Executive summary

In today's world, regardless the size or type of the organization, it's imperative for an organization to keep pace with the current challenges, transform itself or left behind. Lack of coordination between cross functional teams can make it difficult for the business leaders to take agile decisions. With Anaplan HyperModel, teams across organization can work together, build robust models tackling the operational complexity & enable the decision makers to take the correct approach.

HyperModel capabilities drive three key performance benefits

• Robust - Every organization requires a robust modelling capability to accelerate the decision-making process. With HyperModel, teams can add more dimensions, years, scenarios, and data into a single model for extensive analysis & long-term planning. Furthermore, teams across the organization from different departments can come together & collaborate on a unified, robust model as part of connected planning.

• Scalable - With HyperModel, teams can expand new plans, load more historical data, adjust forecast and update models as when it is required without archiving any data sets or splitting up the models. Furthermore, business does not have to rearchitect their models to avoid data storage issues.

•  Adaptable - HyperModel with improve performance & functionality, can take care of any multi-dimensional scenarios with large-scale data sets for in depth analysis. Modelers can build more what-if scenarios incorporating potential business challenges to predict possible outcomes.

Issue: After installed and configured EPM 11.2.2 environment, end to end SSL has been implemented for the below components.

OHS, Hyperion Financial Management, Financial Reporting, Financial Data Quality Management, Enterprise Edition, Calc Manager and WebLogic.

All components seems working as expected; however whilst try to export artifacts under Application groups in Shared Services for FDMEE & Calc Manager, the migration status report shows the status Failed and the error as below:

Error "EPMLCM-13000 - Service currently unavailable"

Cause: This has been identified by Oracle as a BUG 32079785 - ERROR "EPMLCM-13000: SERVICE CURRENTLY NOT AVAILABLE" WHILE IMPORTING FDMEE ARTIFACTS

Possible Solutions to fix this issue --

Solution 1: You can try adding a directive to the ssl.conf file of Oracle HTTP Server:

Copy</IfModule>

LimitRequestLine 20000

</VirtualHost>

</IfModule> 

Solution 2: Try applying the Patch Set Exception (PSE): 32101854 which was provided by Oracle Development for the Release 11.2.2.0.000 to address this Bug.

Solution 3: Alternatively, you can also try the below steps which we had followed to proceed with the environment. 

Import and Export FDMEE Schema from other environments such as intermediate server (11.1.2.4) to QA (11.2.2); and from QA to Prod, DR and Dev.

Overview

Natural language processing, widely known as NLP, is a subfield of artificial intelligence. This is used to create a link between human and machine. NLP helps machine to understand human language by educating or train them based on rules or data.

NLP is mainly used in Speech Technology, OCR, Machine learning etc. Most common example we can consider of NLP is email or text filter, predictive words in email or text, digital assistant, data analysis etc.

Now researchers have taken NLP into a next level where a machine is trained to understand financial market's up and down. Using its data analysis capability, a machine can now predict how a specific stock price will behave in future.

Now this is important to understand why we needed such an AI powered system which will tell what stock to buy or not. This can be also done by a human also. But here machine beats human by it's computational power. It can analyze large number of historical and current financial data, data from social media and news and then analyse it and finally provide the prediction.

Investment is one of the most difficult decisions which may result in huge profit or loss according to the investors' analysis. It is very crucial that the extent of human errors in these pressure situations is reduced so that the profit can be maximized. The technical analysts believe that the future price can be forecasted using the past price movements.

Sentiment analysis uses text mining, natural language processing and computational techniques to automatically extract sentiments from a text. It aims to classify the polarity of a given text at the sentence level or class level, whether it reflects a positive, negative, or neutral view. In stock market prediction task, two important sources of the text are used either social media or online financial news article and historical stock prices. Sentiment analysis decreases the risk factor by informing the investors about the intricacies of the decision they are about to make. The stock closing prices for some future date could be predicted by training the machine learning models by providing the stock prices for previous dates. When sentiment analysis is applied on stocks in news from moneycontrol.com regarding the public sentiment or opinion on that stock. Then, it becomes evident that whether to invest in that stock or not.

Block diagram representation:

Above diagram shows how data can be fed to a machine and then rules will be applied to those data to make the prediction. The more data machine consumes to train the more accurate result can be seen.

