Imarticus Learning – Page 284 – Finance, Tech & Analytics Career Resources

Conversion Rate Optimisation (CRO) Techniques

Posted on June 13, 2023May 14, 2024 by Imarticus Learning

There is various content all over the internet and it is only increasing day by day. This has generated a competition of engagement among different pages to earn more money. The engagement of a page can easily be enhanced with the assistance of content marketing.

This marketing attracts huge traffic to a page which increases the engagement of the content of that page. A page might have various content like videos, blogs, newspaper articles, podcasts, etc. Content marketing also enhances the finances of the business through several brand collaborations and promotions.

However, bringing traffic to a page is only half of the work that is done by any digital marketing expert. The rest work can be performed only if the team can extract more from its present or current traffic so that the company can sustain itself in the long run. This is only possible with the help of Conversion Rate Optimisation (CRO).

Let’s dive in to learn more about Conversion Rate Optimisation!

What is Conversion Rate Optimisation (CRO)?

The method of calculating the percentage of new viewers or fresh traffic to a page so that they can fulfil certain actions is known as Conversion Rate Optimisation or CRO. These actions can be liking a post, signing up for the page or purchasing anything from the website. There can be either a high conversion rate or a low conversion rate.

Many factors are responsible for affecting the conversion rate of a page. If a page is wisely designed, is attractive and has a user-friendly format then it is likely that page would receive a high conversion rate. On the other hand, a page can receive a low conversion rate if it has a poor design or a malfunctioning website.

How to Calculate and Determine a Good Conversion Rate?

Calculating the rate of conversion is extremely simple and requires basic mathematical techniques. In the first step, the number of conversions is divided by the number of viewers or visitors. Subsequently, in the second step, the entire division is multiplied by 100 to extract the percentage.

The final percentage indicates the conversion rate. Here, the meaning of conversion is the desirable actions taken by the viewers.

For example, to calculate the conversion rate of an ebook website, the company should simply divide the total number of downloads by the total number of visitors. Then multiply it by 100.

Importance of Conversion Rate Optimisation (CRO)

Conversion Rate Optimisation is one of the crucial traits when it comes to digital marketing or content marketing. This is because it will assist a company to make more money by simply determining its conversion rate. If a page has a high conversion rate it is likely to earn more revenue than those pages which have low conversion rates.

Conversion Rate Optimisation (CRO) will help a low-rated page to optimise its content so that viewers may have an excellent experience. It will also conduct continuous examinations to provide users with impressive and attractive content. This will gradually help a page to grow physically as well as economically.

Many companies are adopting Conversion Rate Optimisation to grow and sustain icn this competitive sector. Therefore, online ventures must opt for Conversion Rate Optimisation by considering its benefits.

Where is Conversion Rate Optimisation (CRO) Used?

There are several real-life niches where a digital marketing expert can enforce Conversion Rate Optimisation (CRO). Here are a few niches where this technique can be implemented effortlessly:

Home Page: One of the most important niches where CROs can easily work is the home pages. The home page is the main page for any business therefore it must be comprehensive and can be the best guide to further pages.

The conversion rate can be easily increased by simply adding numerous links, chat boxes, sign-up forms, and product descriptions on the home page.

Product Pages: CROs can easily be implemented on the product page. This will assist a business to convert its viewers into potential buyers. To achieve this a product page must contain credibility, authenticity, and detailed descriptions of the selling products.
Landing Pages: The third most crucial niche where CROs can be executed is the landing pages. It is also considered to be the most influential page that has the potential to convert viewers into customers. As the name suggests, Landing pages interact with and attract viewers in the very first instance.

Viewers can be easily converted into customers if landing pages are optimised appropriately. This will assist to flourish the business further.

Various Conversion Rate Optimisation (CRO) Techniques to Enhance the Conversion Rate

There are various Conversion Rate Optimisation techniques. Some of them have been elucidated below:

Blogs encompassing text-based CTAs

To enhance conversion rate through traffic text-based call-to-action (CTA) button acts like a boon. Text-based CTA buttons allow the viewers to carry on with certain actions that the business wants them to. This will automatically boost the conversion rate and will direct towards the path of a successful online business.

Usage of Lead Capture Pop-ups

Lead pop-ups are another technique for Conversion Rate Optimisation. It is highly attractive and once a viewer clicks on the pop-up boxes it will automatically increase the conversion rate.

A/B Tests should be conducted on the Landing Page

To optimise a landing page businesses can conduct A/B tests. This test will recognise the best content for the new viewers and will increase the conversion rate.

Making use of Chat Box to Interact with the Customers

The live chat box is another way a business can increase its conversion rate. Chat Box will guide and assist viewers which will automatically increase the activity on the page. This will result in positive growth of the website.

Conclusion

In the present era, it is essential to know about Conversion Rate Optimisation and its techniques before commencing a career as a digital marketing expert. Therefore, Imarticus Learning has brought an online postgraduate programme in digital marketing. This course will incorporate an individual with the essential knowledge and skills.

So without any further delay enrol yourself in this course so that you do not miss out on big opportunities.

Analytics and Visualisations for Businesses: Getting the Most Out of Data

Posted on June 12, 2023April 2, 2024 by Imarticus Learning

What is Data Analytics?

Data analytics involves acquiring, arranging, evaluating, and transforming diverse raw data into comprehensive insights to enhance a business’s or organisation’s operational efficiency and performance.

This multifaceted approach comprises distinct phases:

Data categorisation: Grouping data based on various parameters, such as demographic factors (e.g., age, gender, income).
Data acquisition: Gathering data from diverse sources, including computer systems, cameras, personnel within companies/organisations, and more.
Data structuring: Organising data utilising spreadsheets or specialised software to help ensuing analysis.
Data cleansing and preparation: Ensuring the accuracy, consistency, and elimination of errors or duplicates, enabling analysts to start the data analysis process.

What Are the Types of Data Analysis Techniques?

Data analysis encompasses four categories: descriptive, diagnostic, predictive, and prescriptive. These analyses enable businesses to make informed decisions.

Descriptive analysis

The descriptive analysis focuses on understanding past events or trends. It provides insights into sales volumes, fluctuations, and other relevant information without delving into causality.

Diagnostic analysis

The diagnostic analysis aims to uncover specific outcomes or events’ root causes or factors. It investigates reasons for sales increases or decreases, such as seasonal patterns or marketing campaigns.

Predictive analysis

The predictive analysis leverages statistical techniques and data mining to forecast future outcomes or trends. It creates visual representations to help understand and inform decision-making.

Prescriptive analysis

The prescriptive analysis offers recommendations based on predictive analysis outcomes. It suggests specific actions to take and assesses the potential implications of those actions.

What Are the Components of Data Analytics?

