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Best Practices for an Optimized Cloud

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Did you know that as per Industry reports, 30-35% of the Cloud spend goes wasted (Source: TechBeacon).

Switching to a Pay-as-you-go model is the right beginning. You get rid of capex and can address your growth uncertainty to an extent. But it’s quite likely that you’re paying more by not having the right sizing on the cloud.

Managing your Cloud expenditure is easier said than done. In this blog, we’ll take a deeper insight into challenges faced in Managing Cloud spendings and how one can overcome them.

1. Tap on Utilization

As you evolve in your Cloud journey, it gets more and more difficult to keep a tap of the numerous Cloud services you’re using. You do get to know your Billing at the end of the month, but do you monitor how much utilization has actually happened at the server level.

2. Shadow IT

In organizations, apart from IT, there are a lot of other departments that use Cloud services which go largely unchecked. The most common concern across organizations is that they use the services for a while that they have provisioned and then leave them idle only adding up to the charges without utilizing them.

3. Rightsizing & Automation

The biggest advantage of using Cloud is to Semi-Dynamic and Dynamic applications since they are unpredictable in nature and can be scaled up and down depending on usage.

In such a scenario, you cannot follow a set it and forget it approach.

How to overcome such challenges?

Proactively keeping a tab on utilization is one the keys to optimizing your Cloud. But what all do you need to monitor?

Well, here’s a checklist to begin with –

  • Utilization of unused and underutilized resources
  • The timing of resources utilized, especially development resources to ensure they’re switched off while not in use
  • Resource utilization by departments, especially idle resources
  • Pricing structure of the Cloud Solution Provider

While you monitor all these parameters to begin with, necessary and corrective action of terminating resources needs to be taken timely to ensure you’re actually paying for only resources you’re using.

These activities will also help Forecast your usage and plan better.

Think you need to optimize your Cloud? Get in touch with us

at cloud.sales@teamcomputers.com or give us a quick call at +91-8860716613

Build a culture of Analytics

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Without the required organizational change, your analytics project will not fly

Companies are looking to leverage the benefits derived from analytics tools to enhance decisions and performance at all levels of their organisation. However, merely investing in analytics is not sufficient to obtain the desired results.

Merely layering technology on top of existing operations is not sufficient in itself. It can be hard to persuade end users that the solution deployed adds value to their work, rather than adding complexity. This added value may range from something as simple as saving hours of routine work to the generation of strategically valuable insights.

Users need to start demanding data to make decisions rather than relying on their gut feeling or untested assumptions. They should be both excited and aware of the opportunity to save hours of time wasted on slow methods so that they can do more productive tasks. This can happen if they see how the new tools make their day-to-day work more efficient and effective.

“A common issue is that end-users continue to
use the old methods despite the availability of
productivity enhancing tools at their disposal.”

Adoption issues are not uncommon

Organisations build large data warehouses, hire right talent, and deploy advanced analytics only to find that decisions are still made with the help of inefficient (and sometimes even ineffective) old methods. No matter how advanced the technology underlying the analytics program, adoption and change management is necessary”

Common problems with adoption According to a 2017 Forbes Insights-EY report on Analytics:

38%

Lack of support from senior leaders

46%

Lack of collaboration between IT and Users

38%

Inability to change organizational culture

Problem

Lack of support from top management

Insufficient engagement of business users

Inability to Adopt a Data Driven Culture

Questions to be asked

Are top leaders encouraging the use of BI tools?

Is there a mechanism to drive change towards the new system?

Was there top management and business user buy-in before and during the adoption of the solution?

Are business users aware of the benefits of the new tools?

Do they have trust in the information generated from these tools?

Are users receiving the desired information from the tools?

Has the program facilitated a change in the manner of decision-making?

How often are the users leveraging the BI tools to increase the efficiency and effectiveness of their work?

Are users comfortable with accessing and navigating through the solution provided to them?”

Things to do

Appoint a change sponsor who owns the transformation process

Regular communication with management on the progress of usage and RoI

Train managers so that they can promote new behaviours in their teams

Engage all users to build trust and acceptance

Enable the IT team to handle queries of business users

Identify the top users and what they are doing as against the low performers

Recognise the users who are doing their best in driving the change

Establish incentives to drive new behaviour

Team Computer drives adoption as an essential component of its analytics implementation. We work closely with our clients to help them realize high returns from their analytics investments. Get in touch by writing to us at analytics@teamcomputers.com to know more.