To show how this prediction model works I have created various case studies and tested with Amazon, Facebook and Netflix stock prices.

Note: These codes are written in Python using google colab.

Programs are created for this article are very simple and it shows how to train the machine with dataset and predict future stock prices. I have used SVM, LR and Decision tree model. These programs uses downloaded stock files from financial site (Yahoo Finance) as input data. Also, these programs can be more enhanced which can read from all type of social media news and multiple financial files.

SVM model:

Support Vector Machine is a supervised machine learning algorithm which can be used for both classification or regression challenges. However, it is mostly used in classification problems.

LR model:

Linear regression was introduced in statistics as a model to understand the relationship between input and output numerical variables. But later this is used in natural language processing. It is both a statistical algorithm and a machine learning algorithm.

Below are the steps used for Decision Tree Classifier with Amazon, Facebook and Netflix stock files.

Case Study 1: With Facebook Stock

We are loading the stock file here.

Next step is making 'Date' field as indexed field.

Here we are using identifier 1 or 0 to understand when stock prices gone up or down. We are monitoring 'Close' field for this purpose. So, if the price is up next day it will show as 1 and if the price is down then it will show 0. Please refer 'Price_Up' column.

Next step is manipulating this dataset for further activities:

 N

Above score is predicted by Decision Tree Classifier.

Below is the comparison of actual and prediction data:

Case Study 2: With Amazon Stock

We are using same program here with different stock file.

Prediction as below:

So far, we have seen Decision tree model, the prediction score is not high enough. Therefore, Support Vector Machine Model or Liner Regression Model comes into picture. Below studies have been done with both SVM and LR.

Case Study 3: This has been performed with Wiki data and Facebook stock price which is available in quandl

First, we will install the required packages as below. Also this is a new program created. Please follow below series of steps.

SVM model score:

Linear Regression model score:

LR vs SVM prediction:

Above case studies help us to understand how an AI based prediction system can be built. Also, the prediction score will depend on multiple factors like complex logic, training dataset etc. This process is not just simply trying to predict a value but it works on every stock related sentiment and risk analysis.

Now we will perform another case study which will show the graphical representation of prediction.

Case Study 4: Graphical representation of Amazon stock price prediction

To showcase this below steps/codes were built. 

Graphical representation of Original and Predictive values in Tree model:

Graphical representation of Original and Predictive values in LR model

As mentioned earlier, this machine can perform more accurately if it is built to handle massive load as training data equipped with better hardware or processor etc. Also, this can be interfaced with any number of language feed. The machine will translate any feed to a common machine language and then perform its analysis. 

Reference:

1. Wikipedia

2. Yahoo Finance

3. Forbes

4. Google Images

Exploring Anapedia

What is Anapedia?

Anapedia is a reliable source for Anaplan. It is the home for Anaplan's in-depth technical documentation. It is an encyclopedia for everything in Anaplan which is divided into various topics as listed below;

Ø  Administration and security - enable administrators to make the required changes to the Anaplan environment and workspaces.

Ø  Anaplan Home - assists as a tailored access point and overview to Anaplan experience, with quick access to pages, models, favorites and apps.

Ø  Anaplan mobile app - enables you to view and edit your worksheets and boards and perform data analysis on the go from your mobile device or tablet.

Ø  User Experience - allows you to review and modify exhaustive data from models in Anaplan

Ø  Application Lifecycle Management - to manage the governance, expansion and upkeep of your Anaplan applications

Ø  Calculation functions - it is a complete reference to Anaplan's in-built functions

Ø  Dashboards and Visualization - building dashboards in the modelling experience

Ø  Data integration - Anaplan offers integration possibilities at various levels

Ø  Extensions - Microsoft office Add-ins helps in extending Anaplan experience

Ø  Import and export - provides easy solutions for importing and exporting data

Ø  Modeling - Learn the basics of creating an Anaplan model and proceed with each passing level.

Ø  Resources for Anaplan - there are more resources available for Anaplan like downloads, support, academy training and community forums.

How to access Anapedia?

 Within an Anaplan model, the Help menu provides users with instant access to:

Ø  Context - specific Technical Documentation

Ø  Anaplan Community articles and discussions

Ø  Customer Support

 Click the Help menu icon to take a closer look at the resources that are available.