Data analytics elements cover various techniques for processing data. They include:

Text analysis: Text analysis involves analysing large volumes of text to develop algorithms. It is applied in autocorrect features, linguistic analysis, and pattern recognition, such as in Microsoft Word.

Data mining: Data mining focuses on extracting valuable insights from vast datasets. It helps identify behavioural patterns in clinical trials and breaks down large data chunks into smaller, purposeful segments.

Business intelligence: Business intelligence is a vital process for successful enterprises. It transforms data into actionable strategies, guiding decisions like product placement and pricing to drive commercial success.

What is Data Visualisation?

Data visualisation involves presenting information, such as graphs or maps, to improve understanding and extract insights from data. Its primary aim is to ease the identification of patterns, trends, and anomalies within large datasets.

Data visualisation is often used with terms like information graphics, information visualisation, and statistical graphics.

Within the data science process, data visualisation is a crucial step. Once data is collected, processed, and modelled, visualising it enables drawing meaningful conclusions.

Additionally, data visualisation is a component of the broader discipline of data presentation architecture (DPA), which focuses on identifying, manipulating, formatting, and delivering data.

What Are the Types of Data Visualisation Techniques?

Visualising data can range from simple bar graphs and scatter plots to robust analyses comparing variables like the median age of the United States Congress to that of Americans.

Some common data visualisation types include:

Table: Data organised in rows and columns, created in Word documents or Excel spreadsheets.

Chart or graph: Data presented in tabular form with values plotted along the x and y axes, using bars, points, or lines to represent comparisons. Infographics combine visuals and words to illustrate data.

Gantt chart: A timeline-based bar chart that visualises tasks and their duration in project management.

Pie chart: Data divided into slices representing percentages, combining to form a whole (100%).

Geospatial visualisation: Data displayed on maps using shapes and colours to highlight relationships between specific locations, such as choropleth or heat maps.

Dashboard: Business-focused display of data and visualisations, providing analysts with an overview and deeper insights.

Each visualisation type serves different purposes, aiding in data understanding, analysis, and presentation.

What Are the Advantages of Data Analytics and Visualisation?

Data analytics and visualisation play vital roles in the business decision-making process, offering many benefits:

Enhanced decision-making: Using skilled data analysts and appropriate software, companies can identify market trends and make informed decisions to boost sales and profits.

Deeper insights: Data analytics and visualisation enable companies to gain valuable insights into their customer base. Businesses can better understand clients’ preferences and behaviours by breaking down large datasets.

Improved productivity and revenue growth: By analysing data, companies can identify areas for investment and process automation, leading to improved efficiency and revenue growth.

Real-time market behaviour monitoring: With real-time data analytics and visualisation dashboards, stakeholders can identify changes in market behaviour and adapt their strategies.

Market analysis: Data analytics and visualisation techniques allow companies to analyse different markets, enabling informed decisions on which markets to focus on and which to avoid.

Business trend analysis: Data analytics and visualisation enable businesses to examine present and past trends, facilitating predictions and guiding future strategies.

Data relationships: By exploring data relationships, companies can uncover valuable insights and make informed decisions based on these findings.

What Are the Differences Between Data Analytics and Data Visualisation?

Data visualisation and data analytics are distinct careers with differences in how they work with large datasets and communicate their findings.

Data use

Data analysts study datasets with a specific purpose, drawing conclusions and making predictions based on the data. They provide recommendations and insights to decision-makers in organisations.

Data visualisation experts focus on presenting data visually to improve understanding. They don’t reach conclusions or make predictions themselves but translate the findings of data analysts into visually appealing and understandable formats.

Communication methods

Data analysts primarily communicate through written and oral reports, conducting in-depth analyses of their research questions. Their reports include the question, methodology, and findings of their analysis.

Data visualisation experts present their reports using graphs, charts, and visual aids, simplifying complex data into easily understandable visuals. Their presentations often consist of a series of visual aids without providing direct conclusions or recommendations.

Conclusion

Businesses and organisations can make informed choices based on analysed data by using the power of data analytics and visualisation, improving performance and profitability.

Businesses can identify the value of their collected data using a data-driven approach, making it a significant advantage they should consider.

Embark on a data-driven career journey with Imarticus Learning’s online BBA course in Business Analytics by Geeta University.

Gain comprehensive data visualisation and analytics skills to make informed decisions and excel in business. Start shaping your future today!

Visit Imarticus Learning for more information on our BBA in Business Analytics program.

Leveraging Financial Data for Business Intelligence and Insights

Posted on June 12, 2023April 2, 2024 by Imarticus Learning

In today’s rapidly evolving business landscape, the ability to create informed decisions is crucial for organisations to stay onwards of the competition. Leveraging financial data for business intelligence has become a strategic imperative, enabling companies to win valuable insights and work data-driven decisions.

Financial information serves as the backbone of business intelligence, providing organisations with a comprehensive savvy of their financial wellness, execution, and potential opportunities. By analysing financial data, businesses can expose valuable insights that can drive strategic preparation, optimise operations, and heighten overall performance.

In this article, we will explore the importance of financial information for byplay intelligence and how it can be effectively very used to drive growth and success.

Importance of Financial Data for Business Intelligence

Understanding the Role of Financial Data

Financial information encompasses various types of information, including revenue, expenses, assets, liabilities, and cash flow. It offers a snapshot of a company’s financial position and execution over a specific period. By analysing this data, organisations can assess profitability, liquidity, solvency, and efficiency, among other key financial metrics.

Extracting Insights from Financial Data

Financial data analysis enables businesses to describe patterns, trends, and correlations that may not be patent at first glance. By applying analytical techniques, such as ratio analysis, trend analysis, and financial modelling, organisations can gain valuable insights into their financial execution and identify areas for improvement.

Sources of Financial Data

To leverage financial data effectively, organisations must have access to reliable and accurate data from various sources. These sources can be broadly classified into internal and external sources.

Internal Sources

Internal sources of financial information include a company’s accounting systems, financial statements, and dealings records. These sources provide really detailed information almost the organisation’s financial activities, such as sales, expenses, investments, and cash flows.

External Sources

External sources of financial data encompass industry reports, market research, economic indicators, and publicly available financial statements of other companies. By incorporating external data, businesses can gain a broader perspective on market trends, competitor analysis, and industry benchmarks.

Collecting and Analysing Financial Data

To derive meaningful insights from financial data, organisations need to adopt effective data collection and analysis methods.

Data Collection Methods

Data assemblage can involve manual processes, such as data entry, or automated systems that captivate financial data in real-time. Automation, through the use of accounting packages, financial management systems, and information desegregation tools, can significantly streamline the collection process and ensure accuracy.

Data Analysis Techniques

Analysing financial data requires the application of various techniques, including statistical analysis, information visualisation, and predictive moulding. These techniques enable organisations to distinguish trends, anomalies, and relationships within the data, facilitating the best decision-making.

