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Category: Management

Integrating S&OP in Business Planning

Posted on by Imarticus Learning

Effective planning and coordination across all parts of a company’s operations are critical in today’s continuously changing business world. Sales and operations planning, otherwise known as S&OP, has evolved as an effective structure for streamlining sales projections, production plans, and inventory management. Organisations may streamline processes, increase customer satisfaction, and generate long-term growth by incorporating S&OP into overall business strategy. 

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This article delves into the main concepts and benefits of incorporating S&OP into corporate planning and practical tips for building an efficient S&OP process.

What is S&OP?

Sales and operations planning (S&OP) is an integrated business management approach that enables firms to achieve focus, alignment, and synchronisation across all functions. It is a strategic planning process aligning demand, supply, and financial planning to support executive decision-making and approve material and financial plans that are viable and financially rewarding.

The primary purpose of S&OP is to balance customer demand and the organisation’s ability to supply that demand effectively. S&OP entails the integration of numerous data sources, such as customer relationship management (CRM), engineering, independent systems, and external databases. This integration improves the supply chain’s overall health and gives enterprises a competitive advantage. 

Benefits of integrating S&OP in business

Integrating sales and operations planning in a corporation can result in many significant advantages. Here are some of the benefits: 

  • Enhanced decision-making: Integrating S&OP delivers a complete and robust business image, allowing executives to make better-informed decisions. S&OP supports improved strategic decision-making that analyses the full impact on the business by synchronising demand, supply, and financial planning.
  • Improved alignment and coordination: S&OP ensures alignment and coordination among various business operations, encouraging improved coordination and collaboration. It integrates departments like sales, operations, finance, and supply chain, allowing them to work towards common goals and objectives. This collaboration breaks down barriers and improves cross-functional communication.
  • Optimal resource allocation: S&OP assists in optimising resource allocation by matching supply and demand. It allows companies to adapt production and inventory levels to customer demand, minimising overstocking or stockouts. Companies can reduce expenses, improve operational efficiency, and increase customer satisfaction by aligning resource allocation with expected sales.
  • Improved customer service: By integrating S&OP, firms can improve their customer service levels. Organisations can ensure timely delivery and satisfy customer expectations by aligning production plans and inventory management with customer demand. As a result, client satisfaction, loyalty, and retention improve.
  • Improved financial performance: By using S&OP, firms can improve their financial performance. Organisations can maximise revenue generation, reduce costs, and increase profitability by aligning sales projections, production plans, and financial targets.

Key steps to integrate S&OP in business planning

The key steps involved in incorporating sales and operations planning into broader business planning are:

  • Establishing a cross-functional S&OP team

Involving representatives from sales, operations, finance, and other departments in the S&OP process ensures diverse perspectives and expertise are considered, leading to more informed decision-making.

  • Defining clear objectives and performance metrics

Setting clear goals and metrics is crucial for a successful S&OP process. Measuring performance with metrics like sales revenue, customer service, inventory turnover, and forecast accuracy allows for continuous improvement and accountability.

  • Developing an integrated demand and supply planning process

Aligning sales, production, and inventory is crucial for optimising resources and customer service. Organisations can avoid stockouts, minimise bottlenecks, and enhance customer satisfaction by synchronising sales projections with production capacities and optimising inventory levels. Collaboration between sales and operations teams leads to improved efficiency and cost savings.

  • Enhancing data visibility and analytics

Advanced analytics and technology solutions enable firms to access and evaluate massive amounts of data in real time, facilitating scenario analysis and boosting decision-making. It provides greater insight into market trends, customer behaviour, and operational performance. Forecasting algorithms, predictive modelling, and data visualisation are examples of advanced analytics techniques that can help spot patterns, estimate demand more precisely, and simulate multiple scenarios to evaluate their impact on business outcomes.

  • Implementing a regular S&OP review cycle

Conducting regular S&OP reviews is crucial for evaluating performance, detecting gaps, and implementing required changes to the business plan. These reviews enable the S&OP team to learn valuable lessons, adjust forecasts based on market fluctuations, resolve bottlenecks or inefficiencies, and align plans with strategic objectives. Moreover, they provide an opportunity to communicate outcomes to stakeholders and ensure lasting commitment.

Conclusion

Organisations can improve operational efficiency, strategic alignment, and, ultimately, long-term success by adopting effective S&OP practices. Sales and operational planning assist in harmonising conflicting goals between different departments. A holistic S&OP process can unify the whole supply chain, from supplier to customer. Enrol in a supply chain course to upskill and learn more about S&OP.

The Professional Certification in Supply Chain Management and Analytics offered by Imarticus and IIT Roorkee is the perfect course for candidates wishing to succeed in the supply chain industry. Visit the website for more details.

The Importance of Employee Engagement in Organisational Success

Posted on by Imarticus Learning

Employee engagement revolves around the team’s commitment and enthusiasm toward their work. 

Engaged employees possess a sense of empowerment to immerse themselves in tasks fully, contribute innovative ideas, and foster meaningful relationships with their colleagues. 

They have a profound understanding of the purpose and significance of their work, which ignites a sense of inspiration to embrace new challenges, even in the face of potential setbacks.

Types of Employee Engagement

Differentiating employee engagement into three primary categories requires employing specific strategies to cultivate each type:

Involvement with the organisation

Involvement includes the level of engagement employees have with the entire organisation, encompassing their sentiments towards senior management. 

As a manager, you can establish a positive company culture, and uphold core values, instilling employees with confidence in the business and its leadership to stimulate organisational engagement.

Interaction with supervisors

It pertains to how employees establish relationships and communicate with their immediate managers. 