              Select each of the Help menu options to review the available support resources.

B.                           Anapedia can also be accessed directly through a web browser with the link https://help.anaplan.com/

My Anaplan Certification Journey

Tell me and I forget. Teach me and I remember. Involve me and I learn. - Benjamin Franklin

These words by Benjamin Franklin are true reflection of Anaplan's Academy course as the course not only provide the theoretical knowledge but also gives a hand on experience of building the models. So the first question is What is Anaplan and what are the models that I am talking about. Anaplan is a cloud based platform that enables planning. Models include a full business use case. What is a business use case? It is an issue that an Anaplan model is built to address. Most often, these are areas such as: Territory and Quota , Sales and Operations, or even Supply Chain Planning.

Level 1 Training Program - I started the Anaplan learning journey with the Level 1 certification course and entered the world of Anaplan. The course covers all the basics from basic navigation to model building steps in an interactive way. The short video lessons along the way also makes the learning more fun and addictive. The way course is structured makes it easy to follow along and build the model and if you are facing a difficulty in understanding any topic  you can go back to the course any number of times or take help from Anapedia. In Level 1 Model Building, I got a chance to create a new model, set the Time and Version dimensions, create lists, modules, and line items, import data, use functions and module line item references to build formulas, build User Experience pages with charts and graphs, and review user and role permissions and access settings. After all the model building activities are finished there comes the time to take the certification and once you are done with it voila you are Level 1 certified.

Level 2 training program -  Level 1 gives a glimpse of the road ahead for level 2. Level 2 course is the advance version of Model building and make the journey a bit more difficult but again the structure of the course and the mini lessons provides the base that we need to build the model effectively. In Level 2 course, we will learn more advanced model building techniques and practices that one should follow, as well as utilize the skills that we have learned earlier in Level 1 program. The Level 2 program is organized into three sprints - like a real project and the challenges that come along with it. In each sprint we have to complete some user stories like we do in a project to focus on the need of users. There is lot to learn from the Anaplan academy in order to build the efficient models and the course makes it easier to do so. There are lot of things that I like about Anaplan some of them being the ease of navigation from one element to another and different segments for the model building requirements. After all the hard work of creating models and completing all the lessons there again comes the time to give the certification exam and become Level 2 certified. I was bit nervous this time but again I succeeded in qualifying the exam.

The Anaplan Way -In order to get Anaplan Certified Model Builder tag we need to complete one more course i.e The Anaplan Way. What is Anaplan Way? Anaplan is a unique software and requires a different approach to go forward. The Anaplan way includes all major stages during an execution of any project. The Anaplan Way methodology will help the team quickly build models that hone in on the customer's most important requirements. The Anaplan Way cornerstones provide the basis that is required for an execution of a project. These cornerstones should be put in action during each stage. They are:

• Process: The process that the Anaplan model supports.
• Data: All the data components required.
• Model: All the stages of the model [Design, Build, and Testing].
• Deployment: A plan to make sure that the Anaplan model and new business process are embraced in the corporation.

After completing this course you are now Anaplan Certified Model Builder and your certificate is ready to be downloaded.

New User Experience - After completing the Level 2 now I am moving forward and excited to complete Level 3 certification. On my way I came across the new UX as I have completed my level 2 training with the classic dashboard. With its intuitive approach, clean look and streamlined navigation, the New User Experience makes it easier for end users to use Anaplan to do their jobs, and it's easier for builders to create tools for them. The new UX includes different page types to meet a variety of needs, can access data across the organizations models and is responsive to different sized devices from mobile and tablets through large projection screens. The new UX moves the classic dashboard to a new generation of dashboards where it gives a new look and feel to the dashboard elements and makes it more pleasing to the eyes.

As the Chinese Proverb says that Learning is like rowing upstream, not to advance is to drop back. I continue my journey with Anaplan to become a Master Anaplanner. Looking forward to new challenges and new learning that awaits me.

Anaplan Tips & Tricks

This document outlines some of the tricks to use (for users) and configure (for model builders) Anaplan application effectively. Look for Underlined and Italic text throughout the document for helpful tips.