Benefits of Leveraging Financial Data for Business Intelligence

Utilising financial data for business intelligence offers several benefits that contribute to the overall success of an organisation.

Improved Decision-Making

By leveraging financial information, organisations can make informed decisions based on exact and seasonable info. Financial insights provide a solid foundation for strategic provision, imagination allocation, investiture decisions, and evaluating the financial viability of really new initiatives.

Enhanced Financial Performance

Financial information analysis enables organisations to identify inefficiencies, cost-saving opportunities, and revenue ontogeny potential. By optimising operations and resource allocation based on these insights, businesses can improve their financial execution and profitability.

Risk Management

Financial data analysis helps organisations place and mitigate potential risks by assessing factors such as liquidity, solvency, and cash stream. By proactively monitoring key financial indicators, businesses can take measures to denigrate risks and ensure long-term stability.

Identifying Market Trends

Financial data analysis allows organisations to identify market trends and customer behaviour patterns. By understanding market dynamics and customer preferences, businesses can tailor their products and services to meet evolving demands, gaining a competitive advantage.

Financial information analysis allows organisations to identify marketplace trends and client doings patterns. By understanding market kinetics and customer preferences, businesses can sort their products and services to meet evolving demands, gaining a competitive advantage.

Challenges and Solutions in Utilising Financial Data

While leveraging financial data offers significant advantages, organisations may encounter challenges that need to be addressed to ensure effective utilisation.

Data Security and Privacy

Financial information is highly sensitive and subject to strict regulatory requirements. Organisations must implement robust information security measures and bind to data shelter laws to safeguard raw financial information.

Data Quality and Accuracy

Inaccurate or incomplete financial information can lead to flawed analysis and wrong decision-making. Organisations should give information quality controls, implement data substantiation processes, and ensure data accuracy through habitue audits and reconciliations.

Data Integration

Financial data is often scattered crossways various systems and departments within a system. Integrating information from really different sources can be really complex and time-consuming. Implementing information integration solutions and adopting standardised data formats can streamline the process and ensure information consistency.

Future Trends in Financial Data Analytics

As technology continues to advance, financial data analytics is expected to witness further advancements and innovations. A few emerging trends in the field include:

Artificial Intelligence (AI) and Machine Learning (ML) algorithms for predictive analytics and anomaly detection.
Natural Language Processing (NLP) for automating financial reporting and analysis.
Blockchain technology for enhancing the security and traceability of financial data.
Cloud-based financial data management and analysis solutions for scalability and accessibility.

Conclusion

Leveraging financial data for business intelligence is no thirster an option but a requirement for organisations striving for success in today’s competitive landscape. By effectively collecting, analysing, and interpreting financial information, businesses can gain worthwhile insights that drive informed decision-making, enhance financial execution, and mitigate risks. Embracing rising trends and technologies in financial data analytics can further unlock very new opportunities and assist businesses to rest really ahead of the curve.

If you’re interested in pursuing an Online MBA program specialising in Fintech, consider exploring Geeta MBA in Fintech. By enrolling in Imarticus Learning’s MBA In Fintech, you can gain the skills and knowledge needed to excel in this exciting field.

Visit Imarticus Learning to learn more.

Agile Marketing: Adapting to Rapidly Changing Market Conditions

Posted on June 12, 2023April 4, 2024 by Imarticus Learning

How effectively is your business riding the waves of change? Agile businesses demonstrate a remarkable ability to swiftly adapt to shifting market conditions and proactively overcome challenges. Equipped with the necessary tools, they conquer the ever-evolving business landscape and cater to the ever-changing needs of customers in the digital age. Agility empowers businesses not only to compete but to thrive in the midst of dynamic markets.

If you are an individual aspiring to pursue a CMO program with the intention of propelling your business toward unparalleled success, then this blog is tailor-made for you.

What is agile marketing?

Agile marketing refers to a marketing approach that leverages the principles and techniques derived from agile methodologies. It involves the formation of self-organising, cross-functional teams that engage in iterative work cycles accompanied by continuous feedback. Agile marketing necessitates both a strategic vision and the development of marketing plans spanning short, medium, and long-term objectives.

Agile marketing distinguishes itself from traditional marketing through various key aspects. Such as:

Emphasis on frequent releases

Agile marketing places great importance on regularly delivering marketing initiatives, campaigns, or updates to maintain a proactive and adaptable approach.

Embracing deliberate experimentation

Agile marketing encourages a mindset of experimentation, where marketers actively test and explore new ideas, strategies, and tactics to uncover what works best for their target audience.

Unwavering commitment to audience satisfaction

Agile marketing centres around continuously satisfying the needs and preferences of the target audience, focusing on their feedback, and making necessary adjustments to ensure maximum customer satisfaction.

The agile marketing manifesto outlines several values that embody agile marketing, such as:

Agile marketing prioritises customer value and business outcomes over mere activity and outputs.
Agile marketing emphasises delivering value early and frequently instead of waiting for perfection.
Learning through experiments and data is valued over-relying on subjective opinions and traditional conventions.
Agile marketing promotes cross-functional collaboration, breaking down silos and hierarchical barriers.
Responding to change is valued over following a static plan.

Furthermore, it’s important to note that while each agile marketing implementation may differ based on the organisational context in which it is adopted, there are multiple key characteristics shared by all versions of agile marketing.

What is the significance of organisations adapting to ever-changing business environments?

The current business landscape is undergoing significant changes on a global scale, leading to increased complexity and volatility. These changes encompass various aspects such as environmental concerns, the recent COVID-19 pandemic, and specific challenges like rising inflation and escalated customer living costs in the UK.

Industries, economies, and societies are being reshaped constantly with the rise in digitalisation, posing a challenge for businesses to adapt to rapid changes. In this dynamic environment, adopting an agile approach is crucial for organizations to effectively respond. It requires embracing innovation, flexibility, and the ability to swiftly adjust operations and strategies to meet evolving market needs.

This not only enhances a business’s capability to handle unpredictable circumstances but also cultivates resilience in the face of uncertainty which is a must-need quality to become a CMO.

Strategies for attaining business agility

Business agility is the ability of a business to promptly and efficiently adapt to technological advancements, customer requirements, and employee expectations. To attain business agility, organisations should concentrate on the following fundamental elements:

Cultivating a flexible culture

Encouraging a flexible culture empowers employees to take ownership of their tasks and make swift decisions in response to evolving demands. This can be accomplished by fostering collaboration between departments and breaking down barriers.

Establishing efficient processes

Defining well-structured procedures enables employees to respond rapidly and effectively to changes. It is also important to regularly review and update these processes to keep pace with the latest trends.

Harnessing technology

Technology plays a vital role in enhancing operational efficiency and agility. For instance, organisations can utilise cloud-based tools and applications to facilitate collaboration, automate tasks, and obtain real-time analytics.