You can create an environment where team members feel valued, providing constructive feedback and guidance for their growth and accomplishments to improve managerial engagement.

Collaboration with colleagues and shareholders

Collaboration refers to employees’ interactions and connections with their coworkers and external partners. 

You can drive this form of engagement by offering opportunities for team bonding, such as engaging in team-building activities and collaborative cross-functional projects.

Levels of Employee Engagement

Highly engaged employees

Highly engaged employees have a strong affinity for their workplace. They feel connected to their teams and hold favourable opinions about the organisation. 

They go the extra mile, serve as brand advocates, and inspire others to perform their best.

Moderately engaged employees

Moderately engaged employees view their organisation in a relatively favourable light. While they like their company, they see room for improvement. 

They may not actively seek additional responsibilities and can underperform due to specific barriers that hinder full engagement.

Barely engaged employees

Barely engaged employees exhibit indifference toward their job and the organisation. They need more motivation and only do the bare minimum to get by, sometimes even less. 

These employees may be considering other job opportunities, posing a high turnover risk.

Disengaged employees

Disengaged employees hold negative perceptions about their workplace. They feel disconnected from the organisation’s mission, goals, and future. 

They need more commitment to their roles and responsibilities, potentially affecting the productivity of their peers. It’s crucial to address disengagement to prevent its adverse impact.

Factors That Influence Employee Engagement

Level of job satisfaction

Job satisfaction strongly influences employee engagement. Employees who are content with their job are likelier to feel engaged. 

Job satisfaction encompasses various aspects, including:

  • The organisation itself
  • Leadership within the company
  • Colleagues and coworkers
  • The work environment
  • Compensation, benefits, and growth opportunities also contribute to job satisfaction.

Sense of meaning and purpose

Employees who perceive their work as meaningful are more likely to be engaged. 

Employers can enhance employee satisfaction and engagement by:

  • Demonstrating how the employee’s role impacts the company’s customers positively.
  • Providing career development opportunities, such as counselling and mentorship.
  • Improving training programs for skill enhancement.

When employees find purpose in their work, they are more inclined to commit to the organisation long-term.

Work environment

The work environment, encompassing physical and digital aspects, is vital to employee engagement. 

The considerations include:

  • Atmosphere, climate, and culture within the workplace.
  • Leadership behaviour and attitudes.
  • Digital work environment.
  • Employee behaviour and attitudes.

These factors collectively shape employee engagement, either positively or negatively. 

Employees absorb the work environment, which can impact their motivation and engagement. Building a supportive and engaging work environment is crucial for maintaining high levels of employee engagement.

What Are the Benefits of Employee Engagement?

  • Enhanced productivity: Engaged employees demonstrate increased commitment and communication, fostering a positive work environment that fuels productivity and pride in their contributions. 
  • High customer satisfaction: Engaged employees who interact with clients exude passion, resulting in better customer experiences and improved customer retention. 
  • Heightened employee retention: Supportive managers and dynamic work environments reduce turnover, retain valuable talent, and promote organisational stability. 
  • Cultivated company culture: Prioritising employee engagement as a core value nurtures a positive work culture, inspiring employees to model good behaviour and contribute to a productive environment. 
  • Stimulated innovation: Engaged employees are more likely to think creatively, driving problem-solving and fostering innovation within the organisation. 
  • The attraction of top talent: Focusing on employee engagement, including respect, inclusivity, and a comfortable work environment, enhances the organisation’s ability to attract and recruit valuable talent.

Strategies for Improving Employee Engagement

  1. Develop a clear engagement strategy: Establish objectives aligned with company values to guide employee engagement initiatives and ensure consistency. 
  2. Seek employee feedback: Include employees in the design process and gather their input through surveys, focus groups, or suggestion/feedback boxes to gain valuable insights and enhance engagement efforts. 
  3. Foster an open and authentic culture: Promote open communication and create an environment where positive and constructive feedback is valued, recognising achievements and personalising praise to make employees feel valued. 
  4. Provide career growth opportunities: Offer professional development and growth opportunities to demonstrate support for employees’ career aspirations, boosting engagement and retention. 
  5. Prioritise work-life balance: Enhance work-life balance and flexibility to attract a diverse talent pool and improve employee satisfaction, catering to individuals with varying needs and skills. 
  6. Implement initiatives from the start: Engage new hires early by introducing them to company culture, providing information about their first day, encouraging involvement in employee resource groups, and sending welcome packs. 
  7. Maintain momentum: Continuously improve and adapt engagement programs to demonstrate commitment and consistency, avoiding sudden changes that may lead to employee disengagement. 
  8. Make engagement a daily habit: Incorporate engagement strategies into day-to-day operations, including fostering a no-blame culture and emphasising problem-solving to support employees and build trust. 
  9. Establish a culture of ongoing feedback: Encourage open communication and create an environment where employees feel comfortable providing feedback, fostering a sense of value and engagement. 
  10. Get leadership onboard: Ensure leaders are actively committed to increasing employee engagement, as their actions and behaviours set the tone for the organisation and influence job satisfaction.

Conclusion

Investing in employee engagement is a crucial endeavour for any company. The benefits are plenty and diverse. 

Engaged employees bring unmatched passion and dedication. They stay with the organisation for extended periods and strive for excellence, inspiring and uplifting their colleagues in the process.

Kickstart your career by enrolling in Imarticus Learning’s Global Senior Leadership Programme from IIM Lucknow.  

The IIM course for working professionals offers a comprehensive study and provides valuable insights and strategies to maximise employee engagement and propel organisational growth.

