Friday, May 12, 2017

The power of cloud integration for business IT systems

Before cloud computing existed, data used to reside in individual stores, on different computers, and sometimes within very different ecosystems. Users would have a record for a client in accounting, another in the order entry system, and another in a database of leads. Even emails were hosted on individual machines with only a local access point. To make matters even more complicated, none of these systems would automatically synchronize or intercommunicate; it was a virtual mess!

Thankfully many business systems today operate in the cloud allowing users to, for example, pull emails from a customer relationship management (CRM) system (like ProsperWorks) and with a single click, dial a contact via RingCentral which logs the interaction for productivity reporting and follow ups. Since data now has the ability to flow freely between software, it doesn't make sense for it to live in individual stores any longer. Think of software integration like bridges in a city, allowing traffic to flow freely from one place to another.
Our team at Interlock IT advocates a simplified workflow which eases integration between all of your business systems – phone, email, and software. For instance, allowing calls to be logged in your CRM both in and out of the office, and emails automatically synced to client records in your CRM and accounting software. Our skilled team can perform custom integrations with many other solutions that we may not necessarily resell. Our use of Google App Engine instead of hosted servers and the pervasiveness of modern Open API's with cloud software means integrations are low cost, secure, reliable, and near realtime. Gone are the error prone days of file exports to hard drives and batch import processes that frequently failed due to data structure changes. Modern API's flow through the software business logic layer to prevent issues like posting unbalanced accounting entries. Database or file level integration methods of the past often required duplication of this critical error checking logic and would fall behind as the core software business logic changed.

To illustrate an example of cloud integration, we use Hubdoc to automatically push our monthly phone bill to Xero which codes it to the correct expense account. It attaches the pdf image of the invoice and also saves a copy to our Google Drive where we can take advantage of the world's best search engine to instantly find it again. Enabling auto-pay with our provider allows us to simply let Xero's automatic downloading of bank transactions find the matching payment and mark it as paid. There is zero traditional human data entry required, which in return allows us to use that time towards more important tasks like following up with our customers.

Unfortunately many businesses still use obsolete (non-cloud) IT software that is inherently inefficient and expensive. Even custom integrations of legacy software is generally designed hastily to fill a need but isn't a permanent fix. This usually involves data that is only accessible from one computer and often by only one user at a time, not remotely and collaboratively. In the era of cloud computing, these sort of 'patch-ups' aren't necessary. Cloud computing has opened the doors for powerful software integrations that yield far superior results when it comes to productivity and efficiency. If there's a cloud application that your business needs to integrate, our team is ready to design and deploy it. Contact us today to find out more about how you can unify your workflow and improve your business IT system!

Friday, May 5, 2017

Machine learning in G Suite - How it increases productivity

Humans have been evolving rapidly over the last few centuries; from the agricultural age, to the industrial age, to now the information age. As we evolve so do our tools and the ways we interact with them. Take G Suite for example. Just over the last few years, G Suite has evolved from more than just an email and contacts solution, it now has the capacity to anticipate your business needs and facilitate collaboration and productivity at an unprecedented level.
Formatting documents, email management, and creating expense reports. These are just a few of the common time-consuming tasks that negatively affect productivity. Time spent working on tasks that do not directly relate to a creative output is costly and is referred to as 'overhead'. Unfortunately, huge overhead is common in most businesses and hinders valuable potential. According to a study by Google in 2015, the average worker spent roughly 5 percent of their time actually coming up with the next big idea. The remaining 95 percent of the time was dissolved in the form of formatting, tracking, analysis or other mundane tasks. With all these tools and efficiencies, one would think the percentages would be reversed. To make this possible, Google introduced what's known as machine learning.
What is machine learning? Essentially, machine learning algorithms observe input examples and make output predictions based on data. In G Suite, machine learning makes your workday more efficient by handling menial tasks, like scheduling meetings, or by predicting information you might need and surfacing it for you, like suggesting Docs for example.

Ever notice how you received less and less spam over the years with Gmail? One of the first applications to use machine learning was Gmail. Historically, Gmail used a rule-based system, meaning Google's anti-spam team would create new rules to match individual spam patterns. With over a decade worth of data and using this process, Gmail improved it's spam detection accuracy to 99%! It's now one of the most secure and spam free email applications in the world. To take it a step further, in 2014 Google augmented the rule-based system to generate rules using machine learning algorithms instead. This took spam detection to another level which now allows Gmail to continually regenerate the “spam filter”, so systems learn to predict which emails are most likely junk. Naturally, machine learning finds new patterns and adapts more quickly than previous manual systems - it’s a great reason for why there are more than one billion monthly active Gmail users today!

The goal of G Suite is to help teams accomplish more with an intelligent range of applications, no matter where they are in the world. Smart Reply for example, uses machine learning to generate three natural language responses to an email. If you find yourself away from the office or time-restricted and are in need of a quick way to clear your inbox,  you can let Smart Reply do it for you. Click here to learn more about Smart Reply.

Explore in Docs, Slides and Sheets uses machine learning to eliminate time spent on things like tracking down documents or information on the web, reformatting presentations or performing calculations within spreadsheets. The whole point of these tools is to help the user accomplish more with less.

Another great example of machine learning is Quick Access in Drive which predicts and suggests files you might need within Drive. Quick Access intelligently predicts files based on who you share files with frequently, when relevant meetings occur within your Calendar, or if you have patterns of using files at specific times of the day. Using predictions based on recent Drive activity greatly increases a users productivity and efficiency for day to day work.

To learn more about how machine intelligence can make work easier, check out this video from Google Cloud Next with Ryan Tabone, director of product management at Google, where he explains more about “overhead.” G Suite was made to make businesses run faster, smoother, and more efficiently. If those are things you're looking to adopt for your organization, give us a shout! We'd love to hear from you and discuss the possibilities for you business IT solutions.