Integrating agility into corporate culture

Embracing agility requires more than just adopting technical solutions; it necessitates a cultural shift. All stakeholders should understand the significance of agility and the need to respond swiftly to change. This involves investing in employee training and effectively communicating the importance of agility at all levels of the organisation.

By focusing on these four key elements, organisations can create an environment that enables them to promptly and effectively adapt to market changes. The outcome is an agile company that remains competitive and achieves its objectives more quickly.

How to implement business agility?

In today’s rapidly changing environment, maintaining competitiveness requires businesses to have strong business agility. Establishing an agile workplace involves addressing various internal and external aspects of the business, encompassing employees, customers, technology, and processes. Consider the following recommendations for fostering an agile workplace.

Embrace change

Organisations should be ready to embrace change and swiftly adapt to evolving customer needs and market trends. Equipping employees with appropriate tools and resources enables them to effectively manage their work and adapt to the changing environment.

Prioritise quality

Companies must prioritise delivering high-quality products and services while providing reliable support to both customers and employees. Quality is a dealbreaker in any strategy looking to promote business agility.

Leverage technology

By leveraging technology, businesses can automate numerous tasks, freeing up employees’ time to focus on more significant responsibilities. Utilising technologies such as artificial intelligence, machine learning, and automation streamlines processes and enhances overall efficiency.

Foster a learning culture

Encourage a culture of continuous learning within the organisation. Offer employees opportunities for training, workshops, and conferences to ensure they stay updated with industry trends and developments.

Enhance processes

To meet customer demands effectively, companies must consistently evaluate and improve existing processes and develop new ones when necessary. Striving to minimise bottlenecks in processes enhances efficiency and effectiveness.

By implementing these suggestions, businesses can establish an agile workplace capable of promptly adapting to shifting trends and customer requirements. Such an environment will enable businesses to maintain their competitive edge in today’s fast-paced world.

Why is it crucial for modern CMOs to embrace agility and innovation?

In today’s business landscape, it is essential for modern CMOs to wholeheartedly adopt agility and innovation. According to Fortune magazine, CMOs are expected to possess expertise in driving brand growth and market dynamics while maintaining an external perspective. This enables them to promptly respond to the ever-evolving market conditions and ever-changing customer expectations.

CMOs find themselves in a constant struggle as initiatives face potential failure, markets undergo transformations, customers switch preferences, organisational structures undergo shifts, and technologies rapidly advance. They are continuously challenged by disruptive changes that seem to come in endless waves.

To navigate this challenging environment successfully, CMOs must embrace innovation and agility as indispensable tools. By relying on these qualities, they can effectively adapt and remain buoyant amidst the sea of unceasing change.

Conclusion

Embracing agility allows businesses to maintain a competitive edge and achieve long-term success. By cultivating the appropriate mindset and implementing effective strategies, organisations can swiftly and efficiently attain the desired level of agility.

If you’re looking to enhance your skills as a Chief Marketing Officer (CMO), one option to consider is the Executive Certificate Program for Chief Marketing Officers by Imarticus in collaboration with the IIM Indore CMO course. This program helps you elevate your expertise and proficiency in the field of marketing.

Robotic Process Automation (RPA) in Procurement and Supply Chains

Posted on June 12, 2023April 4, 2024 by Imarticus Learning

RPA, or Robotic Process Automation, is a technology that automates repetitive and rule-based tasks using software bots. These bots mimic human actions and interact with digital systems to perform tasks like data entry and report generation.

RPA enables the automation of tasks such as order processing, shipment scheduling, logistic management, and invoicing, leading to improved logistics performance and cost reduction.

The Advantages of RPA for Modern Supply Chains

RPA use cases in supply chain management provide lots of benefits to businesses. It is the ultimate solution to improve your online or offline business.

Some of the specific benefits are:

Enhanced Accuracy: RPA eliminates the potential for human errors in data entry and processing. Bots follow predefined rules and perform tasks consistently, improving data accuracy and reliability throughout the supply chain.
Improved Productivity: By automating routine tasks, RPA boosts productivity by reducing the time and effort required. It enables supply chain teams to handle increased workloads, meet tight deadlines, and achieve higher output levels.
Scalability: RPA can quickly scale to accommodate fluctuations in demand or business growth. RPA helps supply chains handle increased volumes without the need for significant additional resources.
Cost Savings: By automating manual tasks, RPA reduces labour costs and decreases the likelihood of errors or rework. It also optimises resource utilisation, leading to cost savings in the long run.

RPA-Automated Supply Chain Processes

Robotic Process Automation (RPA) has revolutionised various industries by automating critical processes in the supply chain.

Let’s see how RPA has aided in automating processes across different sectors:

Order Processing and Payments: RPA streamlines order processing by automatically extracting sales order data from multiple sources such as emails, faxes, and EDI. It eliminates data entry errors and simplifies order entry and fulfilment by managing complex business rules.
Onboarding of Partners: RPA simplifies the onboarding process by creating intelligent bots that synchronise and automate the onboarding of new goods and services from partners. It helps streamline the integration and collaboration with suppliers and other business partners.
Shipment Scheduling and Tracking: RPA automates scheduling and tracking shipments by automating data entry, applying relevant conditions for scheduling, and assigning unique IDs for tracking purposes. It improves efficiency and accuracy in managing the shipment process.
Invoicing: RPA facilitates invoicing by automating data entry, extraction, and calculation tasks. It ensures accurate and efficient invoicing processes, reducing manual errors and improving overall efficiency in financial transactions.
Procurement and Inventory: RPA automates procurement and logistic management processes by automatically updating data entries and utilising unique identifiers to track and manage goods efficiently.
Supply and Demand Planning: RPA supports supply and demand planning by automating data updates and streamlining the process of managing new goods entries. By leveraging RPA, organisations can forecast demand more accurately and efficiently, improving customer satisfaction.
Customer Services: RPA improves customer service by enabling quick and efficient responses to customer requests and demands. By automating receiving and addressing customer inquiries or interest changes, organisations can deliver timely and attentive service, enhancing overall customer satisfaction.

Implementing an RPA Program in Your Supply Chain

Implementing an RPA program in your supply chain can bring numerous benefits, such as increased efficiency, cost savings, and improved accuracy.

Here are the key steps to consider when implementing an RPA program in your supply chain:

Identify Suitable Processes

Start by identifying the supply chain processes that are repetitive, rule-based, and prone to human errors. These processes are ideal candidates for automation through RPA.

Conduct Process Analysis

Analyse the identified processes to understand their steps, dependencies, inputs, and outputs. Document the existing workflows and identify any pain points or areas for improvement.

Prioritise Processes

Prioritise the processes based on their potential impact, complexity, and feasibility for automation. Begin with smaller, less complex processes to gain experience and build momentum before tackling more critical or intricate processes.

