple inputs and output variables.
Deep learning methods offer time-series forecasting capabilities such as temporal dependence, automatic learning, and automatic handling of temporal structures like seasonality and trends.
Benefits of Using Deep Learning to Analyze Your Time Series
- Easy-to-extract features: Deep neural networks minimize the need for data scaling procedures and stationary data and feature engineering processes which are required in time series forecasting. These neural networks of deep learning can learn on their own. With training, they can extract features on their own from the raw input data.
- Good at extracting patterns: Each neuron in Recurrent Neural Networks is capable to maintain information from the previous input using its internal memory. Hence, it is the best choice for the sequential data of Time Series.
- Easy to predict from training data: The Long short-term memory (LSTM) is very popular in time series. Data can be easily represented at different points in time using deep learning models like gradient boosting regressor, random forest, and time-delay neural networks.
Time Series is Valuable for Business Development
Time series forecasting helps businesses make informed business decisions because it can be based on historical data patterns. It can be used to forecast future conditions and events.
- Reliability: Time series forecasting is most reliable, especially when the data represents a broad time period such as large numbers of observations for longer time periods. Information can be extracted by measuring data at various intervals.
- Seasonal patterns: Data points variances measured can reveal seasonal fluctuation patterns that serve as the basis for forecasts. Such information is of particular importance to markets whose products fluctuate seasonally because it helps them plan for production and delivery requirements.
- Trend estimation: Time series method can also be used to identify trends because data tendencies from it can be useful to managers when measurements show a decrease or an increase in sales for a particular product.
- Growth: Time series method is useful to measure both endogenous and financial growth. Endogenous growth is the development from within an organization’s internal human capital that leads to economic growth. For example, the impact of policy variables can be evidenced through time series analysis.
We can help you get the best of Time Series Analysis to benefit your business. Reach out to us to understand more about our data analytics and machine learning capabilities and how it can help your business grow.
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Understanding the concept and significance of Deep Reinforcement Learning
The field of reinforcement learning has exploded in recent years with the success of supervised deep learning continuing to pile up. People are now using deep neural nets to learn how to use intelligent behavior in complex dynamic environments. Deep reinforcement learning is one of the most exciting fields in artificial intelligence where we combine the power of deep neural networks to comprehend the world with the ability to act on that understanding.
In deep learning, we take samples of data and supervise the way we compress and code the data representation in a manner that you can reason about. Deep reinforcement learning is when we take this power and apply it to a world where sequential decisions are to be made.
We use deep reinforcement learning to solve tasks where an agent or an intelligent system has to make a sequence of decisions that directly affect the world around the agent. While trial-and-error is the fundamental process by which reinforcement learning agents learn, they do use neural networks to represent the world.
Types of learning
All types of machine learning– supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning are supervised by a loss function. Even in unsupervised learning, there is some kind of human intervention required to determine and provide inputs on what is good or bad. Only the cost of human labor required to obtain this supervision is low. Thus, the challenges and the exciting opportunities of reinforcement learning lie in how we get that supervision in the most efficient way possible.
In supervised learning, you take a bunch of data samples and use them to learn patterns to interpret similar samples in the future. However, in reinforcement learning, you teach an agent through experience. So the essential design step in reinforcement learning is to provide the environment in which the agent has to experience and gain rewards. In other words, a designer has to design not only the algorithm but also the environment where the agent is trying to solve a task.
The most difficult element in reinforcement learning is the reward – good vs bad. For example, when a baby learns to walk, success is the ability to walk across the room and failure is the inability to do so. Simple! Well, this is reinforcement learning in humans. How we learn from so few examples through trial-and-error is a mystery. It could be the hardware – 230 million years of bipedal movement data that is genetically encoded in us or it could be the ability to learn quickly through the few minutes or hours or years of observing other humans walking. So the idea is if there was no one around to observe, we would never be able to walk. Another possible explanation is the algorithm that our brain uses to learn which has not yet been understood.
