Month: January 2019

Digitalization in Food and Beverage Industry

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Innovation is not just innovation, but it has become like a new famous song that everyone is listening too and the ones who have missed it are looking to forward to listen. So the song, I mean innovation is everywhere and expanding as well. Internet of Things (IoT), Machine learning, Blockchain, Artificial Intelligence (AI), and many other disruptive technologies are taking up the industries. I would like to share how efficiently Food and Beverages industries are taking the major benefits so from supply chain to packaging to waste management and the process goes on. Here are a few areas that are majorly impacted by the technology.

Production

IoT has given the organizations a new term “Smart” where everything is connected to everything. The IoT has automated the entire process of production. Here all the components are connected and real-time data from the systems are utilized to achieve maximum efficiency which results into best quality. These Real-time data provides more opportunities for predictive maintenance and scheduling which directly reduces the time consumed in unplanned and unorganized maintenance. The advancement supports us to the next level with smart sensing to reduce the time in any new product development. They necessarily do take care about the taste and preservation through smart vessels and packaging. Basically, the food and beverages industries are leveraging from the smart environment.

Consumer Analytics

This is one of the most important factors where the food and beverage industries are facing major problem. As it is really critical to look at the stock unit. A company has various food products, flavors, different size packets for different geographic locations which becomes very difficult to maintain as such in the stock units. IoT here came up with Smart Bottles, labels, and shelf with sensors to gather data and work on advanced analytics. This could really be a solution for the major concern to the industry.

Supply Chain

The demand for the product information is always greater and the supply chain. Supply chain helps with transparency, building brand loyalty, lowering inventory, and efficiency can be achieved by end-to-end visibility. For this visibility, industries are taking help of technologies such as IoT, Blockchain and advanced analytics. Product details are being captured such as moisture, temperature, etc. during the movement at different locations. Analytics are gathered and being analyzed continuously to alert before any deviations.

Warehouse Management and Inventory

A market is never the static its always dynamic and this nature brings a lot of things. This leads to integration between customer demand, procurement, and production. An automated inspection with inbound material and outbound quality are going to change the picture for same.

These are few just few areas where the technologies are playing a major role for Food and Beverages industry which are increasing the efficiency for same with better insights. The process of innovation is going to continue as the demand for fresh, healthy and hygienic food is always going to be the need of time, so the technologies will always sing the song of innovation.

Blockchain will take care of your resume

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We have always heard saying a single piece of paper or the one-page resume can decide my future but ultimately it does. A resume is the most important factor for the individual to represent themselves with their excellencies. We all understand how crucial a resume is for any candidate to get the job. Well, we can say for the first impression it is going to save you at all.

Blockchain is the tremendous technology and has emerged across every industry. Blockchain has played a major role behind Bitcoin and is expanding now. The technology is really expanding within various industries. We all know and consider blockchain for its security concerns which takes us towards trust so what if blockchain can give us resume, that can be handled by blockchain. Blockchain will change the landscape for HR as well, as it does have the potential to bring the revolution.

According to a survey conducted, among 2100 hiring managers found that 40% of employees were bluffing on their resume. This inability to trust the basic information on resumes and letters becomes the crunch in the hiring process. The solution for this came out to cross verify with multiple peoples but the truth is it’s difficult to find the certainty.

This is where blockchain is to crash the crunch out of it with a solution, there are several methods that will help to hire managers to know the certainty about the individuals on the resumes. Some of the universities have already adopted the blockchain, they are heading towards digitalization with the digital degree and signature of the authority. So, it would start college itself then there won’t be difficult finding the certainty which would reflect the validity from the base. These validations aren’t limited to certificates it can also be applied to an individual’s history and even skills. The organizations where HR department would use blockchain technology will have access to the profiles and thus the validation can be trusted.

Thus, Blockchain technology would eliminate one of the layers for the hiring process, where neither the candidates nor the HR would have to waste their time and efforts. A worthy time can be spent on evaluating a good fit with their corporate environment and what potential the candidate has got to match the company’s goal.

The technology will bring the next major innovation for HR. It would be much easy for the organizations to trust the information without putting much of efforts on validation. This would not only decrease the cost but would save from another meditators cost. This is also going to help the candidates by saving their time looking for other opportunities and getting quick updates about their recruitment. I think the immutable blockchain technology is going to help us with great efficiency and effectiveness of this end to end recruitment process make it much faster, effective, reliable and trustworthy.