Visit Imarticus Learning to learn more about the IIM leadership program. 

Big Data Analytics in Supply Chain Optimisation

Posted on by Imarticus Learning

Only 14 per cent of the supply chain management executives had realised the importance of big data in 2014. By 2022, the percentage had increased to 50 per cent and has been increasing ever since, thus proving the change that big data analytics has brought to the scene of supply chain management.

From closely monitoring quality in real-time to predicting and preventing risks, massive data sets have become the new solution to optimising supply chains.

Transformative Impact of Big Data on Supply Chain Management

For optimisation of production planning

While it can be quite daunting a task to create the most realistic production plan and schedule, Data Analytics can help tackle this challenge. Also known as logistics management, it helps clear up the scheduling constraints that manufacturing units often face due to a multiplicity of schedules. With the help of data analytics, the manufacturing facility can compare the prepared schedule and the real-time output to ensure that the plan most accurately represents the actual quantity that can or will be produced. 

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Using integrated data sourced from the supply chain, companies can perform both catalogue management and planning for restocking, as well as monitor delivery situations. Since the time lapse between the scheduled delivery and actual delivery, both early and delayed can be expensive, data signals can be used to track the delivery speed and location of goods and identify the best routes for delivery, staffing and so on. 

Analysis of consumer behaviour 

Behaviour analysis of customers has formed a significant part of data analytics due to the volatile market conditions and the imminent possibility of a recession. By using data analytics to understand customers’ preferences, organisations can adjust their schedules and production stocks. By predicting the demands, it is easier to predict the requirements of the customers and provide them with a unique experience.

Behavioural analytics can be applied to internal stakeholders and vendors as well. The executive officers who work in the domain of supply chain management can assess the behaviour and requirements of every participant in the business, and offer support while mending gaps wherever required. 

Maintenance of machines

Maintenance of big machines has been much easier with the aid of data analytics. Supply chain enterprises often have to encounter the risk of sudden equipment breakdown, malfunctioning due to rust, and other unexpected obstacles. The maintenance department can benefit from combining large data systems with the Internet of Things (IoT) to transmit alerts for any kind of irregularity detected in the equipment. For instance, they can use detectors to monitor production, find any abnormality, and inform the controller about the need for routine maintenance when the time comes. 

The detectors are installed to mirror the operations of the machine and the data retrieved in real-time can help predict machine failure, and thus augment the efficacy of the maintenance department. In the long run, this is a highly cost-saving move for it minimises expenditure on repairs and prevents unscheduled downtimes.

Management of supplier relationship

IndusSupplier Relationship Management can be greatly improved with the aid of Data Analytics. If the company can efficiently collect supplier data and analyse it with data analytic tools, then it can proactively monitor supplier behaviour and minimise obstacles.

For instance, decisions made on purchase orders are hugely influenced by supplier lead time, especially concerning timing and sizing. Considering that there can be fluctuations in supplier lead times, professionals can use big data analytics to accurately forecast lead times and avoid considerable variations. Qualitative data in the form of assessments and audits can be used by the companies to keep track of the suppliers’ activities for future purposes as well as to choose the right kind of suppliers. In case the primary supply chain is disrupted or violated, then the companies can easily pick an alternative reliable supplier for delivery and avoid losses.

Product design and quality control through predictive maintenance

Industries such as food processing, agriculture and chemicals often need to be constantly supervised and controlled, especially in specific elements. For instance, temperature control is a significant factor in ensuring the quality of the product, as even the slightest fluctuation in temperature can render the end product completely unusable.

One use of big data analytics is in cold chain monitoring technology, where data logging facilitates logistics for temperature-sensitive products. Furthermore, managers can control the heating and cooling equipment during packaging, transit, and delivery in real-time as needed.

 In supply chain management, product designing is also another important factor, and the designers can use data about the changing preferences of consumers to incorporate changes into product structure.

The Future of Predictive Big Data Analytics in Supply Chain Operations 

According to a survey by Gartner, among the supply chain leaders, 76 per cent have reported that they are increasingly facing supply chain obstacles. Hence, businesses are seeking out more applications of data analytics in predicting and preventing disruptions rather than remedying them. It is assumed that cross-functionality, or collating multiple supply chains to get a singular perspective and thus make quick strategic decisions in a fluctuating market, will be the biggest contribution of big data analytics in supply chain optimisation. Moreover, predictive data analytics will always be an integral part of the three main vital steps in supply chains: procuring goods, tracking inventories, and logistics management. 

Apart from the logistical strategies, big data analytics can also be impactful in endorsing sustainable practices in supply chain management. ESG (Environmental, Social, and Governance) issues, such as the eco-friendliness of the products, and exploitative labour practices can be addressed by the companies who retrieve data from their supply chain networks.

Conclusion

Managing supply chains in a digital mode has become increasingly in demand due to the cost-effectiveness and the greater amount of information to be retrieved. Aspirants seeking to make a career in this lucrative profession can hence train themselves in a Supply Chain Management Certification Course. 

One such programme is the Digital Supply Chain Management with E&ICT, offered by Imarticus Learning in partnership with IIT Guwahati. The classes will be held live virtually and will run for 6 months. The curriculum is focused specifically on industry orientation and students learn to use technology to get real-life experience in supply chain management. After completing this Supply Chain Management Certification Course, students are guaranteed to get placed in companies such as Nestle, Amazon, Microsoft or Paytm.

Supplier Performance Analytics and Inventory Optimization With Safety Stock Analysis

Posted on by Imarticus Learning

Supplier performance analytics is a game-changing tool for optimising supply chain design. It provides valuable insights into supplier performance, enabling informed decision-making. This data-driven approach enhances collaboration, fosters innovation, and improves efficiency. 

