Simplify Data Management by Dealing with Process Issues

  Data process issues and inefficiencies are stealing capacity and money from your business. Data engineering can help.

Wherever there is a headache of a repeatable, time-consuming task you’re likely to find employees using some kind of workaround to try and simplify or speed up the task. Within a large organisation, this can happen across multiple data processes in multiple teams. As long as things keep ticking along, managers, IT and leadership haven’t prioritised doing anything about it. It may feel too time-consuming and costly to find and establish a better way to do things.

It’s easier to let people do whatever it takes to get it done, right?
Wrong.

The Obvious and Hidden Costs of Workarounds

A company’s data process issues are compounded by the number of people using workarounds and the sheer number of times the process is run in a day, week, and year. That act of choosing or allowing a workaround or process hack comes at a cost, and that cost continues to accumulate.

Let’s consider a team of five people performing the same manual task many times a day, every day. Different people on the same team come up with their own workaround, so the process step is actually being completed in a number of different ways. This might be fine for a while if you’re talking about a BAU situation, but it will cause issues when that team is called upon to explain its processes, such as when onboarding a new team member, trying to unravel a mistake to find out how it happened or complying with regulatory reporting requirements.

At some point, a process hack will stop working or come to light in some other way and the process step itself will need to be reworked so that it’s more efficient, effective, or even automated. The longer the workaround is used the more complicated and costly it becomes to change the process.

What if the process hack causes a minor calculation error in a resulting report each time it is run? The longer that workaround is used, the more errors that are accumulated. This can hamper decision-making within the business or decision-making that impacts your customers.

Besides quantifiable costs resulting from data process failures (when the workaround stops working) such as overtime hours, service fees, fines, lost sales or the cost of going through an RFP process to find and then implement a new technology solution, there are hidden costs that result from inefficient data workflows include:

• Missed opportunities because there simply wasn’t enough bandwidth or mindshare to pursue them in addition to keeping the day-to-day operation running
• The burden of time-consuming manual tasks that increase risk and lower productivity
• Delayed growth because the team doesn’t have time to focus on innovation and diversification
• Employee dissatisfaction due to repetitive manual tasks and dealing with data processes that just don’t work, causing productivity and retention issues

The Transformative Power of Data Engineering

Data issues have a multifaceted impact on business operations and collectively, represent a formidable hindrance to overall success.

On the flip side, recognising this creates an opportunity. Organisations that fix their data management issues set themselves up to claw back capacity and reduce costs related to data management.

Establishing consistency in methodology and operations anchors an organisation’s data ecosystem, regardless of personnel, process and technology change.

Data engineering addresses the process of data management. Data Engineering simplifies data management. Data Engineers build and manage the means by which data is collected, translated, validated and the way it flows through data pipelines to support business processes, operations, applications and more.

At BizCubed, this is what we do. Every day.

We end data pain by atomising data processes down to their component parts. We then build them back up into loosely coupled, scalable and repeatable patterns
We end data pain through agility. We utilise feedback loops to drive down data cycle times to encourage iterative development and responsiveness to the market
We end data pain by identifying and relieving bottlenecks to mitigate single points of failure
We end data pain by driving down costs and improving data quality

Contact us now to end your data pain and help your business Make Better Decisions Each Day