The promise of deep learning is that it converts raw data into meaningful representations whereas the promise of deep reinforcement learning is that it builds an agent that uses this representation to achieve success in the environment.
Deep Q learning
Q-learning is a simple and powerful algorithm that helps an agent to take action without the need for a policy. Depending on the current state, it finds the best action on a trial-and-error basis. While this works for practical purposes, once the problem size starts increasing, maintaining a Q-value table becomes infeasible considering the amount of memory and time that would be required. This is where neural networks come in.
From a given input of action and state, a neural network approximates the Q-value function. Basically, you feed the initial state into the neural network to get the Q-value of all possible actions as the output. This neural network is called Deep Q-Network. However, DQN is not without challenges. The input and output undergo frequent changes in reinforcement learning with progress in exploration. The concepts of experience replay and target network help control these changes.
Read more: Top 10 Machine Learning Algorithms in 2020
Deep Reinforcement Learning Frameworks
Here are the three Deep Reinforcement Learning frameworks:
1. Tensorflow reinforcement learning
RL algorithms can be used to solve tasks where automation is required. However actual implementation is easier said than done. You can ease your pain by using TF-Agents, a flexible library for TensorFlow to build reinforcement learning models. TF-Agents makes it easy to use reinforced learning for TensorFlow. TF-Agents enables newbies to learn RL using Colabs, documentation, and examples as well as researchers who want to build new RL algorithms. TF-Agents is built on top of TensorFlow 2.0. It uses TF-Eagers to make development and debugging a lot easier, tf.keras to define networks and tf.function to make things faster. It is modular and extensible helping you to pick only those pieces that you need and extend them as required. It is also compatible with TensorFlow 1.14.
2. Keras reinforcement learning
Keras is a free, open-source, neural network Python library that implements modern deep reinforcement learning algorithms. Using Keras, you can easily assess and dabble with different algorithms as it works with OpenAI Gym out of the box. Keras offers APIs that are easy and consistent, thus reducing the cognitive load. These APIs can handle the building of models, defining of layers or implementation of multiple input and output models. Keras is fast to deploy, easy to learn, and supports multiple backends.
3. PyTorch Reinforcement learning
PyTorch is an open-source machine learning library for Python based on Torch and is used for applications such as natural language processing. It consists of a low-level API that focuses on array expressions. This framework is mostly used for academic research and deep learning applications that require optimized custom expressions. The PyTorch framework has a high processing speed with complex architecture.
All these frameworks have gained immense popularity and you can choose the one that suits your requirements.
While deep reinforcement learning holds immense potential for development in various fields, it is vital to focus on AI safety research as well. This is going to be fundamental in the coming years in order to tackle threats like autonomous weapons and mass surveillance. We should, therefore, ensure that there are no monopolies that can enforce their power with the malignant use of AI. So international laws need to keep up with the rapid progress in technology.
We have tried to brush across the basics of deep reinforcement learning and the top 3 frameworks that are in use currently. Want to know more about this amazing technology? Reach out to us at Fingent!
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Why your business needs to adopt headless CMS architecture
70% of companies are actively investing in content marketing and almost 60% of marketers rate content marketing as extremely important or very important to their marketing strategy, states HubSpot. Modern customer behavior is driving up the demand for a more flexible, customizable, and scalable CMS that is adept to deliver the experience your customers expect. When compared to traditional CMS, Headless CMS enables organizations to speed up delivery times while iterating quicker. This blog walks you through seven specific business benefits of headless CMS. Let’s begin by understanding what headless CMS is.
What is meant by Headless CMS?
A headless CMS allows us to edit CMS and database without an integrated presentation layer. The integrated presentation layer, which is referred to as a ‘head’, restricts the use of content only to one particular channel such as a website. Once CMS is severed from the head, it could be used across various other platforms such as a mobile, tablet, and smart devices, making it ideal for the current business scenario.
7 Business Benefits of Adopting a Headless CMS
1. More flexible
Since headless CMS is API driven, it allows you to build your own head or a presentation layer/ frontend. Besides enjoying the ability to pick your programming language, your developers can develop the website without having to conform to any proprietary development constraints. A single piece of content can be reused or combined with various other presentation outputs enabling faster project completions.