Combining supplier performance analytics with safety stock enables companies to identify cost savings opportunities. This holistic perspective drives transformative change, streamlines processes, and maintains a competitive edge in today’s fast-paced market.

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If you’re considering upskilling yourself with a supply chain analytics course, then keep reading and embark on a learning journey that will enrich your understanding and expertise in the realm of supplier performance analytics before you make a sound choice for your career. 

Why is supply performance analytics important?

Efficient sales and operation planning and optimising supplier performance is a critical yet complex endeavour. It goes beyond merely focusing on price, as suppliers adhering to agreed-upon pricing might still fall short in terms of service quality or provide substandard goods. Achieving your savings targets requires a holistic approach.

Supplier performance management grants you comprehensive visibility into the risks associated with a supplier, empowering you to implement measures that mitigate or eliminate those risks within your supply chain design.

For companies aiming to maximise profits, timely delivery, price reductions, and service quality from suppliers are paramount. The effective management of supplier performance directly impacts the overall quality of the entire supply chain. 

Establishing an efficient mechanism to enhance supplier performance becomes essential, enabling accelerated improvement and ensuring the delivery of high-quality services and products. By prioritising supplier performance, you set the stage for a successful supply chain ecosystem.

Different types of supplier performance analytics 

Here are the four primary types of supplier performance analytics:

Operational Analytics: This type hones in on the operational data within a company’s supply chain. It delves into critical aspects like supplier performance, on-time delivery metrics, and quality measures. Operational analytics provide insights into the efficiency and effectiveness of suppliers’ operational processes.

Financial Analytics: This type concentrates on the financial data associated with a company’s suppliers. It delves into key financial factors such as invoices, payment history, and credit risk assessment. By analysing financial analytics, businesses can gain a deeper understanding of the financial stability and reliability of their suppliers.

Contract Analytics: This type revolves around analysing the contractual data related to a company’s suppliers. It focuses on crucial elements like pricing structures, terms, and conditions outlined in supplier contracts. Contract analytics enables businesses to assess adherence to contractual obligations, identify potential risks, and optimise supplier relationships.

Social Media Analytics: This type zeroes in on the social media data connected to a company’s suppliers. It entails monitoring and analysing online reviews, ratings, and feedback provided by customers or stakeholders about suppliers. Social media analytics offers valuable insights into a supplier’s reputation, customer satisfaction levels, and overall brand perception.

How to implement supplier performance analytics?

Implementing supplier performance analytics successfully requires careful consideration of key factors. Here’s a guide to ensure a smooth implementation:

Acquire accurate supplier data: Gather precise and reliable data on your suppliers from various sources such as financial reports, customer surveys, and supplier performance evaluations. This comprehensive data will serve as the foundation for your analysis.

Identify relevant KPIs: Determine the key performance indicators (KPIs) that align with your organisation’s goals and will effectively evaluate supplier performance. Consider metrics like on-time delivery, product/service quality, and total cost of ownership. Tailor the selection of KPIs to your specific needs.

Track and analyse KPIs: Regularly monitor and analyse the identified KPIs to gain insights into supplier performance. Track trends, identify areas for improvement, and spot any anomalies or patterns. This ongoing analysis will enable proactive decision-making.

Develop a scorecard system: Establish a scorecard system to track and evaluate supplier performance against the selected KPIs. The scorecard serves as a quantitative tool to assess suppliers, aiding in decision-making for future partnerships. It provides a standardised framework for supplier evaluation.

Maintain open communication: Foster open and transparent communication channels with your suppliers. Provide both positive feedback for commendable performance and constructive criticism when necessary. Collaboration and effective communication contribute to continuous improvement within your supplier base.

Why is safety stock important?

Safety stock is an essential component of inventory management that involves holding extra inventory beyond normal demand. Its importance can be summarised in the following points:

It accounts for fluctuations in customer demand, minimising the risk of stockouts during unexpected spikes in demand or supply disruptions.

It compensates for uncertainties in supplier lead times, guarding against delays in receiving materials or finished goods.

Safety stock provides a cushion during supply chain disruptions, such as natural disasters or labour strikes, ensuring business continuity.

It reduces the risk of stockouts caused by variations in order cycle time, enhancing service levels and customer satisfaction.

Safety stock minimises the likelihood of backorders, ensuring product availability and customer loyalty.

It accommodates seasonal demand fluctuations, allowing businesses to meet increased customer requirements during peak periods.

Safety stock acts as a buffer for uncertain demand forecasting, providing a safety net against demand forecast errors.

Overall, safety stock plays a crucial role in mitigating supply chain risks, maintaining customer satisfaction, and ensuring smooth operations.

When do you not need safety stock?

There are valid reasons why having safety stock may not always be the optimal choice for your business. Instead of applying a blanket rule to every product in your inventory, it’s important to strategically evaluate its necessity. Here are some considerations for not having safety stock:

Firstly, investing a significant amount of money in inventory ties up your cash until those products are sold. If a substantial portion of your capital is locked in safety stock, it may limit your ability to address unforeseen expenses or capitalise on business expansion opportunities.

Secondly, managing retail inventory is both time-consuming and costly. The more inventory you hold, the higher the expenses associated with holding costs, such as storage units, warehouse space, and labour.

In cases where products consistently sell at a predictable rate, safety stock may not be essential. Instead, focus on investing in additional units of items that experience occasional unpredictable surges in demand.