Engage Stakeholders

Involve key stakeholders from IT, supply chain, and relevant departments in the implementation process. Seek their input, insights, and buy-in to ensure the successful adoption of RPA in the supply chain.

Select RPA Tools

Evaluate and select suitable RPA tools that align with your supply chain requirements. Consider factors such as ease of use, scalability, compatibility with existing systems, and support for process integration.

Develop RPA Solutions

Work closely with RPA developers or experts to design and develop automation solutions for the identified processes. Collaborate to create bots to perform the desired tasks, integrate with relevant systems, and handle exceptions effectively.

Test and Validate

Thoroughly test the RPA solutions to ensure they function as intended and deliver the expected results. Validate the automated processes’ accuracy, reliability, and efficiency before deploying them in the live environment.

Train and Educate Employees

Provide training and education to employees who will manage and oversee the RPA program. Help them understand the benefits, purpose, and functionalities of RPA and address any concerns or misconceptions.

Monitor and Optimise

Continuously monitor the performance of the implemented RPA program and gather feedback from users. Identify opportunities for further optimisation, refine processes as needed, and make adjustments to maximise the benefits of RPA in your supply chain.

Scale and Expand

Once you have successfully implemented RPA in selected processes, consider scaling and expanding the program to cover other functions in your supply chain. Use the insights and lessons learned from initial implementations to guide future deployments.

Supply Chain Challenges for RPA

Supply chains encounter several challenges when implementing Robotic Process Automation (RPA). Some of them include:

Data Integration: Integrating data from several systems, including enterprise resource planning (ERP) and logistic management systems, can be complex. RPA installations need seamless data connectivity for decision-making and automation to guarantee accurate and current information.

Exception Handling: Supply chain processes often encounter exceptions or deviations from the standard workflow. Handling these exceptions and developing automation solutions to address them can be complex, as they may require human judgment and decision-making.

Change Management: Introducing RPA in the supply chain requires change management efforts to address potential employee resistance. It involves educating and training employees on the benefits of automation and addressing any concerns about job security or changes to their roles and responsibilities.

Process Standardisation: RPA implementations work best when processes are standardised and well-defined. In cases where supply chain processes vary across locations or departments, standardising procedures may be necessary before implementing automation.

Conclusion

Robotic Process Automation (RPA) holds immense potential in transforming procurement and supply chains. By leveraging RPA, organisations can achieve increased efficiency, enhanced accuracy, improved productivity, and streamlined processes.

RPA plays a crucial role in logistic management, enabling supply chains to optimise operations, respond to customer demands, and gain a competitive edge in the market.

To further enhance your expertise in Supply Chain Management and understand the application of RPA in procurement and supply chains, consider enrolling in Imarticus Learning’s Digital Supply Chain Management With E&ICT, IIT Guwahati course.

This Supply Chain Management certification course offers all the necessary knowledge and skills that you will need to excel in the digital era. Visit Imarticus Learning for more information.

Network Optimisation for Efficient Distribution

Posted on June 12, 2023April 5, 2024 by Imarticus Learning

An efficient distribution network is the heart of a successful supply chain. In today’s world, companies that are operating on e-commerce platforms are gaining a competitive edge with better logistics and distribution networks. When we speak about distribution network optimisation, we mean the availability of enough distribution centres at locations in proximity to delivery points and adequate numbers of vehicles to transport the materials there.

Network optimisation is also required for the time taken in loading and unloading materials and during planning the inventory for each distribution centre. All these may be achieved by strong sales and operation planning.

Factors Affecting Distribution Network

Some of the factors which affect the distribution network are as follows –

Customer analysis

The demand volume history and financial credibility of the buyer need to be researched. Simultaneously the payment cycle or policy of the customer also needs to be assessed.

Analysis of suppliers

Purchase order history and logistic details of suppliers are to be monitored. Besides this, the commitment to quality and timeliness of supply needs to be maintained.

Inventory assessment

The inventory assessment for each distribution point should be prepared. Inventory management should be considered keeping in mind the sudden upsurge in demand.

Financials

Cash flow, capital investment, availability of working capital, legal obligations etc. are to be monitored. At the end of the day, the objective of any organisation is to make a profit out of a business.

Trade zone analysis

Preparing a detailed report on geography with a proposal for a new distribution centre is essential. It needs to be checked whether the benefits of a free trade zone are available or not. Marketing potential also needs to be reviewed.

Sales and Operation Planning

Before setting up an efficient distribution network, any manufacturer should have a master plan for its sales and operation. The planning should be aligned with the demand and supply of its products and its financial planning.

Strategic decisions of the sales team include elements like whether the demand for a product in a specific geography should be more than it was in the last year or whether this demand should shift to a more promising geography. These strategic sales decisions influence tactical operational decisions like whether to increase or reduce the production capacity and manpower. Other long-term vendor management policies are also determined accordingly.

All these planning parameters are to be backed up by strong financial planning or budget. There are several challenges to a proper error-free sales and operation planning process. They are as follows –

Zeroing down on accurate information regarding supply and demand at a given point in time is a rigorous task.

In cases where demand shifts significantly from its previous earlier values, sales and operation plans need to be amended with the approval of top management.

Making a presentation to the top management incorporating all real and assumed parameters for the purpose of decision-making is challenging. Assimilating a database from multiple systems for making visible interactive reports is a complex activity.

Planning for new products as a result of demand shift or merger and acquisition of companies leads to newer hurdles for the team.

The latest technology trends have been incorporated into the sales and operation planning exercise. The usage of Enterprise Resource Planning (ERP) software and Supply Chain Management (SCM) software have become quite common nowadays. Besides the above-mentioned, Artificial Intelligence (AI) and the Internet of Things (IoT) have been introduced.

Supply Chain Design

A real ground working model that elaborates on the structures or distribution outlets of the supply chain and the available logistics network for calculating the time and cost to deliver goods to the market is loosely understood as supply chain design. The model points out the errors committed in the system during the planning stage and flags potential risks involved in the process under different given conditions.

It aims towards reducing inventory, working capital and logistics costs and, in turn, increases operational efficiency, transparency and cost savings. The design model also aims to match supply to its demand under uncertain business scenarios by leveraging on its efficient inventory management skills.

It deals with strategic parameters like the number of distribution centres, location and size of the centres and deals with all global and domestic sourcing strategies. The design model is fully equipped to respond to all possible “what if” scenarios. It also has the flexibility to adjust to any shift in strategic decisions due to changes in the supply-demand curve.

Tips for Maintaining an Optimised Distribution Network

Optimising the distribution network is an ardent activity. Dynamic business conditions and varying parameters make the task difficult. However, a few tips may be followed to optimise the distribution network. They are as follows –

Early engagement of top management of business owners and other stakeholders is a must-do-thing. A high-level meeting regarding network optimisation at the beginning clarifies many issues, which otherwise could have posed a serious threat due to wrong assumptions.