1.  Know the application: For users, first thing is to know the application and here's a quick introduction to how Anaplan looks like:

1.1. Landing page of Anaplan: The models are represented in the tiles - this view can be easily changed by clicking three parallel horizontal lines on top right of screenshot. Chose a view which best suits you.

The list view:

1.2.   The models are auto arranged based on when user visited the model but there could be some models which are required to be visited less often but are critical - The models can marked as favorite and filtered easily for quick access:

Filtering as quick as marking the models favorite - Just click on the star on the header row to show only favorite models:

2.       2. Know the model: The model for end users comprises of set of dashboards which can be accessed from the left pane. The pane can be closed and opened using the horizontal arrows. If, you are planning to work for a longer period on one dashboard, it is better to close the pane to have a wider view of the dashboard.

V

3.       3, Know the dashboard: Dashboards are the interface designed in Anaplan for the user interaction. A dashboard will consist of grids and charts, input and calculated numbers/values, action buttons etc. Any cell that has a blue colored text is editable and black colored text is read only.

3.3.1. A good model builder will make sure to include the instructions on the dashboard. Instructions, if written correctly can help users to take appropriate action on the dashboard. Usually, instructions will be in light blue colored box.

3.3.2. Synchronization: Synchronization is a powerful feature in Anaplan. The dimensions are available in Anaplan as dropdowns (or in Anaplan language page selectors) - As name indicates, the drop down impacts the whole page, if synchronization is set across grids and charts. Drop down is not the only way for synchronizations to work. Users can also select a value in the rows and if the same dimension is in page selector in another grid, the grids will synchronize.

3.3.3. Drill Down: Drill down is another useful feature in Anaplan. Drilling down is very simple. Right click on a cell à Select Drill down option and it will show up the calculations. Users can keep drilling down to any number of calculation levels. Quicker way is instead of right click, users can press F8 after selecting cell.

3.3.4. Understanding the formulas - After drilling down, it is important to understand the formulas - Anaplan formulas are usually easy to understand. If the line item which is being referred in a formula belongs to another module, the line item structure would be <Module Name>.<Line Item Name>.

ALM

Anaplan Lifecycle Management

Thanks to Anaplan's process of ALM, users can easily manage their models. It's easy to understand and easier to use like every other function of Anaplan. So, let's dig deep into ALM.

ALM?? What is it? 

ALM is the process of managing the development, testing, deployment, and ongoing support and enhancements of the models.

But before we go to what ALM is, lets understand a few features.

u Standard mode, Deployed mode, Revision Tags, Compare and Sync.

Standard and Deployed Mode

Standard: This mode is for model building and for developing the model where the data can be changed. Used in Dev model.

Deployed: This mode blocks any modification being made to the structural information. Used in Prod and Test model.

Revision Tags

u They capture a model's structural information and not its Prod data, at a point in time.

u This can only be used in models in standard mode

u After making at least a single structural change, we can revert a model back to the most recent revision tag.

Is it possible to Create a Model from a Revision Tag?? 

Yes, it is, if you are Workspace Admin (well, that goes without saying because if you weren't you wouldn't be able to do half of the Anaplan magic tricks explained here).

You can also revert a model to the most recent revision tag, removing any unsaved structural changes made by anyone. Lucky for us, the model's production data, contents like production lists, will not be affected. It is used to discard undesired changes made in a source or development model. However, this action is permanent and cannot undo it. Comparison of revision tags between the same models is possible but synchronizing them is not an option.

Comparison and Synchronization

When two models, source and target, are structurally compatible, structural changes made to the source model can be synchronized with the target model.

What can Compare and Synchronize do? 

The major flow of data is from development model to a test model where they are in standard and deployed mode respectively, from test model to production model where both are in deployed mode and from development model to production model where they are in standard and deployed mode respectively.

Compare and Synchronize is a three-way process:

Firstly, choose two models to compare, the source and the target. The target model here being Current_Accruals_Prod_ALM_R1.0 is compared to the source model here being Current_Accruals_Dev_ALM_R1.0 and changes are moved from the source model to the target model.

Secondly, from the source model select a revision tag and compare it against the latest revision of the target model. We will get to see all the differences in the changes made between the two revision tags.

Finally, once you synchronize the models, all the changes from the source model are passed on to the target model. A successful sync will mean that the models have the same revision tag.