Lastly, if your suppliers are reliable and consistently deliver products as agreed upon, you may not require safety stock. Furthermore, having multiple suppliers for the same product provides a contingency plan, reducing the need for excess inventory.

Upon carefully assessing these factors, you can make informed decisions about when and where to allocate resources for safety stock, optimising your sales and operation planning and maximising your business’s overall efficiency.

Conclusion 

Supplier performance analytics is an indispensable asset for any business striving to thrive in the ever-evolving business landscape. It empowers organisations to adapt, optimise, and seize new opportunities, ultimately leading to sustainable growth and a competitive edge in the market. 

If you have an interest in expanding your knowledge of supply performance analytics, consider enrolling in the supply chain analytics course by Imarticus- the Professional Certification in Supply Chain Management and Analytics, in collaboration with IIT Roorkee.

Feature Engineering: Transforming Data for Machine Learning

Posted on by Imarticus Learning

Raw input data are generally available in tabular formats, where rows highlight observations or instances and columns show attributes or features. Feature engineering is a tactical process which is used to transform raw data into valuable features that can be utilised for creating accurate predictive machine learning models. This uses Python programming and Power BI as key visualisation tools. 

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Feature engineering helps to prepare models with reasonable prediction even when a few missing raw data are missing. This is possible when the work is done using the most relevant features that eliminate undesirable or non-influential ones.  

The Process of Feature Engineering

Feature engineering in machine learning broadly consists of four processes. They are as follows:

Feature creation

Feature creation is a process that uses the human brain’s creativity and is performed by addition, deletion or rationalisation of existing data variables. This activity is done by professionals who have chosen a career in data analytics. 

Transformation

The process of adjusting the selected variable so that it may contribute effectively towards the accuracy and performance of the predictive model is known as transformation. The process ensures that all the features follow the same scale. It also helps to make the model flexible to accept a variety of data inputs.

Feature extraction 

Feature extraction is an automated method of generating new meaningful variables out of the raw data provided. This makes the predictive model more reliable and accurate by reducing the input data volume. The process involves text analytics, cluster analysis, edge detection algorithms, and principal components analysis.

Feature selection

Feature selection is the process of selecting the most useful variables out of many for incorporating them into the predictive model. Irrelevant or noisy data are left out since they are useless to the model and negatively affect the model when infused into the system.

Tools of Feature Engineering

Many feature engineering tools help make good predictive models. A few of them are described below:

FeatureTools

FeatureTools helps to perform auto-feature engineering. It is particularly good at converting meaningful raw data to useful features in machine learning.  

AutoFeat 

Linear predictive models with automated feature engineering and selection process is a key strength area of the AutoFeat tool. AutoFeat helps us to select the unit of useful variables.

TsFresh 

TsFresh is an open-source Python package tool that helps to correlate and automatically calculates a large number of time series data. It helps to extract details such as peak, average value, time reversal symmetry statistics etc. Knowing Python programming is of immense importance in today’s world.    

OneBM 

This tool works on the raw data, irrespective of whether they are relational or non-relational to the predictive model. It can generate both simple and complicated features.

ExploreKit

It is a structured framework to produce automated features. It can combine multiple data and may unearth common useful features thereby eliminating duplication. This makes the predictive model compact and error-free. 

Feature Engineering Techniques in Machine Learning

Some of the regular feature engineering techniques used in preparing data for machine learning models are as follows:

Imputation 

The most common problem is missing data, which arises out of the following typical cases of human errors, data flow interruptions, privacy issues etc. Numerical and categorical imputations are applied in these cases.

Handling outliers 

This is a process of suitably dealing with specific data which is exceptional in terms of value and category. When several outliers are very few, the process of removal is applied. However, if the number of outliers is quite a few, then removal will cause us to lose enormous data and hence be avoidable. In these cases, the process of replacing values, capping or discretisation is applied.

Log transform 

Logarithms are used to convert data of a skewed distribution into that of a normal distribution. This process is also used to handle confusing data. The efficiency of this tool may be best expressed visually with Power BI.    

Scaling 

It is the process of bringing all data under a common scale by scaling up or down, as required. The purpose is to make the features similar in terms of their range. The two standard procedures adapted here are normalisation and standardisation.

Binning

Excessive and irrelevant data and unwarranted numbers of parameters deter the performance of models. Binning is the process of segmenting several data and features and eliminating unwanted ones from the system.

Feature split 

This is a process of segregating features into two or more parts to closely monitor the same with the help of the data available. This characteristic produces meaningful features with better algorithms and is better numerically representative.

One hot coding 

It is a commonly used technique in machine learning. It is used to convert categorical data in a specific form which can be easily interpreted by machine learning algorithms and can be used in creating successful predictive models. 

Benefits of Feature Engineering in Machine Learning Models

Using feature engineering in machine learning applications has some notable advantages, which are as follows:

Flexibility 

Better features impart better model flexibility. Even if a wrong model is chosen by mistake, the flexibility of features will generate good predictions.

Simplicity 

Flexible featured models are simple and quick to operate.

Better Results 

With the same available data, the selection of better features gives way to better results in predictive models. 

Conclusion

A career in data analytics is a booming option for modern youth. A data science course with placement assistance makes this opportunity lucrative. Having a machine learning certification is very necessary for a prospective candidate. Several reputed institutes in India offer machine learning certification courses.

The Postgraduate Program in Data Science and Analytics at Imarticus will give the prospective candidate a perfect start to their career. This is a data science course with placement and the duration of the program is 6 months. The classes are held on weekdays where the mode of teaching is both online as well as classroom training. 

