We’ll begin by defining data and looking at the places you store it. Next, we’ll look at how you can make this data available. We’ll finish with some examples of how automation and data can be combined for impressive results.
By the end of this article, you’ll know how to effectively use data in automation to benefit your business.
By the end of this article, you’ll know how to effectively use data in automation to benefit your business.
What is data?
The most basic definition is that data is a collection of information.
This information can be almost anything. Most businesses will capture customer data such as names, email addresses, or purchased products. Start thinking about it and you'll see the list goes on and on.
You’re continually generating huge amounts of new data through the day-to-day activities of your business. Your employees and IT systems will produce lots: marketing efforts, new customers, and more sales all add additional data you can use. In fact, IDG found that “the average company manages 162.9 Terabytes of data”. Not only do businesses manage lots of data, but on average they collect it from over 400 different data sources.
But how can you make use of it? You’re only limited by your imagination. Some common examples include creating bills, solving customer problems, and suggesting products your customers will enjoy.
This information can be almost anything. Most businesses will capture customer data such as names, email addresses, or purchased products. Start thinking about it and you'll see the list goes on and on.
You’re continually generating huge amounts of new data through the day-to-day activities of your business. Your employees and IT systems will produce lots: marketing efforts, new customers, and more sales all add additional data you can use. In fact, IDG found that “the average company manages 162.9 Terabytes of data”. Not only do businesses manage lots of data, but on average they collect it from over 400 different data sources.
But how can you make use of it? You’re only limited by your imagination. Some common examples include creating bills, solving customer problems, and suggesting products your customers will enjoy.
Data is everywhere
Right now you’re probably thinking about a few specific examples from your business. You likely have data stored in a variety of places. When prompted, our clients find it in a surprising selection of formats, systems, and locations.
You need to understand all the places your business keeps data if you want to make the best use of it. Let’s look at some common locations:
You need to understand all the places your business keeps data if you want to make the best use of it. Let’s look at some common locations:
- Physical documents – paper documents kept in filing cabinets, storage boxes, desks, or scanned and saved on a server.
- Spreadsheets – often manually managed and updated by a handful of people.
- On-premise – the data is stored on your own servers.
- In-cloud – everything from popular offerings like Salesforce, Google Drive and Dropbox to bespoke software used by your company.
How to access this data for automation?
Where the information is stored changes the method that automation uses to access it.
Cloud-based solutions
This is the easiest location to extract data from. The majority of these will have an Application Programming Interface (API) built in. The API makes it easy for an automation platform to interact with the information stored in the cloud. It uses a simple format that allows specific queries to be directly answered.
On-premise apps
These occasionally have APIs that can be accessed through a secure link – powered by a Virtual Private Network (VPN). However, many businesses are using legacy IT systems not designed with APIs. In these cases, the data can be accessed with other techniques (more on these shortly)
Databases
Often they can be accessed by a secure VPN link too. Although, automation platforms are often restricted to a read-only view. Data is a valuable company resource, so this is commonly done to protect data integrity.
Spreadsheets
These can be easily imported into a suitable automation platform. Once successfully loaded they can be quickly accessed and updated.
When importing data from spreadsheets, it’s important to make sure the automation platform can accept large amounts of data – millions of rows are not uncommon for large businesses. As human error is common in spreadsheets, the platform also needs to gracefully handle any incorrect information.
When importing data from spreadsheets, it’s important to make sure the automation platform can accept large amounts of data – millions of rows are not uncommon for large businesses. As human error is common in spreadsheets, the platform also needs to gracefully handle any incorrect information.
Physical documents
Artificial intelligence (AI) can be used to extract data from paper documents. AI reads the document and processes the relevant information into a format that’s easy for an automation platform to work with.
Want to learn a bit more about AI? Check out our article discussing AI in automation.
Want to learn a bit more about AI? Check out our article discussing AI in automation.
Other formats
If the above doesn’t work, you’re not out of luck. There are a range of tools you can use to make the data available. For on-premise apps that don’t make it easy to share data, screenshots can often be used and processed by AI to extract the relevant data.
For even trickier cases, Robotic Process Automation (RPA) can be used. This mimics human behaviour to get the desired result. An example might be extracting customer information from bespoke legacy software. RPA clicks through the user interface the same way a real person would. This is used as a last resort because it’s not as efficient as other methods.
