Photo by Nataliya Vaitkevich:
Data-driven businesses are becoming more popular. The idea is to use as much data as possible to make better decisions for all stakeholders (including staff).
But, of course, data isn’t perfect. Statistics can lie, and even collection methods can lead to issues that throw businesses off-course.
The purpose of this post is to explain why so many data-driven businesses get into trouble and what they can do about it.
Here’s everything you need to know:
Over-Reliance On Data Above Intuition
We currently live in a world where the scientific mind rules everything. The entire culture revolves around the idea of evidence and logic.
However, metrics don’t tell the full story. A job candidate could look fantastic on paper, but they might have negative qualities that data can’t capture, which make them unsuitable for your team. If you only made data-based decisions, you’d hire them immediately, but that might not be best for your firm.
The trick here is to allow some intuition into your management process when it’s helpful for you. You don’t want to use it all the time to avoid bias, but you should employ it when it makes sense to do so.
Poor Data Quality
Another reason data-driven companies get into trouble is poor data quality. The business costs of inaccurate data can be significant.
For example, data that’s wrong can lead to poor analysis and misjudgments. A brand can think it is making marketing and staffing decisions based on the best available data, but that can also be wrong.
Poor data quality is an issue when the data is incomplete. Lacking data may lead to inaccurate interpolation that doesn’t reflect the real world.
The solution to this problem is to check the data against the real world. If it matches, it’s a strong sign that it’s safe.
Chasing Vanity Metrics
Data-driven businesses also get into trouble when they chase vanity metrics. Companies are often more concerned about things like page views or comments than they are about their core KPIs relating to income.
You can avoid falling into this trap by using software that lets you keep tabs on the metrics that mean the most to you. These can help you avoid focusing too much on the ones that don’t really make much of a difference to your overall success.
If you want to use vanity metrics for marketing purposes, that’s okay. Just remember that it’s the core financial metrics that matter the most.
Siloed Data
Another issue for data-driven businesses is data silos. Many firms find it challenging to harmonise their data across their organisations to make it usable. Siloed data tends to sit on departmental hard drives without ever getting to the stage where it can be used more globally.
These data silos are problematic for obvious reasons. First, some departments may have information that is pertinent to others, but they can never use or access it, leading to wasted time and poor decisions. And second, nobody has a complete overview of the company based on the available data. Staff have to guess or constantly ask internally for access, which is slow.
You can fix this issue by hiring an external company to centralise data for you. Usually, they’ll do this by setting up a cloud database and a rental.
Analysing Too Much
Analysing too much is another data-related issue. Companies become obsessed with figures on the screen and can’t move forward before they’ve crunched the numbers to their satisfaction.
These data issues can be okay for some companies, but severe for others. Analysts can’t always crunch the numbers fast enough, and management can tie itself in knots when data seems to conflict on the course of action that needs to be taken. This inaction can then lead to delays and other issues that make the company less effective overall.
Solutions to “analysis paralysis” are complex and difficult to obtain. However, they usually involve making the data more parsimonious. If you can simplify it, it makes unclear conclusions less likely.
You can also run data through AI and use prompts to get decisions out of it. Already, numerous AIs are being trained on database management.
Lack Of Data Literacy
Finally, your data problems may simply arise from a lack of literacy. If people in your organisation don’t understand how it works, then they may not be in a position to use it the way you want.
Therefore, ensure you provide sufficient education and get people on your team who understand data. The more you can implement, the better.