Cloud-Native Applications are worthy investing

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When industries are planning to develop cloud-native applications and majority of them are already on the road to develop it. More than 60% of enterprises have started building their strategy for Application development on Cloud platforms. According to source forecasting has been made that double of current percentage would be moving on Cloud platforms. Cloud Platforms like Azure and AWS are redefining the businesses of the enterprises. IT industries are changing the game in technical solutions and cloud-native apps are one of them keeping enterprises ahead of the competition.

Enterprises are understanding the need for cloud-native apps and their advantages to them. Here are few of major advantages of developing cloud-native apps,

Auto-scalability:

Scalability is the feature every enterprise is looking for and this we can get from Cloud-native apps. They are been enabled with the auto-scale feature to handle the business needs continuously. This feature is very useful as it deals with complex issues. They don’t require to pay extra for anything they aren’t using. They have to pay only for the computing resources used and only for the time being it is used. This saves thousands of dollars of enterprises and they can expand the life cycle of the application.

Auto-manage:

As the traditional applications where the resources are been physically provided Cloud-native is different. Cloud-native applications enable automatic provision of resources. They provide self-service, on-demand, releasing of resources for computation and storage services. This helps the applications to run smoothly with any issue. The critical business applications run smoothly with allocating the resources on-demand directly from the application. These applications automatically handle the task of data analytics and get back to the pool after the execution of the task. This automation helps a lot to enterprises.

Auto redundancy:

Any failures occurring in the cloud-native apps are been handled automatically. They automatically handle the errors and take corrective actions to avoid them. During any failure, the application processing goes on smoothly without any interruption. The application runs swiftly without interrupting the service. This is executed so smoothly that even end user doesn’t know that there was an issue.

These are the advantages of cloud-native applications and with the help of these enterprises can improve their business processes with lower cost and minimized infrastructure overhead. Even the manual efforts would be reduced. They are efficiently scalable, automated, resilient, portable, and can be easily updated.

Enterprises should think over this and they should migrate their enterprise applications to cloud-native application architecture. This would help them to improve their business process and the results would be more efficient and better. But maybe before this, they need to analyze the necessities as application architectural complexity, level of efforts and other essential things for migration. As few applications require just specific code changing and testing while some are to architecture again maybe on PaaS or Saas. Therefore, it is essential to analyze all the necessities for the migration that is been required as efforts, costs and return on that investment as it is very essential to analyze how we can get benefitted from it. Many enterprises are innovating themselves towards Cloud-native applications and preferably Microsoft Azure is the choice.

To find why Microsoft Azure is the preference please read why you can choose Azure over AWS

 

RPA is like the Band-aid Feature for the Future

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Robotic Process Automation (RPA) is undoubtedly the future for every enterprise. The beauty is how every technology is emerging themselves with this process. According to the TechED 2018 event held in Barcelona last year, SAP has announced that they are going to add RPA to their software suite. The most interesting part they included about adding RPA was that they have chosen to build their own RPA capability instead of associating with any of product vendor.

This announcement was interesting by SAP of choosing their own capabilities. The product they represented at the TechED was with a great runtime environment, monitoring process, analytics, audit trails and other functional elements as a great platform. It also evolves machine learning platform and integration with SAP.

Another interesting and fascinating part was their vision of automation. SAP has a different vision for implementing automation, unlike other RPA products. SAP is focusing on native API-based integration. Thus, the walls for the garden are too high as for now SAP’s version of RPA will be limited to SAP. They may begin with S/4HANA and then, later on, moving ahead with Concur, Success factor, etc. Thus, in their announcement, there were many things to come yet which will be planned accordingly.

The momentum for Robotic process automation is an all-time high, the acceleration is at the speed. RPA is on fire, people have already started investing in the process by millions of dollars. The investment was with a high figure in 2018 and it will go on with this year as well. The prediction for the coming years is that every major industry would approach for the automation that would involve RPA. RPA has a broad view for the future with great insight for every enterprise.

RPA has so much to give us, it would be the healing for all those issues which were nightmares for the automation once. We can say RPA is a Band-Aid putting everything together in this modern workplace. RPA has got what all the businesses need. It is going to decrease the inefficiency and increase the efficiency; this transformation can help them to focus on more about what they care.

RPA has already started touching the larger enterprise suites as we saw SAP but like SAP even Oracle is also interested in the flavor. Every major industry is taking interest and looking forward to getting involved. Oracle and SAP have planned towards RPA while SAP has shown the broad view with its product suite.