The important takeaway is there are a lot of potential data sources. It’s not a case of adding one data source and you’re done. The full power of automation is only available if you use all of these sources.
For even trickier cases, Robotic Process Automation (RPA) can be used. This mimics human behaviour to get the desired result. An example might be extracting customer information from bespoke legacy software. RPA clicks through the user interface the same way a real person would. This is used as a last resort because it’s not as efficient as other methods.
The important takeaway is there are a lot of potential data sources. It’s not a case of adding one data source and you’re done. The full power of automation is only available if you use all of these sources.
Automation doesn’t only use data
Although having access to multiple data sources is important, it’s not only existing data that relates to automation. Automation platforms often generate large amounts of new data themselves – this often needs to be made available for use within the business.
Consider an automated journey for an insurance claim, reporting a public water leak, or customer feedback and sentiment analysis. It involves multiple steps and multiple systems. There’s a lot of data generated throughout the process: documents, dates, and progress on various KPIs.
Some of this data is used exclusively by the automation platform and can be stored in the most convenient format. Other times it’ll be used elsewhere and will be stored in the locations we already discussed.
As we said earlier, the value of automation platforms increases alongside the amount of data sources it can access.
Consider an automated journey for an insurance claim, reporting a public water leak, or customer feedback and sentiment analysis. It involves multiple steps and multiple systems. There’s a lot of data generated throughout the process: documents, dates, and progress on various KPIs.
Some of this data is used exclusively by the automation platform and can be stored in the most convenient format. Other times it’ll be used elsewhere and will be stored in the locations we already discussed.
As we said earlier, the value of automation platforms increases alongside the amount of data sources it can access.
Making use of your data
We’ll now work through two examples that show exactly how you can combine data and automation to increase efficiency, deliver improved customer service, and save money.
Automotive industry
Motor vehicle companies keep a record of who has purchased from them. We’ll assume they store it in a database.
Let’s use a historical fault to see the effect of this. The 2004 Ford Ranger had a recall issued for a faulty airbag – affecting 328,000 vehicles. To manually find the owner’s contact details and then prepare a communication would be a huge undertaking.
Instead, it’s possible to use an automation platform to complete the task. It quickly extracts the relevant information, finds the best contact method, and sends a recall notice to each affected individual. Much easier.
Let’s use a historical fault to see the effect of this. The 2004 Ford Ranger had a recall issued for a faulty airbag – affecting 328,000 vehicles. To manually find the owner’s contact details and then prepare a communication would be a huge undertaking.
Instead, it’s possible to use an automation platform to complete the task. It quickly extracts the relevant information, finds the best contact method, and sends a recall notice to each affected individual. Much easier.
Retail industry
Online retail captures a lot of customer data. If this data is accessible to automation, it can greatly enhance customer service.
Imagine a shopper sends an email about their order. The customer rep could look up the shopper’s history in a CRM (Customer Relationship Management software such as Salesforce). By having access to information about previous orders and communications the rep can offer a personalised response.
Doing this manually for every customer email is time-consuming. A better solution is to connect with an automation platform. AI can read the email, understand it, and decide how best to proceed.
If it’s an order update the platform can access the CRM and automatically reply. For complaints, the platform will forward the email and CRM data to the relevant team. This significantly reduces their workload.
Imagine a shopper sends an email about their order. The customer rep could look up the shopper’s history in a CRM (Customer Relationship Management software such as Salesforce). By having access to information about previous orders and communications the rep can offer a personalised response.
Doing this manually for every customer email is time-consuming. A better solution is to connect with an automation platform. AI can read the email, understand it, and decide how best to proceed.
If it’s an order update the platform can access the CRM and automatically reply. For complaints, the platform will forward the email and CRM data to the relevant team. This significantly reduces their workload.
Final thoughts
You now understand why data is such an important business asset. It allows you to do amazing things. We looked at several locations where your business is probably storing data. However, knowing it’s there isn’t enough.
Using data to save time and money requires working with an automation platform. That’s where we come in. We make it easy and affordable to get started.
Learn how your business can get started with automation.
Using data to save time and money requires working with an automation platform. That’s where we come in. We make it easy and affordable to get started.
Learn how your business can get started with automation.