The meeting should be done in the presence of cross-functional leaders from both sides so that several overlapping functions get clarity right at the very beginning. All the parameters affecting network distribution should be chalked out and debated in a thread-bare manner.

The usage of commercially available modelling tools is better to tackle complex problems than homegrown spreadsheets. The model should be flexible to record all relevant parameters and able to show visually a tangible solution.

Inventory distribution should be the top planning criterion.

A study or research on network distribution typically takes three to six months’ time. Organisations must allow this time for a stress-free operational experience in future.

Conclusion

The supply chain management system has come a long way. A supply chain analytics course equips a prospective candidate with all the lessons to be learned. The candidates may find lucrative placement offers in the port and logistics companies besides other opportunities.

The Professional Certification in Supply Chain Management and Analytics by Imarticus will enable the prospective candidate to boost their career towards a bright future. With the help of this supply chain analytics course, the candidates learn job-relevant skills from experienced IIT faculty.

Visit the official website of Imarticus for more course-related details.

Lean Management for Emerging CFOs: Streamlining Processes and Eliminating Waste

Posted on June 12, 2023April 2, 2024 by Imarticus Learning

Lean management has become a very popular domain in recent years and is being used in a lot of work areas. Lean management has also become an integral part of the financial industry and it is extremely important for finance professionals to know the concept and applications of lean management. One can learn everything about lean management with an effective CFO course that will help professionals to become successful CFOs in the future.

Every business process either adds some value to the organisation or generates some kind of waste. The main objective of involving lean management in business processes is to eliminate anything that results in waste and increase the operations that add value to the business. Eliminating waste has proven to be effective in improving product quality while lowering manufacturing time and expenses.

Read on to know how lean management can help emerging CFOs in streamlining business processes and eliminating waste.

What are the Wastes of Lean?

Lean management always tries to make business processes as efficient as they can be. Here, efficiency is about achieving the target objectives and reaching the peak performance of the business by optimal use of resources. It helps to add value to the organisation as well as reduces the amount of waste generated. Eliminating waste in lean management allows companies to yield the highest output with just the right amount of resources.

Waste in lean management is said to be operational and accounting waste that can be categorised as follows:

Inventory

An important aspect of eliminating waste in lean management is to do away with excess inventory. Keeping more than the required inventory results in over utilisation of resources and capital. In terms of production, keeping excess inventory in hand results in wastage of the products as they may get absolute or damaged. Hence, the amount of inventory should be kept as per requirement.

In the case of deduction analysts, the best way is to eliminate the inventory of invalid deductions so that the system must be capable of robust classification of deductions into various categories.

Transportation

In manufacturing and production, transportation is about providing the data to the concerned individuals and rightly extracting information from various spreadsheets and databases. The major waste in transportation is spending a lot of time retrieving information about Proof of Delivery. Such documents should be available at hand and not much time should be spent on collecting this information.

Deduction analysts devote almost 60% of their time to classifying deductions and carrying out backup retrieval whereas more time should be invested in investigating and validating deduction claims.

Overproduction

Overproduction means producing more items than the consumer has ordered and it is considered as a waste activity in manufacturing. There is no point in spending time, effort and resources introducing more than the actual order amount. Hence, overproduction needs to be eliminated for building an effective lean management system.

Poor forecasts of market demand can lead to overproduction and poor automation is a major cause of this calamity. Analysts need to prepare proper production schedules as per the results of conducting a thorough analysis of the market.

Waiting

Sometimes, business processes are not optimally synchronised with each other and create a lot of waiting time. It is a waste of time which results in unproductiveness. waiting time is a result of improper synchronisation of two business processes that should have occurred one after the other.

Poor planning of layouts and processes is the major cause of waiting time. Managers need to optimise and connect the business processes in a manner that leads to minimum or no waiting time. Output will be standardised and no wastage of resources and time will occur.

Over-processing

Over-processing is when any product is given more attention than a consumer value. According to the lean management strategy, only the required amount of processing should be done on a product, neither less nor more. Overprocessing an item does not add any value to the business and only results in a waste of time and resources.

The major cause of processing is unnecessary manufacturing steps and the absence of standard procedures. Hence, analyse what the customer wants and invest keeping in mind what the customer is willing to pay for an item.

Excess motion

The movement of all products and equipment should be done in the easiest and the most convenient way possible. But many times the movement of products takes place without analysing the easiest way possible. It causes immense wastage of resources.

Excessive motion in the business process involves huge expenses, labour and time. The major form of motion waste in businesses is the expenses incurred for lifting heavy items, doing a lot of paperwork, etc. Companies should try to simplify and optimise business processes and minimise the motion of equipment as much as possible. Motion waste results in delays in the completion of work and disrupts the progress of work.

Defects

The most obvious kind of waste that can be eliminated with lean management is the defects and errors in the business procedures. A defective item requires replacement or repair which creates additional pressure on the organisation and leads to a poor customer experience. As a result of which the company loses view of their valuable customers.

Inefficient machinery and management systems can be a major cause of these defects. Additionally, human errors cannot be neglected either. It is always better to minimise the occurrence of defects than to repair them later. Better quality control can be exercised with the help of a lean management system that can do away with such defects.

Conclusion

Eliminating waste and streamlining business processes is a major objective of lean management systems. It is also a great means of performing capital budgeting and setting the workflow just as it should be without any delays. Is important to know what exactly is causing the waste and then start working towards eliminating it.

Lean management is an inseparable part of the financial industry and if you want to become a successful CFO in the future, it is a must for you to have in-depth knowledge of line management. Consider signing up for the Postgraduate Certificate Programme for Emerging CFOs by Imarticus and inculcate the essential skillset. Measuring the waste in a business and getting rid of the same is a great way of ensuring optimal use of resources and building a lean management system in the company.

Incident Response and Management in Cybersecurity

Posted on June 12, 2023November 28, 2023 by Imarticus Learning

The strategies and processes that firms use to recognise, address, and recover from cybersecurity events, including data breaches, cyberattacks, and system failures, are called incident response and management in cybersecurity. A component of event management, incident response refers to how an organisation deals with cyberattacks on a large scale and with various stakeholders from the executive, legal, HR, communications, and IT departments. A cybersecurity expert provides valuable insights and recommendations to improve the incident response and management processes, making the organisation better prepared for future security incidents.

In today’s digital environment, cybersecurity risks are growing increasingly prevalent. Cybersecurity events can vary from minor security lapses to big data breaches that can seriously impact a company’s standing and bottom line. Therefore, companies need to have an incident response and management strategy to lessen the effects of such accidents.

Incident response and management in information security needs strong coordination between IT teams, security specialists, legal departments, and senior leadership to guarantee a rapid and efficient reaction to occurrences.