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

The Impact of Technology on Management Practices

Posted on by Imarticus Learning

For a business, the most important thing is to achieve success. And in order to accomplish that, they must follow a set of management practices. This not only aligns the tasks of the organisation but also oversees all the aspects of the business to form strategic decisions. Further, these decisions help in driving success to the organisation. 

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There are several management practices, like establishing quality control and providing adequate training to employees. These practices have a huge role to play in getting the company’s employees to achieve their target with the given resources. But as we know, with time, technologies have advanced greatly. And like any other realm of human existence, it has highly impacted management practices. 

Here, we will discuss different management practices and the role of technology in impacting them. To understand concepts like these in-depth, one can also go for a BBA in business analytics or an online BBA course.

Different Business Management Practices

The management of an organization is responsible for the well-being of its employees, as well as its stakeholders. Thus, business management practices are of immense importance. Below are some useful management practices that should be applied in every organization.

Communication

It’s essential for every organization to have a clear chain of communication with its employees. This practice helps the company communicate its goals and expectations to the staff and make them understand their roles that fit in the business strategy. 

Assessing Operations of Business

Improving a business and meeting success isn’t an overnight thing. It needs a constant effort from everyone associated with it. Thus, close attention should be paid to every detail of the business. And to do this, an assessment of business operations with the right tools and practices on a regular basis is needed. 

Strategic Planning

Far-sightedness is crucial when one aims for a successful business. That being said, strategic planning is one of the most important practices of an organisation aiming to yield some long-term benefits. Here, quantitative data can be used for making informed decisions. According to the collected data, training can also be reshaped for better results in the future. 

Engagement of Employees

The management practices also include the job of engaging the employees to solve problems, take initiative, and come up with innovative ideas. All these can be done only if the employees and passionate about their job which will happen once they’re aligned with the company’s vision. Also, studies have found that companies with high employee engagement and more profitable. 

Open Management Style

Developing a culture where your employees feel free to come up to you with their ideas and queries gives a boost to the overall functioning of the organisation. Open management style also projects the management as a helping hand for the employees rather than an enforcer. Thus, it empowers the employees and makes them feel an important part of the organisation. 

Impact of Technology on Management Practices

Technology can easily create a huge impact for betterment in any space if used judiciously. Thus, there are plenty of enhancements in management practices with the use of the latest technologies. Some of the crucial impacts are listed below. 

Enhances Decision Making 

One of the most important roles of a manager is to come up with effective plans and decisions. To survive in this competitive environment, one must have the latest technologies with them to collect accurate data at an improved speed. This will then faster the decision-making process with more efficiency. Technology also helps in accessing these data to draw a precise conclusion that will assist the business in being on track to meet its goals. 

Employee Collaboration

With time and the advancement in technology, our lifestyle has completely changed. One major impact is also seen in the way people communicate or collaborate with each other. Especially in the professional setup, collaboration in former conference rooms has changed to video conferencing, allowing them to communicate and share their ideas in the blink of an from where ever they are. To enhance the quality of work along with building a culture in the organisation, some real-time collaboration tools like cloud-based file sharing are essential. 

Efficiency in Operational Tasks

There are many tasks in a workplace that needs to be done on a daily basis or are repetitive in some sense. This needs to be done manually and ends up taking a lot of time for the employees. But with the right technology, one can transform this old setup, saving the time of employees from doing time-consuming and repetitive tasks. Further, they can engage themselves elsewhere without sticking to inefficient manual tasks. 

Management of Business Information

Along with building a business comes the responsibility of managing its confidential information. Thus, it becomes the utmost priority of the management to have a structured and efficient way of managing those documents and contents. And to help the management in doing so comes cutting-edge technology at the rescue. 

Digital Transformation

Be it any kind of business, one needs to keep up with technological advancements and grow alongside social trends to attain success. This means that businesses must transform themselves digitally to survive in the competitive surrounding. 

To do this, there must be a good digital strategy that can be planned only after identifying the gaps present in the organisation. After finding it out, the business should look for suitable technologies and out the transformation one step at a time.

Conclusion

Managerial practices are important for the smooth processing of all the workings of an organisation. It keeps a regular check on various activities of different departments and thus, plans out strategies for their best. To further enhance this process, new-age technologies can be a great boon. Be it security, or communication, there are hi-tech innovations to assist in every possible domain of an organization. 

Thus, it is advisable for any fresher or an existing professional to upgrade themselves with a recently crafted online BBA course that will educate them about the application of the latest technologies in management practices.  

For in-depth knowledge on this, one can enrol for BBA in Business Analytics that empower future business leaders. Here, you will get hands-on experience with new-age tools that will enhance your management skills even more. 

Visit Imarticus Learning to know more about business analytics.

Benefits of Batch Tracking and Periodic Inventory

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Businesses are built on two crucial factors, product quality and customer service. 

Batch tracking is an efficient approach to inventory management which plays a crucial role as it impacts on both product quality and customer service. 

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In addition, periodic inventory management, through keeping track of an inventory in periodic segments, helps to maintain the balance between supply and demand patterns to maximize profit.

While batch tracking enables a business to recognize the source of a problem (quality issues) in the larger supply chain, periodic inventory management reduces the chances of such problems as they help to tailor the goods to meet the customer’s demand.

Methods of Batch Tracking

The three most effective methods of batch tracking in the supply chain are:

Push Strategy

It is a method in which goods are “pushed” down, that is, it essentially tracks the downflow of the product from the initial manufacturing process to the reception by the customers. A company must accurately predict product demand in order to successfully use the push strategy. It is important to know how much of a product is required and when, throughout the year. Businesses can gain valuable insights into how inventory has been used over time and how much inventory they may need to order over the course of a year by using inventory management software.