4 Reasons you need Enterprise Mobility right now!

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So what is Enterprise Mobility? Enterprise mobility, to put it simply, is an approach to work in which employees can do their jobs from anywhere using a variety of devices and applications.

The term commonly refers to the use of mobile devices, such as smartphones and tablets, for business purposes. But it also covers the mobility of corporate data and of workers themselves. As an example of enterprise mobility, an employee may upload a presentation from their desktop PC to a cloud storage service, and then access it from a personal Apple iPad to show at a client site. It’s that simple.
Now, let’s look at the four major reasons that might help you understand that important can enterprise mobility to be for you;

1. Increasing number of mobile workers

According to a survey, by 2020, 60% of your workforce will be mobile for work.

If you’re surprised at this number, reflect on the following facts:

  • From 2010 to 2017, internet usage on desktop and laptop devices stayed fairly flat while mobile usage increased by 700 percent.
  • Smartphone ownership has grown from about 30 percent in 2011 to nearly 85 percent in 2017.
  • The majority of millennial smartphone users, 87 percent, say their phone never leaves their side, day or night.
  • Thirty-seven percent of workers telecommute regularly.
  • More than half, we’re talking 68 percent, of business emails, are now opened on smartphones.

Imagine the productivity rise if they could perform all their routine tasks with the same comfort as in office with full access to desktops and applications. According to a recent survey, 40% of businesses are working on improving their mobility strategy for individual productivity gains.

The millennial workforce demands flexibility to work remotely. Organizations that have understood this have policies such as work from home or work anytime anywhere and are building processes and systems to support this.

2. Real-time Management and Analysis

Enterprise mobility enables executives to access current and historical data literally anytime and capture data on the go to make better decisions when required. Transparent enterprise management and reporting platform can further reduce dependency on the IT teams for problem-solving.

At Team Computers. Employees now use an in-house mobile app as against biometric cards to punch in. This app further serves as a one-stop shop to apply for leave, report incidents & almost anything on the go from their mobile app. Pretty cool. right?

3. Provide an improved customer experience

71% of the companies moving towards business mobility are developing and deploying customer-facing apps focused on improving the customer experience.

What is the benefit these companies expect to achieve? The survey revealed that customers who execute business mobility plans have an average 150% return on investments (ROI) – the largest being the ability to bring new revenue streams online more quickly.

An automotive giant, in partnership with Team Computers, is using Apple iPads at their dealerships. The sales person at their showrooms can easily access and share vehicle details like specifications, colors, prices, etc. instead of the traditional brochures & leaflets.

4.Process Efficiency and Reduced Costs

Furthermore, the usage of interactive maps or the recording/logging of location-specific data can help improve processes, reduce costs and deliver value faster and better to customers. Uber has created one of the best use cases here. Isn’t it?

With an enterprise mobility management solution in place to provide access to corporate systems through mobility devices, overall adoption rate and productivity from employees can be achieved.

Think you need enterprise mobility? Get in touch with us

at social@teamcomputers.com or give us a quick call at +91-9350593984

Converting Visitors Into Customers

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The term ‘predictive analytics’ has been thrown around for a while now but the adoption has been relatively low.
Every E-Commerce Retailer has a few common questions when it comes to their business: What is the maximum price a customer will pay for a product/service? How to proactively solve customer queries before they become issues? How to optimize costs?
Companies which make use of predictive analytics are able to to get answers to such questions. So, how can this analytics really help?

1. Price Optimization

The key agenda of optimizing price is to maximize profits. Usually, retailers set prices manually by using different traditional methods which take a lot of time and have a high probability of errors. By using predictive analytics, retailers can optimize prices automatically by looking at previous trends, product performance, consumer behaviors, historic price patterns etc.

2. Customized Product Recommendations

Pitching the right product to the right customer has always been a priority for E-Commerce retailers. Predictive Analytics tools help retailers to optimize these personalized recommendations for their prospects based on purchase history patterns, browsing history patterns, product placement on the website etc. These predictive tools help retailers to maximize the probability of conversion of a sale.

3. Customer Lifetime Value Analysis

The Customer Lifetime Value of any customer is the total revenue that the company can expect from a customer over his entire lifetime. It can help the company take important decisions such as the amount you should spend to acquire a customer, which customers to focus on, and how much should the company spend on servicing and retaining customers.

4. RFM Analysis

Recency Frequency Monetary) uses only past purchase behavior into segments customers basis the comparative recency, frequency and monetary value from the customer pool. The segments can range from Loyal customers to those most likely to churn.