Thus, the journey to RPA is never ending process because with the time we need to expand and so will the technology. Enterprises demand would never be limited and this unlimited need to be resolved every time with a solution. RPA is an opportunistic approach which has a broad vision for the future. The automation has yet to come with many things that enterprises might need in future and cover up the entire broad spectrum.

Why you can choose Azure over AWS?

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Clouds have always been wonderful, whether clouds above us or the cloud technology. Here we will talk about cloud technology and when we hear the word cloud technology Amazon Web Services and Microsoft Azure comes in our mind as the leading cloud service provider. Not to forget they are on the Gartner’s Quadrant for Cloud Infrastructure-as-a-Service (IaaS). AWS is the old player which was launched back in 2006 whereas Microsoft Azure came around 2010. Though there are a lot of points where they are always compared but Microsoft has advanced Azure over the years with amazing features and capabilities to exceed its competitors.

These are some major points where Azure comes over AWS.

.Net Compatibility

The .Net programming language is been preferred by many enterprises which mainly use .Net based apps. Azure’s compatibility is excellent with .Net language which is the major benefit which indirectly gives Microsoft a clear way path above AWS. Azure is been structured in such a way that supports working both old and new applications using the framework. It becomes easier for organizations to switch their windows app to Azure cloud. As there are many organizations using .Net based apps so azure becomes the best choice to choose.

Security Concern

Security Development Lifecycle (SDL) is a leading industrial assurance process, Azure has been designed based on the SDL process. European Union’s data protection has approved Microsoft, as they were the first cloud vendor to be approved. Azure comprises security and private data that stays protected and secured on Azure cloud. Microsoft was also the first to embrace new international standard for Cloud privacy. As Microsoft assures about the security concern and all operations on Azure cloud.

PaaS Capabilities

AWS and Azure both have similar capabilities for IaaS, for any virtual machines, storage, and networking. When it comes to PaaS capabilities, Azure provides the stronger which is an important aspect for cloud infrastructure today. MS Azure PaaS provides application developers with environment, tools and building blocks that they can easily build and deploy to new cloud services. The Azure PaaS helps with lot of infrastructure management which is been supported by Microsoft. It provides a vital “DevOps” connection which is very helpful with monitoring, managing and making the app better. Thus, Azure PaaS have the capabilities that lead the organization to innovation.

Integrated Environment

Azure gives us a fabulous integrated environment for developing, deploying and testing Cloud apps. Clients can easily choose the framework they wish with open development languages. It also provides flexibility for Azure migration. Thus, services like mobile, web, APIs and templates can easily be used to develop Azure app. Azure PaaS having extensive capabilities brings apps, data, and devices together as on both on-premises and Cloud as well. Its flexible toolset helps to solve the integration problems or needs, from on-premises to coordination with other things

Though there are still much where Azure is coming over AWS and the enterprises need to look over it. It’s just not about choosing Azure over AWS or AWS over Azure but choosing the real cloud service as per your requirement.

Transforming BI with AI and ML

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With numerous ways to transfer and process information, we have witnessed the dawn of the digital era. We have seen data being shared via text, images, videos, and various other forms. Data has changed the way business is being done. It has changed the entire enterprise paradigm. Moreover, from the last decade, the usage of technologies like machine learning and artificial intelligence has been widespread. AI has transformed the way we live, work, and shop in many different ways.

Realizing that answers to most of their business challenges lie in data, companies are now turning to machine learning and AI by supercharging performance and implementing innovative solutions to address complex business problems. The combined power of AI and ML is improving the ecosystem of business intelligence which is essential for making insight-driven decisions.

The growing importance of business intelligence

With business intelligence, enterprises receive faster and more accurate reporting as well as analysis. They tend to make better business decisions, improve employee satisfaction, and enhance data quality. They are able to get a 360-degree view of their business which makes it easy for the decision-makers to visualize problems and take proactive actions to resolve them before the situation worsens.

Role of ML and AI in transforming business intelligence

BI is embracing features and capabilities that fuse machine learning and artificial intelligence with traditional BI offerings. With advanced predictive analytics, BI is transforming from providing traditional queries and reports to allowing users to understand trends and future possibilities, predict possible outcomes, and make recommendations. This changes the conventional role of BI of answering, “what happened”, to an AI-driven BI that answers questions like what will happen next, and what measures should be taken in the future.