A headless CMS allows secure and easy integration with any of your existing business systems. Additionally, since it does not have a fixed structure to code, your developers are at liberty to code for any type of integration. This gives them the flexibility to integrate with more complex systems.
For example, Sanity.io is a popular headless CMS that allows you to embed editable data in running text and cache multiple queries on a single request. It also provides real-time collaboration, content versioning, and live previewing.
2. Supports Omnichannel Selling
For marketers to provide a customer-pleasing experience, each channel used by the business would require access to the current product information and availability. It can be quite a challenge to create iconic content that shines across all touchpoints. Instead, a headless CMS provides the capability to orchestrate a seamless experience across all touchpoints while maintaining consistency and relevance. For instance, Sitefinity empowers brands to deliver a personalized experience across channels.
3. Headless CMS is Future-Proof
A headless CMS enables businesses to future-proof their applications by separating the presentation layer from the data and logic layer. You can structure your content to facilitate future-proofing for new projects. Also, you would not be required to make any technical changes when re-branding one or more channels. Sitecore is a leading headless CMS that offers enterprise-class search and content targeting to boost personalization efforts, among other things.
It is a lot cheaper for your business team to create a new functionality because headless CMS requires little technical involvement. For example, if your marketing department chooses to create a new series of product mini-sites, they do not have to depend on developers to build CMS-based templates. Instead, the marketing team can directly go to the CMS and start creating the mini-sites as and when required, reducing your up-front costs. Kentico CMS, for instance, comes with tailored custom pricing. Websites of popular brands like Sony and Starbucks are powered by Kentico.
5. Offers Better Software Architecture
A headless CMS is architected to decouple CMS platforms and published content. This strengthens security because access to the CMS is restructured internally within the organization. It increases scalability simply by spinning up a new app server and pointing it to the content. It remains available against all odds because even when the CMS application goes offline, web applications will not have an impact. Episerver, the leading WCM platform supports editors to drag-and-drop content to create new digital experiences quickly.
6. Allows you to do more with less
Organizations will no longer need large teams of specialists with particular CMS knowledge, unlike the requirements for a traditional CMS.
7. Lets You Focus on Your Business
Worrying about your CMS can be time-consuming and distracting. A traditional CMS structure can take your attention away from growing your business. Whereas Headless CMS allows you to use your precious time and resources to grow your business. Being a multi-tenant system, it is fully managed and upgraded for you.
A Step Forward
Apart from these, there are several other reasons why businesses must consider a headless CMS. The important aspect to consider is how you want to manage and store content for products and articles. This can have an impact on websites, application performance, and conversions. Hence, as marketers, it’s time to take a step beyond traditional CMS.
If you’re considering a headless CMS to improve your digital content experience, send us a message immediately.
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What makes Odoo the best ERP solution for your business?
As business leaders, you may find that you’re spending too much time running your company rather than growing it. You may easily get bogged down due to exhaustive paperwork, long spreadsheets, or have to assemble discrete software to actually work together. This is where the open-source Odoo ERP comes to your rescue. With its vast suite comprising over 40 business productivity applications, Odoo provides a smoother and simpler way to run your business. The range of business apps offered by Odoo is highly comprehensive, fully-integrated, easy to use, and supports numerous different industries. Fingent, utilizing its partnership with Odoo ensures their clients are leveraging one or more apps from Odoo to boost their business efficiencies.
With Odoo, you can easily create your professional website, manage your relationship with customers, design and launch your own marketing strategies, and manage online payments through e-commerce. You also have Odoo apps to manage your warehouse, accounts, and invoicing behind the scenes.
Whatever be your business needs, Odoo provides apps that work together seamlessly. Though a relatively young contender, Odoo comes packed with powerful ERP features and a user-friendly interface like any other market leaders such as SAP, Oracle, MS Dynamics, and so on.
Here are 5 distinguishing features of Odoo that make it a reliable ERP for any business.
