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Digital Technology in the Chemical Industry

Digital Transformation in the Chemical Industry

Shahabudin K
Content Creator

5 min read | Apr 27, 2021

Market Value of Chemical Industries:

 

                  $178 billion is the value at which the Indian chemical industry stood in the year 2019. It is expected to skyrocket to $304 billion in the year 2025. The CAGR is approximately 9.3% when it hits 2025. The specialty chemicals industry hits 22% of the calculated value. The demand for Specialty chemicals is expected to hit 12% more demand in the year 2022.                   

                 How can the chemical industry meet such demands? By which means the chemical industries hit these values in a short span? It is the technology that is boosting the business. Companies hitting a billion dollars differentiate themselves from the rest by the technology they implement to scale business. Let’s dive into the possibilities at which the chemical industries strategize their placement of digital technology.

ERP Selection:

     

                     Chemicals are always in demand, they hit different points in the consumer market, they deliver b2b as well as b2c communities. The business size becomes large here, meaning the maintenance of various business processes becomes a challenge. Here is where digital tech comes into play. ERP systems have evolved almost out of all folds. Around 60-70% of the manufacturing industries use SAP as their ERP and variations of SAP are adopted depending on the needs.

                     So, the star value here is SAP has made almost all business processes easier and profitable too. But here comes another challenge while adopting SAP, manual tasks taking place in SAP require huge manpower and high infrastructure costs. With the advent of Automation and AI, industries started adopting RPA automation which nevertheless proved to be worthy.

                     When an Industry adopts ERP automation, it should keep in mind that the automation implemented suits all time frames meaning the automation used must be versatile enough. Outdated technologies have become common nowadays, ultimately leading to the failure of the companies. So What can be done to face such challenges?

“Modernized ERP Automation is the Key”

Versatile ERP Automation:

“Reduce complexity through Standardization”

                       Most chemical industries fall into the traps of SAP automation which takes place outside SAP, which leads to the increase in infrastructure costs, manpower, increased number of SAP licenses, and much more. In many ways, this type of automation is outdated in all circles.

                       To escape from this rat trap, chemical industries must adapt to modernized ERP automation where they can save these recurring costs. Selecting ERP Automation services that can help you reduce infrastructure costs, recurring licenses and manpower give a perfect fit for ROI and this can contribute to your company’s CAGR indirectly owing to the effectiveness of the business.

                      We Beez Innovation Labs have helped industries adopt our modernized ERP automation, by enabling Automation within the Client’s SAP system rather than automating the ERP outside SAP.

For more information book a slot with us @ appointments.beezlabs.com or write to us at : [email protected]

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Understanding Deep-Tech Startups

Understanding Deep-Tech Startups

Shahabudin K
Content Creator

5 min read | Apr 22, 2021

Quick Introduction:

                           The term “Deep-tech” was first coined by Swati Chatruvedi, Founder/CEO of Propel(x). Deep-tech is the innovation of engineering technology which sets apart itself from the existing protocols and procedures providing a unique scale of productivity and profitability. To be more precise, creating a revolutionary tech with unique aspects that could bring the raise of a particular industry well defines deep-tech.

Footprints of Deep tech:

                                    Deep tech involves fields with respect to Artificial Intelligence, Machine Learning, Robotics, Automation, Blockchain etc., as all these terms suggests it is evident that with these varied technologies the sectors which needs immediate revival or the sectors which can perform better, can be made more efficient, if deep tech is in action.

The Antonym of Deep Tech:

                              Shallow Tech which acts as a strong opposite of Deep tech involves reusability of the existing technologies and aspects. Meaning, it involves the same model of activation and productivity which has been performed for years. Some famous companies like Uber follow a business model which runs on shallow tech. From a business point of view any strategy can be followed for success in the market if it works out well, But giving a deep tech touch makes a business remarkable and will serve as a reference model for upcoming businesses.

How can Deep tech startups help revive the Indian Economy?

                                Intelligent Automation supporting huge business enterprises help in scaling up productivity, with increased domestic production will scale up the downtrodden GDP. With native Indian startups growing, they can adapt to deep tech involving AI, Automation, which will lead to the effective usage of resources and indirectly contribute to productivity and revenue. This ultimate adoption of Deep tech might seem tough in the short run, whereas it proves to be more productive in the long run.

What does it take for an organization to adopt deep-tech?