Steps in the Incident Response Process

The incident response process typically involves the following steps:

Preparation: Examples of preparation include creating an incident response strategy, selecting the incident response team, and conducting training and test exercises.
Identification: Finding and confirming that an event has happened.
Containment: Limiting the incident’s scope and effects is known as containment.
Analysis: Identifying the origin and extent of the phenomenon
Remove: Remove the incident’s returns, and everything to normal.
Recovery: Assuring that normal operations have resumed and the problem has been satisfactorily fixed.

Key terms and concepts related to incident response and management

Incident response plan: A written, systematic process that explains how a company should respond to a cybersecurity problem.
Incident response team: A team responsible for planning and reacting to security events like cyber-attacks, data breaches, and systems failures.
Issue reaction process: The group of measures done by a company to answer a cybersecurity issue.
Cybersecurity incident: An event that undermines the confidentiality, integrity, or availability of an organisation’s computer assets.
Cybersecurity incident management: How cybersecurity, DevOps, and IT professionals identify and react to issues in their business.

Incident Response Frameworks

Businesses employ an incident response framework, a structured process, to recognise, address, and resolve cybersecurity issues. It frequently involves several procedures: preparation, detection and analysis, seclusion, eradication, and complete recovery. Incident response frameworks from NIST, ISO, ISACA, and SANS are just a few of the options accessible.

The four steps covered by the NIST framework are preparation and prevention, detection and analysis, containment, eradication, recovery, and post-incident operations. Preparation, identification, containment, eradication, and recovery are all covered under the SANS framework.

Incident Response Plan

An incident response plan is a document that outlines the procedures, steps, and duties of an organisation’s incident response program. The following information is frequently included in incident response planning:

How incident response contributes to the organisation’s overall mission
The organisation’s incident response strategy
The activities needed for each incident response phase
Roles and responsibilities for carrying out IR activities
Communication channels between the incident response team and the rest of the organisation
Metrics to measure the effectiveness of its IR capabilities.

Incident Response Team

During a cybersecurity crisis, an incident response team is responsible for assembling and aligning the necessary team members and resources to minimise damage and restore operations as soon as possible.

The team’s objectives include research and analysis, communication, awareness-raising, training, schedule formulation, and documentation. The team should detect and categorise security occurrences based on asset value and impact, maintain track of and educate team members on proper reporting processes, and assemble relevant data to assist incident response efforts.

Goals of Incident Management and Response

The goal of incident management and response is to quickly resume operations and reduce the impact of a cyber catastrophe. The main purpose of incident management is to deal with situations by making short or long-term repairs and restoring the IT service. The following are some of the objectives of incident management and response:

Verify something happened or make sure it didn’t happen
Ensure or reinstate business continuity while reducing the impact of an incident
Determine the cause(s) of the occurrence.
Reduce the impact of upcoming events
Boost security and the purpose of the incident response strategy.
The pursuit of criminal conduct
Inform the relevant clients, staff, and management about the issue and your response.
Utilise what you’ve learned to improve the procedure.

To achieve these objectives, the incident management team should resolve events to decrease downtime to the company, communicate the key incidents’ progress to the appropriate stakeholders, and guarantee SLAs don’t breach for any reason. The incident management team should adopt standardised processes and procedures for effective and rapid response. The primary aims of an incident response technique are to identify, confine, remove, and reduce the time and expense of a cyber intrusion.

Incident Response and Management Best Practices

Here are some best practices for incident response and management:

Prepare systems and procedures: Carry out preventative measures, including fixing system weaknesses and setting security regulations. Create a comprehensive incident response strategy that includes an incident response’s planning, discovery, analysis, control, and post-event cleanup stages.
Manage an event’s lifecycle: Incident response management should include written documents outlining incident response processes. These procedures should include planning, identification, analysis, control, and post-event cleanup to cover the incident reaction process.
Pick the right tools: Businesses should pick the right tools to help them handle challenges. These tools ought to be easy to use, flexible, and scalable.
Automate communication and documentation: Using automation to ensure alerting of all stakeholders and complete recording of the crisis response process may help.
Maintain simplicity: While comprehensive, incident reaction plans must also be easy for staff to understand. A thorough plan could be challenging to implement under pressure.

Conclusion

Incident response and management in information security is a systematic method comprising procedures and tools for detecting, assessing, and responding to cybersecurity occurrences to minimise damage, recovery time, and total costs. Imarticus Learning offers a Post Graduate Program in Cybersecurity, a 6-month extensive programme designed to prepare students for cybersecurity expert, penetration tester, incident handler, and SOC team roles.

The full-time course is designed to assist students in finding lucrative employment in the cybersecurity industry. The course’s curriculum guarantees a job and includes challenging lab work covering subjects like ethical hacking, incident response, and digital forensics.

Image Recognition and Computer Vision: Extracting Information from Images

Posted on June 12, 2023April 4, 2024 by Imarticus Learning

Image recognition is a result of the incredible fusion between artificial intelligence and computer vision that has led to the emergence of this technology. Image recognition software or applications take the help of camera technology and various AI models.

Image recognition technologies can distinguish and identify objects, people, texts and so on by extracting information from the images it captures. The emergence of this technology has revolutionised the industrial platform, be it pharma companies or retail shops and made brilliant opportunities for building a career in data analytics.

How does computer vision help in image recognition?

The role of computer vision is very pivotal in image recognition. It incorporates various processes like Optical Character Recognition (OCR) with the help of which it extracts textual data from images it captures. Two technologies are employed in this case: convolutional neural networks (CNN) and deep learning which generally use Python programming.

With the aid of machine learning, computers can distinguish between images without the necessity of detailed programming. This is done by breaking down images into minute pixels and then making predictions based on that. By undergoing repetitive iterations, the predictions are made more accurate which is almost parallel to human perception.

Using CNN for image recognition

The Convolutional Neural Network inculcates a strong algorithm which it uses for image processing. It uses three different layers for analysing the images namely, Convolutional Layer, Pooling Layer and Fully-Connected Layer.

In the Convolutional Layer, a small portion of input neurons is connected to hidden neurons. The dimensionality of the feature map is reduced by the Pooling Layer which follows the Convolutional Layer. In the end, the Fully-Connected Layer assesses the input data from the previous two layers and helps make assessments through predictions based on memory.

How does image recognition work?

There are a series of steps that are followed to convert images into textual data. These steps include:

Acquisition of image: this is the first step where the image is retrieved from an external source
Enhancement of image: this step involves changing the picture quality for better assessment
Restoration of image: this utilises certain mathematical tools for improving the quality of the image
Multiresolution processing: here the image is divided into smaller wavelets for the compression of data
Morphology-based processing and segmentation: analysis of images is done based on their shapes and then subdivided into smaller individual components
Description and representation: each component is analysed and quantitative information is derived

At the end of these steps, image recognition is made possible where the objects are tagged with a label centred on their characteristic features.