1. Easy to set up and use
Odoo has a very clean, consistent, easy-to-use interface. It is also easy to set up and configure. You can effortlessly carry out an entire transaction all the way from a quotation to the sales order, invoice, and payment due to the consistency between the various applications within Odoo. It helps you to get started within no time.
2. Powerful communication tools
Odoo has powerful inbuilt communication tools. They use messaging systems to keep track of internal communications on either your sales orders, invoices, or purchasing. So if you have a question on your sales order, you can write a message to all the followers of the sales order at the bottom of the documents. Thus, you can attach notes and messages and communicate directly from within the document giving you a great audit trail. All the team members stay on the same page both literally and figuratively!
Read more: Meeting Your HR Requirements with Odoo
3. Integrated front-end and back-end tools
You can have a full-blown website builder with a single click. So, once you install the web platform, you can use it integrated with all the other Odoo applications. Odoo provides powerful e-commerce tools that integrate with your website and are completely tied-in to the web framework. Moreover, the shopping cart looks clean, is built-in to the e-commerce app, and is ready-to-go. Another interesting feature of Odoo is that even if a customer didn’t make it to checkout and has just added items to his cart, you can view it as a draft in Quotations instead of a full Sales Order.
4. Great mobile support
Though Odoo is completely web-based, it looks pretty good on mobile phones and tablets. You even get a mobile preview to check how your website is going to look like. So, unlike a lot of legacy accounting systems that are still trying to catch up, Odoo was founded as a three-tier mobile application platform and it has continued to improve.
5. Powerful enterprise and cloud solutions
Odoo has very powerful enterprise and cloud solutions. You can host it yourself or on Amazon, or on digital cloud. You can also use Odoo.com or Odoo’s own hosted solution. Thus, there are a lot of different ways to host it as Odoo is very cloud friendly. Fingent extends support for deploying Odoo on web servers like AWS and other secure environments.
Other factors that make Odoo unique
Odoo is highly customizable, completely open-source, utilizes Industry Standard Libraries, and is written in Python. The backend database is PostgreSQL which is also open source. Another important aspect is that you can build custom Odoo Applications without modifying the source code. You can easily upgrade or extend without breaking things.
Read more: A 3-day Odoo CRM implementation story!
The COVID-19 pandemic has taught us that going digital is no longer an option, but a necessity. Choosing the right ERP that suits your business requirements and unlocks the returns on your investment can help you get there. The modular framework has given Odoo a wide functional scope. While using Odoo, enterprises do not need to resort to 3rd party platforms or use additional bridging software to build fully integrated websites. Thus, Odoo supports the uniqueness of each business. This ability to customize every aspect of your system gives you a competitive advantage. And all this can be done at minimal cost, compared to the other ERP systems available in the market. As enterprises have to look at the eventual ROI before implementing an ERP system, Odoo shines because of its functionality, scalability, and affordability. Fingent’s partnership with Odoo ensures your projects are tailored for easy adaptability. Get in touch with us to plan the next dependable Odoo application that will assist in your daily business operations.
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Challenges Your Business Should Overcome in the Post-COVID Phase
- Challenges in Reopening Strategy
- Challenges of Shifting Customer Habits
- Challenge of Operations and Employee Safety
- Impact on Operations for Manufacturing Units
- Challenges of Finance and Banking
- Tax, Trade & Regulatory Challenges
- Crisis Management
- Focus on tomorrow
The past few months have been an extremely challenging time for communities across the globe as the pandemic continues to take its toll. Amidst all the chaos and anxiety however, the world is trying to return to the new normal. During this unprecedented reality, businesses are witnessing the beginning of a dramatic restructuring of economic and social order. Everyone is looking forward to the next normal that will materialize after the battle against COVID-19 has been won, with hopes that it will be better and more profitable. Challenges lie ahead though. What are these COVID-19 Aftermath challenges and how do we combat them? This article will discuss that.
Where Do We Start?