For instance, a home appliances business might stock hundreds of air-conditioners and coolers in the spring and summer but only a few in the winter. These shops decide how many grills to purchase based on sales records of appliances previously sold. For companies that can precisely predict their customers’ needs, the push technique becomes the most favorable and efficient of all.

Pull Strategy

A pull strategy is an inventory management method in which a store, warehouse, or company “pulls out” goods only when ordered by a customer or employee. Items move upstream in the supply chain instead of moving downstream. This can take a lot of time. Pull techniques are used mainly for luxury or novelty items (products with unpredictable demand). 

For example, many wedding dresses for brides are “not taken off” until the purchaser submits their credit card. These women choose dresses from dress samples and websites, and the final dress is either made or sourced at the time of purchase. It can take months, but customers usually have no problem using it because it is an industry-standard. However, the pull strategy is not suitable for all businesses, especially when customers have immediate access to the same product from another supplier.

Just-in-Time Strategy

Just-in-time inventory strategies are similar to pull strategies. That is, companies order inventory “just in time” to meet customer orders and business needs. Additionally, to successfully implement and accomplish a just-in-time inventory management strategy, one requires reliable suppliers, vendors and third-party logistics partners. Without these, businesses cannot meet customer’s demands.

 Just-in-time warehouse management helps companies reduce inventory costs, reduce inventory, and improve cash flow. On the other hand, businesses that rely on JIT inventory cannot always keep up with demand and may have to overpay for products just to get them to their customers faster.

Methods of Periodic Inventory

The three most effective and commonly used methods of Periodic Inventory can be categorized as FIFO, LIFO, and FEFO. These strategies can be tailored to suit the requirements of the business, as well as, their customers, by adjusting to a favorable interval of inventory management which can be accomplished by determining the approaches mentioned below.

FIFO

FIFO stands for First In, First Out. This strategy of management is mostly useful if the business deals with fast-moving and/or products for consumption, as it will ensure the oldest inventory is sold first.

LIFO

LIFO stands for Last In, First Out. This strategy is not the most commonly used. However, businesses involved with products that do not have a natural date of expiration are often found implementing this strategy. 

FEFO

Lastly, FEFO stands for First Expiring, First Out. This strategy is used in businesses that deal with products with clear expiration dates, as products with expiration dates closest to the date of purchase are sold, used, or otherwise disposed of first, regardless of when they were manufactured or purchased. This strategy is often preferred by businesses in the food industry (perishable products) over FIFO because it focuses on the date of expiration over the date of manufacturing.

Advantages of Batch Tracking

The main advantage of batch tracking is the full traceability it enables. There are many benefits for companies when they monitoring the shelf lives and quality of their products from raw materials to point of sale. Such as,

Safety and Quality control

Batch tracking is essential to inventory monitoring to ensure quality control and safety, as it allows anyone to quickly and efficiently identify all items in the relevant batch when a problem is identified.

Expiration-date Tracker

Expiry date data is used for supply sequencing strategies and marketing and promotions. With batch tracking, one can easily assign expiration dates to entire batches instead of individual items and track inventory that is nearing expiration, so they can initiate promotions, for example,  to increase sales.

Automated Sequencing

Batch tracking also enables businesses to integrate automated sequencing strategies for their inventories like FIFO or FEFO. This practice results in the extraction of the optimum value of inventory by minimizing potential waste.

Recall Process Ability

No one wants a product removed from the market, but removing it before it causes major problems is critical to long-term customer satisfaction. When a recall becomes necessary, lot tracking software allows companies to more quickly send appropriate notifications to their supply chains and affected customers.

Better Product Quality

Knowing what materials are used in a quality batch of products allows you to continue ordering from the best suppliers and avoid those who do not provide the right materials. Overall, this results in better product quality, increased customer satisfaction, and increased sales.

Hassle-free Supply Chain 

Just like the ability to identify good batches that lead to better product quality, so can your supply chain. Batch tracking helps business owners identify the best and most cost-effective vendors and close more deals.

Financial Benefits

Batch tracking supports more informed decision-making and saves costs. Simply knowing the best time to sell a batch of your product based on the expiration date can prevent your inventory from aging past the sell-by date. Knowing when a product needs to be recalled also helps avoid replacement shipping costs and potential legal fees.

Improved Accounting Competency

Processes automated with the help of batch tracking technology can decrease accounting errors and data misinterpretation. Improved visibility makes it easier to monitor the location of all items in batches to see if they are still in stock, in transit, or already sold.

Benefits of Periodic Inventory

The practice of Periodic Inventory management provides several benefits which eventually enable the system to track both purchases and sales over a set period. By utilizing a periodic inventory system you can determine how much money was spent on what, and how many items were sold. Periodic inventory, therefore, not only improves the general quality of the inventory stocks, but also has economic benefits. Some of the benefits of this practice are,

Simplicity

A periodic inventory system primarily simplifies the process of inventory management and documentation. It reduces manual efforts by doing less math, using less paper, and saving time which can be used for other management tasks required.

Economic Efficiency

One only needs to count their inventory at regular intervals. Thus, they might want to buy some barcode stickers and scanners, but these are a cheaper alternative than running sophisticated computer systems that monitor your inventories continuously (or in real-time).

Accuracy

As the main objective is to count the cost of goods sold and the closing inventory, one needs to be patient until the physical check is finished. These physical checks, although time-consuming, provide accurate and in-depth knowledge of the inventory stocks which cannot be achieved by automated systems.