Tools like Tableau, Power BI, Qlikview, Microstrategy, Logi Analytics, and Splunk prove that with the combinational power of ML, AI, and BI, businesses can achieve a lot in lesser time and with less effort.

Ending intuition-based decision-making with AI and ML

Analytics helps companies to transform raw data into operational reporting insights to reduce decision-making based on intuitions. With vast amounts of data at your disposal, more decisions will be rooted in data analysis than on instinct. However, data-driven tools often require manual development processes to aggregate sums and averages. The findings derived by such analytics methods often lack a holistic reflection and do not generally put statistical significance into consideration. Models developed by leveraging AI and ML facilitate automated learning with less or no explicit programming. This gives businesses the ability to efficiently analyze enormous volumes of data that may contain too many variables for traditional statistical analysis techniques or manual business intelligence.

Machine learning algorithms, when trained properly, automatically discover the signal in the noise, and eliminate the possibility of getting insights that are erroneous. It becomes easier for users to detect hidden patters and trends lying in their data.

Over time, this trained model can teach itself to become more accurate. The model then adapts itself whenever new data is introduced.

Beyond predicting

Perceptibly, businesses are more interested in outcomes and actions as opposed to mere data visualization, interpreting reports, and dashboards that show them how they did in terms of sales or revenue. Hence, by adding an element of machine learning and AI, businesses not only get insights into historical data but also get an answer to “what next”.

The power of machine learning and artificial intelligence goes beyond understanding what has happened to offering the best evaluation of what the future holds. Classification algorithms, specifically, form the foundation of such predictions.

Advanced algorithms are trained by running specific sets of historical data through a classifier. With the help of behavior patterns from the historical data provided to train the models, ML algorithms determine how likely it is for an individual or a group of people to perform specific actions. This facilitates the anticipation of events to make further decisions.

Providing the best suited AI-powered BI services

The principal goal of business intelligence is to provide decision makers with the capability to better see the relationship between trends, patterns and behaviors for better decision-making and optimization of resource like budget and people. At Stridely Solutions, we offer you the optimal BI services powered by AI and ML.

The time is utilities need to rebuild

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Where industries are pushing themselves towards technology which is the future there are still industries that need to push themselves a more, not just to adopt the technology but sustain with them. I don’t really want to use the word “sustain” but “rebuild” would work. As with every industry, utilities are also taking a major shift with smart solutions as sensors, smart meters, intelligent devices, and IoT system. This is not just about shifting but they are facing a major challenge in managing the data which is been generated with these smart devices. A large amount of data is been generated by MDMs, ERP, CRM and SCADA systems. These data if handled properly can give a deep and better understanding of assets, supply operations, consumers and demand. As for now, it is quite hard to achieve because of the traditional data management that is still being used by utilities.

The reason behind they lack is,

There is no real-time visibility of data, about consumption or if to be tracked, if this would be possible it would help them to know exactly the consumption, wastages and related costs.

If data management is a challenge that we can’t hope for scalability, so there will always be an absence of a scalable data which would be collected from numbers of meters and the other data records.

There is no such system that can notify us before damage, theft, leakage or any major utility loss. Hence the consumers and the utility providers can’t do anything about it, as it is something which comes without any alert or awareness.

There is nothing like a predictive intelligence system that can predict failures, outcomes, and events for better operational efficiency.

Thus, utilities need to rebuild their operations and recognize the impact of data systems. What if when utility gets to know about the failure or loss of assets and operations in advance. This would help them to take preventive measures or plan its maintenance before any damage occurs. Though they can realize by adopting predictive analytics capabilities which would help them to enhance their performance, reduce errors and increase the customer-centric values.

According to the source, 30% of the utilities are taking themselves off from the traditional data system to data analytics solutions that give better insights and actions. They can monitor AMR/AMI systems, get the real-time insights on distribution and consumption, manage it and optimize the consumption. They can identify the anomalies. Thus, utilities can create consumer awareness with a pattern.

This can also be beneficial to water utility customers with a smart meter that encounters data systems challenges. By managing millions of smart meters which can send more than millions of records every year. It also helps with real-time visibility of consumption and every data. It also sends an alert or notification for any of usage or damage. It also gives the predictive analytics that can enhance and optimize the performance.

Hence 30% have started and I think its time to shift for the rest of utilities to rebuild the operations.