With lives and livelihoods in danger, businesses are running a spreadsheet for basics that never mattered so much before. Plans are being drawn how many people can fit into a workplace spaced six feet apart, where the one-way path should begin and end, and what adjustments can and need to be made to the entrance, lunchrooms, and restrooms.
All of these are critical tasks but chalking them down is not going to be enough to mobilize and stabilize businesses. We need an enterprise-wide ability to absorb uncertainty while incorporating lessons into operating models quickly. This might seem like a daunting path beset with challenges, but an action plan can get you through this successfully. This article discusses 7 major challenges and resolutions to jumpstart the recovery.
1. Challenges in Reopening Strategy
The pandemic has impacted nearly every industry including retail. Manufacturing is on a downward slope as production moves at a snail’s pace. Supply chains are being disrupted due to higher air freight costs. This supply shock is having a knock-on effect on retail. Navigating their way out of this spiral is going to need a solid reopening strategy.
What can businesses do?
- Restart and reset, not just reopen: Employee and customer behaviors have drastically changed. Be ready to start a new era of business. Build courage and foresight to change for more than just immediate needs.
- Be ready to adopt omnichannel integration: Omnichannel initiatives offer contactless curbside pickup and other features, so be willing to continuously improve services.
- Shape your future workforce: Redeploy store associates to fill other roles. Upskill then to achieve the required digital fluency. Cross-train employees so that they can fill in when others are away.
- Act swiftly to radically accelerate in-store integration: Customers may not be inclined to visit stores unless you give them a good reason to do so. Offer your consumers compelling value propositions for store traffic.
- Develop a future-state vision: Adopt an omnichannel view that includes store closure plans or rent negotiations.
- Digitize and automate non-core tasks: Automate labor scheduling. Expand the use of self-checkout and mobile checkout processes. Provide remote-management tools for in-house and field managers.
- Shift tasks: Sourcing and distribution teams must find ways to move certain tasks, such as price tagging and labeling, away from stores.
2. Challenges of Shifting Customer Habits
As the coronavirus spread progressed across geographies, customer behavior has also changed drastically. Customer habits are changing, and we can expect them to continue to change in the weeks and months ahead. We can break down their behavior into three phases where each phase shows a distinct behavior:
- Escalation: Customers tend to load up on essential goods such as groceries and medicines which include immunity-boosters.
- Accumulation: Customers brace for a sustained quarantine by stocking up on everyday personal care products.
- Recovery: Customers will continue to spend on consumer goods.
Also, customers now prefer making purchases online, their focus has shifted more to eCommerce.
How can businesses respond?
- Enable flexible product flow: Ensure your product inventories align with consumer demand. Make distribution centers more flexible. As more customers purchase products online, make sure you minimize distribution disruptions.
- Bolster online presence: Accelerate direct-to-customer sales.
- Maintain close contact with customers: Ensure they know that products are available.
3. Challenge of Operations and Employee Safety
One of the main concerns of a company leader during and after the COVID-19 pandemic is its impact on operations. Evidently, the epidemic has adversely affected sales volume and the ability to serve clients and customers as well as manage the business. Companies are faced with the challenge of employees being quarantined for weeks after business or vacation trips. They lack the tools required to organize remote work during the quarantine.
How to reorganize the workplace?
- Establish dedicated cross-functional teams: They can coordinate the activities between various business units, provide necessary information to the management team, and communicate with employees, partners, and employees.
- Analyze critical roles and key positions: Develop an effective process for managing decision-making under various scenarios.
- Ensure the safety of employees: Review policies for maintaining good hygiene at the workplace.
- Ensure that there is no crowding in the office: Decide on which roles can be done remotely and which roles require employees to be present in the office. This will help you optimize the work with only 20-30% of employees at the office.
- Easy Transportation: Ensure that transportation is arranged for and accessible by the employees.
- Plans for support staff: Have a written plan on how to stagger the arrival of support staff such as receptionists and security guards.
- Workout checkpoints: Have a series of checkpoints where testing can be done.