Voila! A novel revision tag is created in the target model.

 In the target model, the change will be made, and the revision tag will be added.

Important Principles:

·        Models must be structurally alike or compatible. This is only possible if the target model's revision tag is an earlier version of the source model's revision tag.

·        Permissions required

·        All structural changes are passed on

·       One-Way Sync - changes may be passed on from source to target models and not vice versa.

·        One-to-One Sync - can pass on many changes to only one target at a time.

·        Do not make structural changes to target models.

Confirm that following have been checked in the source model before synchronization:

 production lists contain operational data

·        production imports are selected

·        revision tag is created with the latest changes in the source model

The hotfix can be managed without impacting the work in progress as shown in:https://community.anaplan.com/t5/Best-Practices/Save-Incomplete-Changes-when-Synchronizing-in-ALM/ta-p/33595

Application Lifecycle Management Summary

With the increase in the use of various Anaplan operations, so does the complexity increase to replicate each change from a deployment environment through a testing environment and finally to a production environment.

ALM is that feature of Anaplan that provides effective solutions to these complications. With ALM, you will be able to promote changes through development, testing, and production using a controlled and consistent approach. The capabilities of ALM is such that you will be able to create and govern enterprise-grade applications which will help adjust and alter to meet the rapidly changing business wants.

ALM can be called as the modus operandi of handling the development lifecycle of applications, from design stage to deployment to business users using the application. There are broadly categorized into the following stages:

Design, all you need according to your business demands. You may create user stories; structure, criteria for success, and major deliverables, schema diagrams, modules, and data flows; wireframes; and prototypes to achieve the desired projects goals. Chart out the models required.

Build: create models required to make up the application.  This stage being early in the process, you may not have any production data and so it's not necessary to load application. Sanitized data can be used while creating modules, lists etc.

Test, test, and test in a million different ways. Usually, functional and performance testing is done and if that passes, the next step is to do user acceptance test for the application built. You can use a separate workspace for testing.

Deployment is that stage where the business users get to use the application. To avoid all mishaps production application will be in an independent workspace. Production data can be imported from an external source or data hub.

Once the deployment is settled the application will have to deal with enhancements, bugs to resolve, new models to bear some of the weight of the existing one, the development lifecycle will be perennial.

Thus, in a very efficient manner, ALM helps us in managing different models.

When one starts learning Anaplan, we should be familiar with the basic terminology to build good foundation with Anaplan. We often hear some basic words, and which will be throughout your Anaplan journey (APPHUB, WORKSPACE, MODELS, DIMENSIONS, LISTS, MODULES, LINEITEMS, DATA IMPORTS/EXPORTS, DASHBOARDS). There are many functions and resources in Anaplan which will help build models and start working with various types of data. To learn Anaplan, we will have to explore modelling and model building articles.

A separate workspace is given to each company and may contain its own users and any number of models. The basic structure of an Anaplan model is built by Lists, Line items and Modules which represents each aspect of a business. Dimensions in Anaplan can be linked and updated with data from another model whereas models are independent. A group of related items are called Lists e.g., ppl in a department, products, regions, or entities. These are the basic elements in Anaplan, as they define the structure and content of a model. A dimension is one which measures or defines the characteristic of your data. It can be calculated or changed to help answer business, observe market trends, or assess various situations for planning purposes. Modules are one of the components of Anaplan model and comprised of lists, pages, line-items, and timescales.

End users' primary interface is called as 'Dashboard'. A dashboard consists of grids and charts published from modules in a model. There is no limit for grids and charts in a dashboard you can have as many as you like, and these elements can be published from different modules. A separate view is created in a module to publish it to dashboard. Versions dimension enables you to compare actuals and forecast data. Charts will add good visual impact to your data and help us to spot areas of improvement and successes. Different kinds of charts are provided based on the data that we are working (Column charts, Bar charts, Pie charts, Line charts, waterfall charts, combination charts, Timeline charts, funnel charts). Based on the data that we have we can choose appropriate charts to create different kinds of reports.

There are two types of approaches while building the models, top-down or bottom-up. Either it is top-down or bottom-up approach, need to identify the business functionality. The basic lists that makeup the organization are regions, products, and ppl. Later you can keep on adding dimensions to the data to enable us to see the organization in various ways. List hierarchy helps to support model structure and workflow.