A comparison of Customer Lifetime Value Analysis versus the RFM segments that the customer falls into can provide a good insight into the customers you want to focus on ASAP! A better understanding of your customer buying patterns, purchase history, likes, dislikes, browsing history can really help an E-Commerce retailer in having an edge over competitors which in turn will generate a better market share.

Large E-commerce sites such as Flipkart, Amazon and Book My Show are already ahead of the game It’s time for others to catch up if they want to remain a part of the game.

5 Ways To Bank Happy Customers

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Now that you’ve got your Management Information System with Business Intelligence, have you been wondering “What next?” With a lot of buzz around technology like Big Data, Predictive Analytics, Business Intelligence, Data Science etc. that are floating in the market, it has become increasingly difficult to figure out how to apply these to your business.As an avid user of the banking system, here are 6 things I wish banks would and would not do; also, a few cents on how it can be addressed:

  • Stop the Standardized, non-personalized, non-relevant communication
    I’m actually done receiving multiple calls about how I am eligible for a credit card or that I should pick up a home loan. While these spark my interest once in a while, I am as quickly put off by the fact that the person calling me follows up with questions around my income or what kind of account I hold with the bank when I’ve already provided this information before!What you can do:
    This can be resolved easily by getting a Single View of the Customer using a Master Data Management solution to:Maintain a Golden record per customer that will provide a 360* degree of each customer and his/her relationship with the bank. This data can be further enriched by using social media data. Deliver personalized messaging in marketing campaigns: Segmentation of your customers and an analysis of their behaviour in terms of what are the products most suited to their profile and what they are likely to buy next can help you communicate only the most relevant messages to the customer.
  • Protect my identity!
    Identity theft scares me. I am afraid that, at any point, my money from my bank account might be stolen, or that my credit card may be swiped. While a lot of banks take the necessary actions to reimburse the lost amount to the customers, the stress, tension and inconvenience it causes knows no bounds.What you can do:
    Predictive analytics is at the cutting edge of fraud detection. Analyze your customer’s past transactions, what, where and when they have been using their credit and debit cards and internet banking and pick out the anomalous activity to save your customers some precious time and effort.
  • Help me when I need it!
    More often than not, when I call a bank, post going through an unpleasant IVR process, I reach out to a support executive who does not have the answer to my questions. He/She then promises to get back to me via email, or redirects me to another customer service agent to whom I have to explain the problem to all over again. Sigh!What you can do:Two things.One, get a chatbot in place for customers who prefer self service. A chatbot, powered by AI and with real time access to information, will be indistinguishable from humans. Or more efficient. In a recent survey by PwC, about 27% of customers were unsure whether their last service interaction was with a bot or human.Two, monitor the types of queries each of your call centre agents are most effective in resolving and use analytics on pass on only those queries to the agent. No more forwarded calls! Tada!
  • I don’t get reminders on my Credit Card payments!
    There are months when I am late to pay my credit card bills and run into trouble later. I tend to forget about it and I end up spending more interest on my debt. I get very few reminders for paying up my credit card debt.What you can do:
    Machine Learning offers clear benefits in this area. Banks can integrate various modules of Machine Learning in the collections process and send automatic reminders to their customers. The frequency of the reminders can be set according to the history of payments behaviour.
  • I want to apply for a home loan and I don’t know my credit score!
    I have recently decided that I want to buy a house in one of the metro cities. I am in mid level management position at my firm and currently have a car loan and some credit card debt. I called up the my bank to inquire about my credit score so that I know how much loan can I apply for and at what interest rate. My call just kept getting transferred without anybody giving me a concrete answer.What you can do:
    Credit scores are based on behavioral data, whether the consumer pays on time, amount owed and so forth, and the factors used are public. Some scores may use other factors, such as where you went to school, previous year’s earnings and whether you have dropped a phone number. Predictive Analytics can help with drawing insights into this behavioral data and give a valid credit score.

So, what about you? What are some of the biggest pain points you have as a customer? Or the biggest pain points you’ve identified as a bank? Do let us know in the comments section below.

Also, stay tuned or reach out to Team Computers to know more on the nitty gritties of the solutions mentioned in this article.

Team Cricket Premier League

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Team Computers organized In-House cricket tournament “TPL North’18” on 10th March’18 at Sports Fiesta Club, Chattarpur. 4 knockout matches were played for which the winners are – Kockpit, INS, BA, IMS.
Semis and Finals are planned for 17th March’18. We are eagerly waiting to know the winner of TPL North’18