Companies are gathering data at an astonishing rate but capturing value from that data is a perpetual challenge. Poor quality data is often cited as one of the biggest obstacles to using data – “garbage in, garbage out” as the adage goes. If you’re operating a data-driven business, how do you get to a position where you’re truly predictive?
Lost paperwork, missing data, and delays in data transmission, can all delay insights. Oftentimes, the data must be verified, cleaned, and re-keyed – a process that can take hours, if not days. The problem is further compounded by the fact that data has a half-life of approximately 30 minutes. After that time, its relevance and usefulness are questionable, resulting in muddy insights.
What Real-Time Data Means, and Why it’s Critical
The term “data” can sound vague or intimidating, but you’re likely already collecting tons of important data for your business that you can use to make better decisions — invoices, work/service orders, inspections, employee time on a project, and more. To achieve actionable insights from that data it’s imperative that the information is processed the very moment it enters your data analytics engine. Of course, it rarely happens that way. A huge percentage of any data project is focused solely on cleaning data manually, eating up time and money and introducing the risk of human error, which can further contaminate data and lead to bad predictions.
In the data analytics world, accuracy is essential, and speed is critical. This is where “real-time” analytics comes into play. Instead of second-guessing dirty, outdated data, real-time analytics gives insights on what is going on in the business, right now.
Say you’re the manufacturer of a consumer product and have a team of sales professionals who are responsible for reporting and auditing in-store conditions to ensure brand standards are upheld and inventory is displayed correctly. This process would have traditionally been done with paper forms, limiting access to real-time data back at the head office. Mobile applications in the hands of sales teams, however, can transform how data is collected and reported across the organization providing real-time actionable intelligence.
To achieve such insights, businesses simply can’t afford to rely on data that is questionable or delayed in transmission. Their analytics engines, whether it’s Microsoft, Oracle, Google Analytics, etc., depend on real-time data that is already cleansed, normalized, collated, and error-free.
Closing the Gap Between Data Collection and Data Analysis
To tap into the power of data, companies are increasingly seeking the ability to collect and connect to data in less time. We see companies throwing extra staff at the problem, only exasperating an already manual process. More data entry is not the answer. Mobile-based digital information capture solutions are making it easier for organizations to overcome the time and effort it takes to capture, clean, correlate, and input data into analytics engines. Instead of hiring new employees or retraining staff, you can easily put data gathered in the field on digital mobile applications and have it automatically uploaded to connected cloud-based SaaS systems.
Even if you have data from multiple sources and in multiple formats (photos, signatures, etc.), digital information capture solutions can help pull it all together helping you glean critical insights into your business. Going one step further, API integrations allow for the creation of a digital “handshake” between these tools and almost any other open-ended software that allows for web services. Whether you are using Microsoft Excel or a SQL database or have made the move to more robust applications like QuickBooks, Freshbooks, or Salesforce, cloud-based services, like Zapier, make such integrations even easier by automating the movement of data collected into these third-party systems.
This is the ideal way to get real-time data collected via mobile applications and form data in the field pushed into your accounting, ERP, and other software systems. Using the power of automation, it removes the manual work behind taking CSV data and uploading it daily into those different systems and reduces the time it takes to develop a full-scale web services integration with an API.
IT-constrained organizations will be pleased to know that connecting systems via APIs isn’t the only path to bridging data sources to their analytic systems. So-called “quick connectors” provide the capability for users to instantly connect project or customer information collected without having to set up a backend API integration.
Good Data in Fuels Good Decisions Out
Most businesses – 81% – agree that data should be at the heart of decision-making. However, only 3% describe their strategy as “mature.” Mobile applications are fast-becoming a critical tool in helping organizations move up the data maturity ladder. Moving beyond simple data collection, these tools have the potential to become a matter of course for field service businesses. Leveraging cloud-powered real-time data connections and integrations, business processes are streamlined (freeing up employees and resources), and teams are empowered to make better decisions about how to increase efficiency, save time and money, and predict future performance and sales.