This entire process includes pre-determined signal processing methods which are employed to derive the information from the captured images. These methods include object visualisation, recognition, pattern measurement and so on.

Challenges faced in image recognition

The evolution in image recognition has brought with it several technological advancements. However, the advancements are augmented with various challenges and limitations which need to be overcome. The challenges are as follows:

Model generalisation improvement: the challenge here is to ensure that the system can run well in real-world scenarios that can differ from training and test sets. One finds varying distributions in real-world scenarios like different viewing angles, size of the objects and camera features.
Failure to read small and huge data sets: here the challenge is to enable the system to learn new data by introducing it to small and limited datasets in the beginning and utilising deep learning and machine learning to learn new information and ultimately recognise new objects. Similarly, another challenge here is that the current models lack the efficiency to read huge datasets to perform critical tasks.
Limitations to cognitive understanding: the challenge here is the inefficiency to go beyond just object recognition and achieving a cognitive understanding of objects to interpret inter-relationships between objects like humans to humans, humans to cars and so on.
Limitations to automate engineering of networks: the challenge here is that, instead of focusing on some specific features, the efforts are now to build novel network architectures. However, this is quite a difficult task involving myriads of parameters and choices.

Applications of image recognition

Some of the major arenas where image recognition is used are as follows:

Face Recognition: This is used in surveillance and security works.
Remote Sensing: various sensors are used to extract information about a distant object. This is used in ships, aircraft and satellites to name a few.
Medical sectors: image recognition is being used in image diagnosis of a disease in medical sectors. It is also used in augmenting Computational Tomography (CT) scans and Magnetic Resonance Imaging (MRI).
Processing of Video: it is used to process visual data in television sets and other visual electronic systems.

Conclusion

A massive revolution in the industrial sector has been brought about by the advancements in technologies supporting image recognition and computer vision. Utilising deep learning and machine learning integrated neural connecting systems have been developed which aim at getting much better in the coming days.

However, it has yet to overcome a number of challenges to attain its maximum potential. To gain expertise in such technological backgrounds you can check out Postgraduate Program In Data Science And Analytics provided by Imarticus. This 6-month long program will help data science aspirants with a better chance of securing a career in data analytics with a machine learning certification.

Unlocking the Power of Investment Banking for Small and Medium Enterprises (SMEs)

Posted on June 12, 2023April 4, 2024 by Imarticus Learning

Access to finance is a major concern for small and medium enterprises. They find it difficult to obtain bank loans like large firms do. They mainly have to count on internal funds in order to launch and run their enterprises. SMEs that look forward to improving their capital structure or de-leverage, often face economic crises. This calls for the need to ensure that the capital structures of SMEs are improved and strengthened, and that their dependence on informal borrowing is reduced.

Although banking finance is an important source of financing in the SME sector, credit constraint is likely to become a constraint in the near future. Therefore, it is important to make more financial instruments available in the money market for SMEs so that they do not have to face financial constraints. Read on to learn more about the scope of investment banking in small and medium enterprises.

Traditional Lending to the SMEs

The most common source of funding for SMEs is the traditional methods of lending such as overdrafts, bank loans, credit lines, credit cards, and so on. In this kind of lending, the borrower’s creditworthiness is assessed and he is entitled to pay a certain interest amount to the creditor at a specific interval, disregarding the financial condition of the organisation or the return on investment it is earning. In this case, the interest rate may either be fixed or changeable.

However, traditional bank lending to SMEs can be risky. Monitoring and assessment become a problem since SMEs do not produce any audited financial statement that can provide information on the financial status of the enterprise. In the case of small enterprises, the line between the finances of the business and those of the owner’s personal use is often blurred. It may also happen that the entrepreneur uses the money for some other purpose.

However, to mitigate the problem, it is ideal to incorporate the use of risk management strategies like mandating the requirement of collateral.

Alternate Sources of Finance for the SMEs

Alongside the traditional way of deriving funding through banks, SMEs can also count on some alternate and more innovative sources of finance. Some of these instruments include covered bonds, securitised debts, corporate bonds, etc. Through these instruments, SMEs receive funding not through banks, but through the investors in the capital market or derivative market.

Securitisation and covered bonds are also forms of indirect financing tools that can help SMEs with their funding. Through the securitisation of SME debt, banks can easily transfer their credit risk to the money market. In this process, the SME loans are sold to some specialised companies. This helps to create new security that is backed by the SMEs’ payments.

These debts make sure that SMEs are not directly exposed to the capital markets. The SMEs receive the loan from the bank, and the extension is backed by the activities that the bank carries out in the capital market.

SMEs can also opt for asset-based finance like asset-based leasing and lending, in which an enterprise obtains funding based on the value that is generated by a particular asset during the course of its business. SMEs can also opt for trade credit instead of short-term bank lending.

SMEs can also receive funding through equity finance, where an investor provides financial resources to an enterprise in exchange for some ownership interest. The investor is also entitled to entrepreneurial risks, and the return on investment depends on the enterprise’s success. An investor may also choose to sell his share in the firm, or he may also receive his share in case the enterprise is sold.

You can learn about more financial instruments if you opt for an investment banking course.

Is Investing in the SME Sector a Good Option?

SMEs are a profitable sector and are slowly emerging as the backbone of economic activities. SMEs are also generating employment in many countries. This creates an opportunity for the banks to serve them better. Banks can also extend their digital solutions to the SME sectors.

The focus is improving the access of SMEs to finance and finding innovative solutions to combat the financial crisis, and banks are trying to bring about a holistic approach in the money market to make sure that SMEs can effectively contribute to the economy.

However, although SMEs can be a profitable option to invest in because of the high returns it is capable of generating, the risk factor is also when investing in small and medium-sized companies. If you have not done thorough research, there might be chances of an investor incurring heavy losses. Not only this, but you may also not be able to find a matching seller/buyer almost immediately. Therefore, liquidity is low in the case of SME exchanges.

SMEs can be extended support in a number of ways so that they can access financial services better. For instance, the financial sector can be assessed thoroughly so as to identify the areas of improvement and allow SMEs better access to finance. Improving the credit infrastructure can also be beneficial. SME finance can also undergo a lot of innovation in the form of e-lending platforms, e-invoicing, supply chain financing, etc. They should also be adequately informed of the best practices and the most successful models.

Conclusion

SMEs are important for the economic growth of a nation. They also provide employment opportunities. Therefore, it is important to make sure that they receive adequate financial support.

If you are looking forward to learning more about how investment banking can aid in the growth of SMEs, you can pursue an online investment banking certification course offered by Imarticus Learning. The course is ideally suited for finance graduates who have 0-3 years of working experience.

The course covers the basics of financial markets, risk management, trade life cycle, and everything that you need to become an expert in investment banking operations. Enrol now.