Users in a workspace might be common to all the models in that workspace, components that belong to the model such as dimensions are local to that model, but these components can be linked and update with data from other model. Model recalculates automatically when some change is made to the data. Data to the model is entered manually or using import actions or derived from other line items within the model using calculations. Data imports within models happen using command or import actions between models. Within the model based on the functional area, modules are grouped together to identify them easily.

In Anaplan one should follow certain best practices while creating lists, modules, and formulae. While building the logic, one should not use SUM and LOOKUP in the same formula as it hits the performance of the model. Minimum properties should be created in the lists or instead we can create separate modules for replacing those properties. Within the modules, try to use TEXT format for very less number of line items. In summary tab, using SUM will also impact the performance of the model. Using TIME RANGE and SUBSETS will help in increasing the model performance. Break the very big formulae into smaller by creating multiple line items thereby increasing the performance of the model. So, these are some of the optimizing technics in Anaplan.

Now, new UX has come up with few new additional features for the users. There is a provision to access multiple models and create a dashboard as per business requirement. Updates are reflected in new UX dashboard immediately as you update the views in the model that are initially used to build the dashboards. We will look forward to get new updates from Anaplan going forward.

Anaplan Business Continuity (BCP) & Disaster Recovery (DRP) Model

Delta Airlines, California DMV, Breazeale Sachse & Wilson LLP etc. - these are few names which we don't get to hear much however all these companies have a common story to share.

So, what is this common story? The answer is simple - Improper business continuity & disaster recovery plan resulting in huge financial losses & goodwill.

We must understand the fact that no matter how careful we are, disaster can strike any business, anytime, anywhere. All we can do is take proper precaution & learn from experience.

What is Business Continuity?

In today's world, organizations need to protect themselves from unforeseen business interruptions & its financials impact. In simpler terms, a business continuity plan ensures that your business remains operational when a natural disaster or any other crisis affects your business.

For example - Year 2020 was a watershed moment for us due to the COVID pandemic. Many organizations had to move from Work from Office "WHO" to Work from Home "WFH" model while others had to shut shop temporarily or permanently due to improper business continuity plan. It's important to have a proper business continuity & disaster recovery plan in place to safeguard organization's asset, people & property.

Why Business Continuity & Disaster Recovery plan fails?

To be honest, no one would like to create a business continuity plan which is likely to fail eventually.

So, the question is why a well-defined thought-out plan fails? Let's talk about some common reasons on why business continuity & disaster recovery plan fails -

Some key example where business continuity plan failed -

• Delta Airlines - Back in 2016, the company suffered a huge IT infrastructure outage, resulting in $100 million loss in revenue. The disaster could have been avoided if the company had an effective data recovery strategy in place & a modern back up system

   

• California DMV - In the same year, California DMV had a huge malfunction when their backup system went offline due to power outage. The DMV was offline for the consumer for several days damaging company's reputation

   

• Breazeale Sachse & Wilson LLP - Back in 2005, Hurricane "Katrina" battered the east coast of the United Sates causing widespread damage & destruction. Breazeale Sachse & Wilson LLP, the law firm lost all their confidential documents because they used to keep everything in hard copies at site. This could have been avoided if they had a proper backup & recovery system

Now that, we understand what business continuity plan is & its importance, let us discuss on how Anaplan would like to address some these issues -

A.  How Anaplan Offices are spread across globe?

Anaplan has 17 offices covering multiple continents & time zones. Its global headquarter is based out of San Francisco, California; however, its cores development & technical support team is based out of York, UK. In event of any unforeseen circumstances, all development & technical team can work remotely using secure VPN connections, to provide ongoing support.

B.  Data Centers & Back up Model

Anaplan Infrastructure is primarily hosted on Equinix International Business Exchange (IBX) data centers, based out of Virginia, and Amsterdam with 24x7 x 365 coverage support. To ensure data integrity, all applications & customer data are stored within the data center itself.

All backups (Workspace & Models) are maintained at both primary data center & various AWS facility like Ireland or Oregon etc. In event of any disaster, the secondary infrastructure can be activated with minimal downtime & disruptions.