Robotic Process Automation (RPA)

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Human and Robots are going to have a very engaging relationship in the future as it has started already. Automation would be the survival for the industries. The combination of both requires a process. Robotic Process Automation is the technology where you are allowed to configure computer software, a robot to imitate and integrate the human actions with the digital systems to implement a business process. RPA exploits the user interface to capture data and manipulate the applications just like humans do. They are developed in such a way that they can perform just like the humans even better than them. An RPA software never takes rests and makes no mistakes and the performance is better than a human.

RPA is very different from the other traditional IT solutions. And this difference gives a great impact, it allows organizations to automate with concerning time and cost. RPA is a non-disruptive process, that leverages the infrastructure without any disturbance or loss to the systems, which if happens becomes an expensive affair. RFA does not only take cares of the cost but also solving the time complexity. Thus, RPA has a very different approach of the automation process with a comparison to other traditional solutions.

Fast Implementation and better results

Implementation is always a factor for any technology, why the industry should adopt? What are the benefits and lots of questions? But when it comes to RPA, I would like to take you an example, from a source an HR service provider, were processing 2000 sick leave certificates with an average of five minutes per of them. Then they implemented an RPA solution and within weeks they achieved 90% process automated. The task became easier for RPA to extract data from SAP, inserting information into the customer’s system and then print them. They also got their results within weeks, which was a great return investment for them. They got out with no errors, less manual efforts and processing time reduced by 80%

Reduce efforts

This is one of the most realistic and factual stories, a retailer always finds difficulty closing reports to validate information across his hundreds of stores. The employees used a manual and same lethargic process for these reports to work out which indirectly was time-consuming and because of it more manual efforts were added. By implementing the RPA process the manual process got automated and the employees which were engaged in the manual process can focus on customer-centric activities. The RPA process successfully closes the report to one server and read the information, after reading it settles the information that is needed for closing reports.

Time constraint

Time is the most important commodity or factor to be considered. An insurance company with 40,000 clients globally automated the credit limit request process. This was a real challenge for the underwriters gathering information manually from internal and external sources. RPA, saved their time by 2400 hours which helps employees to focus on customer activities.

Scalable

RPA has been playing a major role parallelly across different industries and geographies from desktop to cloud environments. Thus, it can be easily deployed with minimal cost.

Hence RPA is the technology that is not only for human but with human, so how fast is your industry approaching to RPA?

Do you have a Successful strategy for AI?

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When AI is the inspiration for today’s industry where everything is connected and advanced. Complex algorithms taking place for most complex situations. From start-ups to technological gig to asset concentrated industries everyone is bounded with AI. Industries and their teams working on their own plans and strategies for their AI. At another side of the picture where advancement is the one side and the other is how effectively we can use Artificial Intelligence?

Industries are still struggling to develop a successful Al solution. There are could lots of reasons that why they cannot, maybe due to the incapability of data scientist or may be insufficient knowledge of data literacy and so more. At the bottom of the truth, the common reason which comes out is that of no infrastructure that can implement data science operations and algorithms. And in order to implement, industries have to understand and fulfill the basic requirements as data literacy and data collection. We would need to understand the hierarchy as what is required first at the top level and what after that, so considering the hierarchy AI should be at the top of the pyramid and else other basic requirements to the bottom. So, it becomes clear to go at the top level we have to clear the bottom ones.

Here are few steps industries should consider while implementing AI,

Collection of Data

This is the first and very important point to be considered. What data is being collected and how it should be from sensors, devices, or machines? What and which data to analyze? Is the data accurate that can help us with better results? A data which should be accurate that helps make advance decisions. So, the collection of data should be the first step to get a successful strategy for AI.

Data flow

After collection of data, we need to see if we have scalable and reliable architecture, ETL process and proper IT infrastructure to handle this. The question is like where do we store data and how does it flow? How easily it can be handled with structured and unstructured data. So for the seamless extract, we need to know it.

Explore and Identification

Industries have an ocean of data and to dive down through it we need experts who can deal with any kind of data and find out the hidden insights. This is where Data Science and Data Scientist comes in the picture. Data science is all about methods, processes and systems that help us to generate required insights. This is the field where statistics and analytics are being seen together. Data scientists are the wizard that refines the data removes the anomaly and make the data useful for further processing.

Optimize

So after the understanding of Data science and the role of data scientist, experimentation or testing framework must be in place to deploy. This should go until we get a satisfactory result which will help from the classification and optimization of new data accurately.

After these steps, you would come up with a great strategy for AI Implementation which would now be ready for your data.