Top 10 Reasons Organisations are Spending Too Much on Data

 Data issues and inefficiencies are stealing capacity and money from your business. They are wasting your energy and robbing you of your precious time. Your data is valuable but trying to wring that value out of it feels like an increasingly costly exercise.

While it’s easy to quantify financial expenses associated with data management such as investment in storage, cloud services, compute capacity etc, the financial impact of everyday data management issues extends far beyond the balance sheet.

Inconsistencies and inefficiencies cause unnecessary data costs measured in lost time, missed opportunities or costly errors.

Here are 10 Reasons why organisations today spend far too much on their data: 

1. TECH DEBT: Organisations are incurring tech debt across different data ecosystems which results in an inconsistent approach. 
2. SECURITY AND ACCESS MANAGEMENT: Irregular application of security and access management protocols contributes to the risk of costly, critical failures. They can also come with incremental costs that build over time. 
3. DOWNSTREAM IMPACTS OF CHANGE: Change impacts are poorly understood and missed or mismanaged, and unexpected changes occur.
4. TEAM EMPOWERMENT: Teams are not empowered to proactively address issues, meaning issues and their impacts go on for longer than necessary.
5. TECH ALIGNMENT: Poor connection exists between business outcomes and tech team priorities.
6. SERVICE LEVEL AGREEMENTS: There is a lack of accountability and SLAs for when things go wrong, which means dealing with and rebounding from issues take longer than necessary.
7. STRATEGIC MISDIRECTION: This takes resourcing and capacity away from the data ecosystems driving the business, even though fixing data issues would go a long way to achieving strategic objectives. 
8. SILVER BULLET SOLUTIONS: Too many organisations focus on silver bullet solutions to fix all organisational data problems, rather than getting to the root of data issues.
9. PROJECT DELIVERY FOCUS: Funding models are typically more focused on project delivery instead of investment in continuous improvement of daily operations (which would actually reduce data costs). 
10. WRONG SKILLS, WRONG JOBS: The wrong skills are focused on the wrong jobs eg. data analysts are doing engineering, data engineers are doing analysis, and data scientists are being structurally under leveraged. 

BizCubed finds the untapped value in data ecosystems. We make our clients’ data operations work better so they can make better decisions, at higher velocity, with increased capacity and reduced data costs.

Get in touch today to find out how we can help you reduce data costs by 35%.