4. Impact on Operations for Manufacturing Units
Manufacturers face formidable challenges when it comes to restarting their operations. Globally, they are facing workforce disruptions at an unprecedented scale. Most manufacturers are yet to determine how they will function and perform while struggling to cope with the present scenario. They need fit-for-purpose plans.
How can manufacturers respond?
- Start with possible scenarios: Start with the current need for workforce and design a workforce approach.
- Tap into technology: Consider the possibility of automating certain aspects of the industry which would avoid too many people at the site.
- Create a roster: Ensure that teams come in at different times during the day depending on the number of workers and the skill required at any given point.
- Focus on a safe work environment: Organize regular cleaning and disinfection of workplaces and tools. Invest in medical equipment such as thermometers and sanitizers.
- Review sick leave policies: Consider the possibility of providing temporary sick leave without the need to provide a doctor’s notice.
- Develop agile workforce strategies: It keeps the global economy viable.
- Create your own news channel: Misinformation can create particular challenges for manufacturers. Combat this by ensuring that you put out timely, accurate, and appropriate information for your workers.
5. Challenges of Finance and Banking
Economic uncertainty and risk have either directly or indirectly impacted most finance companies. As businesses slow down, companies are seeing lower revenue due to reduced cash flow.
Managing cash and liquidity positions may become crucial in the coming months. This situation is worsened by inadequate digital maturity, staff shortages and immense pressure on the existing infrastructure as companies deal with the impact of the pandemic. You need strategies to safeguard your customers’ financial security while you safeguard their wellbeing and yours as well.
What can finance services do?
- Craft a strategic response: Adopting the right digital technologies enables innovations. These must include solutions for analytics and insights to detect and prepare for new risks.
- Enable Automation: Ensure availability of digital banking services through business process reengineering and automation.
- Leverage AI capabilities: There has been and will be a surge in call volumes during and after COVID-19. Leverage AI-backed tools and conversation platforms to deal with the surge.
- Initiate video banking: Live web video banking solutions can assist your team in serving customers and maintaining business continuity.
6. Tax, Trade & Regulatory Challenges
There are significant tax provisions and other measures to assist businesses that stakeholders should carefully review. Post pandemic, they should think about the broader implications of their business decisions and strategies.
What can you do?
- Business disruption: Develop restructuring plans. Review intra-group service expenses and expense allocations.
- Cash tax savings: Manage cash taxes by potentially reducing taxable income. Obtain available refunds. Work with the treasury function to align repatriation strategies. Model taxable income against the company’s overall tax posture.
- Agile tax models: Supply chains and business strategies need reevaluation, which is best achieved by agile tax models.
- Review all aspects: Stabilize supply chains. Brace for an unpredictable revenue. Reduce costs and increase productivity.
- Meet regulatory obligations: Despite budget constraints, tax compliance requirements must be met. Consider co-sourcing or outsourcing tax compliance.
- Stay informed: Understand the expense of various supply chain configurations and opportunities. Make informed decisions quickly.
7. Crisis Management
Your response to the crisis today can position your business to thrive tomorrow. You need to prioritize incident management along with the safety of workers. It is important for organizations to understand what data is relevant to their business. Some companies are developing new contingency plans while others are using existing ones.
What can organizations do?
- Dedicate a team for crisis management: Ensure that every team member knows what their role is. Train each team member in executing the plan to be sure that they are ready at any moment.
- Establish facts: Strong data reinforces a central element of crisis planning. Establish facts accurately during the crisis. Use the facts to inform your response strategy.
- Collaborate: Collaborate with the public relations team, legal and regulatory teams, and operational and response teams. Create a small core committee from among them.
Focus on tomorrow
The response window for any crisis is measured in months but recovery is measured in years. Create scenarios today to plan for a stronger tomorrow and beyond. Wider and longer-term perspectives can help your business emerge stronger and more sustainable. Data, Readiness, and Empathy are the three vital qualities required to keep people healthy and businesses running. Fingent is closely monitoring the situation and helping businesses return to work with our technology consulting and innovation capabilities. Contact us to know more.