Conclusion

Batch tracking and practices of periodic inventory management, are thus one of the most effective management practices that provide benefits to most businesses through increased visibility and exactness in inventory management. By extension, as a result of these benefits, both indirectly help businesses in maintaining and/or improving their customers’ satisfaction, as well as in raising their product quality. 

To enhance skills in inventory management in a supply chain and other related areas, professionals can enroll in supply chain management courses such as the Supply Chain And Operations Officer course or the IIM Raipur Supply Chain Management program.

For senior executives looking to develop their skills further, Imarticus Learning offers the IIM Raipur Executive Certificate Programme For Global Chief Supply Chain And Operations Officers, providing them with the tools to excel in their roles and drive success in their organizations.

Visit Imarticus Learning to learn more about Inventory management in a supply chain.

Crisis Management: Strategies for Handling Unexpected Challenges

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Every business whether large or small must be equipped with strategies that help to manage crises in the organisation. Most of the public relations crises are unexpected which leaves organisations with no way of solving them at hand. Hence, it is crucial for businesses to have a solid crisis management plan and strategy that will help them get over unexpected emergency situations.

The most common way in which a company tries to manage a crisis is to decline to comment on many problems that arise in front of the media. However, experts say that the right way to approach a crisis is to advocate for complete and full disclosure to the public. Enrolling on a general management program can help individuals to learn more about crisis management and how to effectively implement various crisis management strategies in an organisation. 

Read on to know about crisis management and how to effectively deal with unexpected challenges and situations.

What is Crisis Management?

Crisis management is the process of implementing certain effective steps for eliminating the possibility of negative effects that arise as a result of various business processes. Crisis management includes multiple strategies for it to be effective and it mainly deals with the areas where individuals need to work with limited resources and time.

The main objective of crisis management is to make and implement strategies to eliminate the crisis in times of emergency and unstable situations. Careful and cautious planning is an absolute necessity for a catastrophe that might not be anticipated. Crisis management allows professionals to deal with difficult situations within an organisation and take timely action.

Crisis Management Strategies

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Creating an effective crisis management system is crucial for companies. The IIM Ahmedabad Management Course can teach professionals an effective way of creating a crisis management system. The following are the ways in which a good crisis management system can be created:

Identify key risks

The first step in a crisis management system is to identify the potential risks that can create a negative impact on the company. These problems can be anything related to natural disasters, internal business problems, supply chain problems and so on. For building a good crisis management system, professionals should be in touch with stakeholders for performing risk identification and evaluating various methods of mitigating such risks.

Build a crisis management team

After identifying the potential risks, the management should start planning to solve them so that it does not create any hindrance in the future. Companies should create a crisis management team that will solely devote their efforts to apprehending and solving the potential risk that can impact the business at a later stage. 

The team should consist of different individuals from different departments that will have the knowledge and expertise of various departments. This management team must be responsible for creating and implementing various strategies within the organisation.

Establish guidelines and protocols

After building a dedicated team towards crisis management it is important to bill certain guidelines and regulations for the team to work accordingly. These protocols should include problems like what to do in case of natural calamities how to handle a data breach etc. It also includes building a plan of communication which will help the team members to communicate with other members of the organisation, the media and the public.

Run regular plan tests

Is important to see whether the plans are working to give the desired results or not. Hence, running a regular plan test is very crucial. Making concrete plans for dealing with difficult situations allows individuals to understand what to do in times of emergencies. 

Also, thinking about the result of an action and how it would impact a business will help make rational choices to solve potential problems. Regular testing can assist team members to find any flaws or gaps in the plans that need to be fixed.

Train employees

The employees act as the first line of defence in times of difficult situations. Hence, it is important for companies to train employees to deal with emergency situations and make them aware of the various crisis management strategies. Online training modules and practice drills can make employees master the art of handling unexpected emergencies.

This step will also help to highlight any gaps in the plan. Performing regular practice drills will train employees to be ready for events of an actual emergency.

Share a communication plan with the teammates

Building a strong and effective communication strategy is very important for a successful crisis management team. This will guarantee that employees are aware of what to do in emergency situations. Additionally, it will aid in avoiding confusion and turmoil when faced with unexpected circumstances. 

A good communication plan includes regulations and instructions on how to communicate and what to communicate with various employees and stakeholders of the company. 

Build resources for the crisis management team

Creating a crisis management team is not enough, the team must be provided with sufficient resources for performing its daily operations. Resources include a dedicated office or area where the team can work and also various equipment and data that are essential to carry out their tasks. It could also mean providing the team with sufficient time and IT machines to do their job.

Providing the team with what they need for mitigating the potential risks in times of emergencies will automatically build an effective crisis management system.

Evaluate solutions team

After a crisis, it is necessary to look back and evaluate the course of action taken and its results. The solution evaluation will help the team to understand whether the action they have taken was enough or not. Could they have done something else and used fewer resources than the original to do away with the problem or not? Hence, it allows the team to identify areas of improvement, if any.

Conclusion

Crisis management is an inalienable part of business management and has become very important in recent times. Every business requires professionals skilled in the domain of crisis management which is making this career option in demand. If you are a management professional and want to acquire the skills of crisis management, register for The 21st General Management Programme in Dubai, Indian Institute of Ahmedabad by Imarticus. This is an advanced-level management program which will help you inculcate all the new age and necessary management skills. 

Launch a successful career in management with the knowledge of crisis management and stay ahead of your contemporaries in this insanely competitive corporate world.

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

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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

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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.

Robotic Process Automation (RPA) in Procurement and Supply Chains

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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.

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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.

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