4 Ways to Achieve Trustworthy Data

One of the more common concerns I hear businesses raise is “I don’t trust the data”. We live in a data-driven world and having the ability to leverage business data and turn that data into valuable insights is critical. Not trusting your own business data is a scary thought but it is also a reality for many businesses today. In this post, I will outline actionable strategies that you can put in place to achieve more trustworthy data.

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1. Remove Software Disparity

Businesses will often have multiple software systems in place to manage various different processes. This may include, ERP systems, CRM systems, Spreadsheets and bespoke software solutions. Typically the more established the business, the more systems in production. In some cases, multiple systems may be unavoidable, but it is important to understand what each system is doing and avoid replication or duplication of functionality. Running multiple systems leads to ‘confusing’ data as business users may not be aware of which data source is the most accurate. Lack of integration between disparate systems may mean that multiple data sources are required to get a complete picture of business operations. Solution: Consolidating data into a data warehouse and replacing legacy systems is a great way to reduce disparate solutions.

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2 Validate System Integrity

Regardless of how centralised and modernised your systems may be if they are outputting invalid data, reporting and analysis will be difficult, ultimately resulting in data that is not trusted. There can be several reasons for poor data output, one is simply that the software in use is faulty. Custom developed solutions are often more prone to software ‘bugs’ because they often do not go through the same quality assurance process as commercially available software. Incorrectly configured software can also produce invalid data output. Solution: It is a good idea to ensure you have skilled consultants review you business systems from time to time to ensure they are functioning correctly. Checking reported data against individual transactional data is a great way to validate your system's integrity. If there is uncertainty in your data, taking the time to validate granular transactional output can be time well spent.

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3. Improve User Training & Understanding

A sure fire way to corrupt quality business data is by having users interact with it. Without proper training or clear guidelines, users will often take shortcuts or implement their own practises when it comes to data entry into business systems. Simple things such as not completing all fields on a form, or phone numbers entered into a name field can all add up and have a dramatic effect on the quality of your data set. Solution: Regular user training and clear documentation is a must for any business where multiple users are regularly entering system data. It is also worth taking the time to ensure the systems are collecting data that is relevant and useful, the software needs to be a useful tool that accelerates business process, not something that simply increases a user's workload.

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4. Implement Quality Business Intelligence Tools

If the steps above have been put in place and you are confident your business data sources are validated and accurate you will need to ensure you have the right tools to interrogate that data and produce insights that are valuable. As with most things in life, not all business intelligence systems are created equal. Excel is probably the most widely adopted and favored reporting platform in the world, but in many instances in can be slow and cumbersome, especially when complex reporting is required. When selecting a business intelligence tool you will need to consider the data sources you are connecting to. What format are they? Where is the data located? Are my systems Cloud-based? This will help narrow the list of possible options. From there you also need to consider what the business intelligence goal of your organisation is. If visualisation and self-service analytics is required, then a tool such as Tableau may be a good fit. Alternatively if you need to warehouse or consolidate your data sources, then systems such as Birst or Microsoft SQL Server may be best suited. Solution: Ultimately, before making any final decision on business intelligence software, speak to an expert.

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If you feel that your business would benefit from a discussion with Sam please contact him by posting a project on the Expert360 platform.