                                   For an organization to adopt deep-tech, be it of any size, must be ready to learn and implement change management, with change management comes the mindset of adapting to new tech in the market, then comes digital transformation, which ultimately proves productivity. Start-ups helping other start-ups to scale productivity will throw light on how technology is leveraging business and will turn the eyes of giant corporates towards these startups, turning everything into a profitable business opportunity.

Now, What is your take on Deep-tech? Are you a Start-up owner? If “yes”, what deep-tech factor have you used in your organization? Let us know in the comments.

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Balancing your Balance sheets with Artificial Intelligence and Machine Learning

Balancing your Balance sheets with AI and Machine Learning

Shahabuddin
Content Creator

5 min read | Apr 15, 2021

Balance sheets:

A company’s current fiscal strength, valuation, IPO releases, the attraction of Investors, and almost everything depends on its Balance Sheet. How? Years-long, balance sheets have been a key for understanding the income, expenses, SKU numbers, interest rates, asset values of a company.

As time passed, the modern world started requiring Modernized solutions, meaning a quick prediction of the future expenses, a short prediction of how a company can cut down interest rates, the level to which assets can be monetized in the long run, etc., These are a very few modern expectations arising from the business world when it comes to financial statements.

With the evolution of Automation and AI, these predictions proved to be effective to a maximum level. However no system is 100% efficient, that is why a prediction is happening instead of accurate outputs. Now let us see some of the important aspects in a balance sheet where ML and AI can help

An increase in the income structure, optimization of Operation costs, bringing down expenses are some of the must achieve targets in any balance sheet. One target in which businesses fail is ” Repayment of Debts” with “Interest”. Can AI help you pay the interest and debt amounts? No. But AI can help you in predicting the range of interest rates that your company will reach within a particular period, which can prove helpful for your finance manager to understand at what rates debts can be settled to free the balance sheet from interest rates and making the debt rates come down to zero.

Interest Rates over debts:

“When a gift is deserved, it is not a gift but a payment”

An increase in the income structure, optimization of Operation costs, bringing down expenses are some of the must achieve targets in any balance sheet. One target in which businesses fail is ” Repayment of Debts” with “Interest”. Can AI help you pay the interest and debt amounts? No. But AI can help you in predicting the range of interest rates that your company will reach within a particular period, which can prove helpful for your finance manager to understand at what rates debts can be settled to free the balance sheet from interest rates and making the debt rates come down to zero.

Revenue Forecasting:

                Revenue in business terms is the expenditure added to income in the balance sheet. You might find this definition a common one, but the results which we are going to get out of this simple formula are vast. Meaning, Revenue of a company decide almost every aspect of the budget in the upcoming financial year.     

              What if AI can do this prediction for you, for example, say for the next 5 financial years, Insane right? It can do even more. In basic aspects of financial management, we can predict the estimated revenue and other terms by using Financial ratios.

               Ratios can give you a certain level of output, but still, it is manual & time-consuming too. If you want to stay ahead of time and also make your company adapt to modern trends then you can bring AI into the picture, training an AI model with numerous balance sheets of all models and sizes with different data can help predict for the upcoming years, this will help your CFO and stakeholders where to concentrate more so that they can increase their revenue.

Failure of CAPEX:

“Money is always eager and ready to work for anyone ready to employ it”

 

                 The smartness of a business persona is making money work for you. Meaning, the expenditure which you had made on your capital assets, must yield a good percentage of ROI. The source of money for spending on your CAPEX depends on various sources, what if all these go wrong? You get hit by a strong debt, which will eventually lead to the failure of the assets, increasing the depreciation value of the assets which in turn will lead to bankruptcy at a certain point.

                 So how can AI/ML can help in this scenario? Again prediction modeling comes into the picture, your AI model can help analyze how much the depreciation cost might hit after a few years or the next year too, it can also help you understand whether investing in a particular asset is worth it or not. Which can help you preplan your monetary allocation on CAPEX saving your company from numerous pain points.

Conclusion:

                    AI & ML are aspects that can help you give a predictive analysis to make your company prepared to face challenges. Any system isn’t 100% efficient, AI is no different from this. But the results will prove sufficient enough to take care of your challenges and over a while, this can skyrocket to any percent level for that matter, meaning the sufficient results given by AI can increase the strength of your balance sheet year on year.

Hope this helps. Now, tell us in which financial aspect you think AI can help you resolve your challenges.

Write your views to [email protected]