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8 Steps to Building Data-Driven Operations

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8 Steps to Building Data-Driven Operations

Learn how data analytics can be taken a step further than it usually is and be integrated into your day-to-day business operations to help you run your business smoothly.

· Big Data Zone ·
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Typically, businesses use data to make informed decisions, to investigate issues, and for exploratory purposes such as finding new growth opportunities. However, did you know that data can be taken a step further and be integrated into your day-to-day business operations to help you run your business smoothly?

Instead of helping people make better decisions, it’s about using data-driven systems and algorithms to improve processes. For example, you can use data to automatically identify manufacturing defects, optimize delivery routes, target the right customer, or even detect fraud.

Here’s an eight-step process to use data to optimize your business operations!

1. Source Additional Data

Most of the time, companies look at their existing data sources such as sales records and customer information to get business insights. Although it’s a great starting point, it’s important to understand that there are many more data sources out there that can provide useful information.

There are two ways to source additional data: internal and external. Internal data is all the data about your business captured by your own business systems and processes. They include information about a company’s performance such as sales data, employee information, and customer records, and all the data captured by your day-to-day business activities. External data sources include all the data available outside your company that may be relevant to your business. They may be free sources available publicly or paid ones provided by third-party vendors.

2. Analyze the Costs and Benefits

Integrating new data sources into your business systems will require investing in tools that allow you to collect, store, and analyze data to improve operational performance. Also, consider the potential costs of not integrating these data sources into your business and being left behind.

3. Own Your Data

If you’re going to use data to run your daily business operations, then it’s essential that you own it. Ensure that data gathering and storage is a core part of your business processes and systems. Wherever possible, at least, own the data that is critical for your business operations to run smoothly. Otherwise, they’ll be adversely affected when you’re unable to access data or face data issues — which brings me to the next point.

4. Manage the Data

If you’re sourcing operational data that spans various systems and processes, then you’re going to end up with big data sets. So, it’s important to think about how you’re going to store and manage your data before you begin using it. If you think of your data as an operational asset, then it’s really important to protect it from storage and security problems. Otherwise, issues like data corruption can cost a lot of money and tarnish your company’s brand. If you’re a small business, then computer hard disks might be the best way to go since they provide an inexpensive solution for high storage requirements. However, if you’re a large enterprise, then you might want to look into alternative storage solutions, such as distributed storage and cloud storage, that allow you to store large amounts of data at a low cost without investing in dedicated data warehouses and systems.

5. Secure Your Data

These days, data security is a big issue for most companies. Data breaches can cost a lot of money and can cause a loss of trust in your business. As it requires specialized skills to build a secure system, it’s advisable to solicit expert help for this purpose. Protect your data through encryption (at rest and in transit), train your staff so they don’t unintentionally or carelessly give away crucial information, and build security systems that detect data breaches and immediately alert the concerned authorities.

6. Set Up Additional Infrastructure and Technology

It’s not enough to source new data sources. You’ll also need to have the necessary technology and systems in place to leverage incoming data. The first step is to examine your existing infrastructure. Identify which parts of your technology need to updated, modified, or completely built from scratch to handle the new data. It's advisable to adopt a three-pronged approach to beef up your infrastructure:

  1. Create tools and processes to generate internal data as well as use external data.

  2. Build systems to store and secure that data.

  3. Set up algorithms are available to automatically analyze this data, create necessary deliverables (reports and dashboards). and distribute them to the right people in your organization at the right time. There are various business intelligence tools to do this.

7. Create a Pilot Project

Start with a pilot project to test your operations on a small group of employees and for a few of your systems. This will help you iron out any kinks before rolling it out to a larger audience. Aim to roll out your operations in a phased manner — a few systems at a time — instead of going live all at once. Remember that it’s a long and iterative process to improve your business, so spend the time to get each stage right.

8. Monitor Your Operations

Improving operations is an ongoing process that requires constant monitoring — just as you regularly monitor your products, marketing channels, and customer service. Analyze and review the performance, maybe once every six months, to see how data is transforming your operations and whether it’s working as expected. If you don’t see the desired improvements, try refining your algorithms or using additional data.

Wrapping It Up

The past few years have introduced several exciting technologies that allow you to monitor and analyze data from virtually any system. As such, businesses are constantly finding new ways to use data to improve their day-to-day operations and gain competitive advantage.

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Topics:
big data ,data analytics ,data management ,data-driven

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