C.  Disaster Recovery Plan

In event of any major catastrophe resulting in complete loss of primary data centers, the backup AWS facility will be used as a recovery tool. Anaplan runs a disaster recovery plan on a quarterly level & it's well documented

D.  How to prevent Cyber and physical attacks?

To counter increasing number of cyber-attacks, Anaplan has contracted Verisign to mitigate DDoS. Any unauthorized connections can be restricted by built-in firewall. Customer can access Anaplan only via secure encrypted HTTPS / TLS connections. To ensure secure infrastructure, vulnerability scans& penetration tests are performed regularly.

The data centers have 24x7 monitoring including CCTVs, multiple authentication points, biometric scans etc. to ensure a complete secure environment.

Conclusion

Anaplan Infrastructure is quite resilient with primary & secondar backups to ensure that the business continuity doesn't get effected in event of any eventualities. In case of major disaster, the disaster recovery plan can be implemented by the support staff ensuring ongoing operations. It's also important to revaluate strategy in case if there are any short comings with the current system, so that the same can be dragonized & implement quickly.

Towards the end of the 2019, when tensions in the China-US trade war escalated and China was practically being held captive, then the whole world could not understand what a terrible time is awaiting for them due to Covid-19 outbreak. Gradually lockdown was announced in all the countries. When all countries were busy in building their infrastructure to fight against covid-19, this sudden lockdown put the whole supply chain system in a strange crisis. It seemed no one had signed up for this challenge but everyone has had to suddenly fall into competition. The sudden shutdown of production units and the increase in demand revealed weaknesses in the supply chains and production strategies. Shortages of essential items such as pharmaceuticals and medical supplies demonstrated their inefficiency  in meeting demand for these items. In this situation, companies had to develop a more resilient supply chain while keeping the main challenge in the form of market competition.

Management should first analyze its vulnerabilities before considering a series of steps. Although some steps may have been taken long before the pandemic actually struck. The visibility of demand, and the ability to make decisions at speed with the right players in the room are the utmost requirement.

Uncovered risks and address to mitigate

Identifying vulnerabilities: Risks may be hidden in many places, which may require a lot of digging. This is very much time-consuming and expensive process too. But it is much more important to be aware of a disarmament that can bring a business to a halt. Therefore, the mapping process should be aimed at categorizing groups as either low-risk, medium-risk, or high-risk. So, here in supply chain, high-risk can be considered as non-availability of an alternative sources to recover from the disruption. It also makes an impact that how long can you keep your manufacturing unit active without procuring raw materials? It's also a million-dollar question about the replenishment cycle which involves distribution channels, replenishment time, delivery cost and demand patterns.

In order to answer these questions, manufacturers should know whether their manufacturing capacity is flexible enough to reconfigure and redeploy as needed or whether it is highly customized and hard to replicate.

Diversifying Supply sources and manufacturing units: This is very important to address this point of diversifying supply sources and manufacturing units. Adding multiple locations instead of single factory, supplier or region always reduce the risk of halting the business. Management should also look into producing the materials within countries or adopt policy to expand atleast more than one country to avoid additional delivery times, international hazards due to trade war or any lockdown situation within that country due to pandemic. Thus, it will reduce the dependency on any particular region.

So, if we divide our focus according to time horizons then we have short term, mid-term and long term problems of supply chains to solve. This diversification of manufacturing units is a long term solution and alternative sources is a part of mid-term solution. During the immediate or short term risk mitigation process, organizations must intensify their focus on workforce planning since quarantine and travel restrictions mean a longer time period to ramp up to full capacity. Also, focus on tier-1 supplier risk and update inventory policy accordingly in order to focus on production scheduling agility.

Process Innovations and movement towards Automation: It has been seen that many industries have already started realizing their need to move from traditional forecasting to scenario based forecasting because the historical data of last few months sometimes are not helping them to get a good indication. They have started to unfreeze their organizational routines and revisit the design assumptions and other orthodox organizational processes. Focus has also been shifted to identify bottlenecks to build mitigation measures. More connected planning approach has been taken to achieve real time data in order to enable agile planning process. External indicators and predictive modelling are also being used for more accurate planning.

In the era of declining human interventions and more focus to social distancing, companies might invest more on robotic process which can reduce human interventions sharply in preparing products for shipping, with more accurately.