The evolution of technologies and solutions dedicated to making the handling of data more efficient, more secure and more dependable has been pivotal in helping companies confidently make data-driven strategic decisions.
Thanks to this, organisations that juggle a lot of data day-to-day, such as those working in the asset management industry, can feel more confident about the validity of the information they have available and its capacity to make a real difference moving forward.
However, the threat of data mismanagement still holds firm in today’s landscape. With such a swell of data being stored within modern workplaces, mistakes are likely to happen if effective precautions are taken.
So, what are the signs of data mismanagement within an organisation, and what steps can be taken to minimise it?
What is Data Mismanagement?
Data mismanagement refers to weak or ineffective processes in place for acquiring, validating, storing, protecting and processing data. With just 11% of those who participated in a recent Altair Knowledge Works survey saying they were ‘very satisfied’ with their organisation’s investment into data and analytics, this indicates that these problems are fairly prominent across the business landscape.
Fundamentally, we want to ensure the data is:
Without these characteristics, trying to apply this data to guide strategic decision-making and support growth will carry risks, which have the potential to cause costly mistakes. Through data mismanagement, instead of working for the organisation, data could actively work against it.
In fact, IBM estimated that in 2016, bad data cost U.S. companies a combined $3.1 billion, as well as significant sums of time dedicated to correcting mistakes and cleaning data that is deemed to be unreliable.
Data mismanagement is often a product of poor data governance. Having these controls and systems in place over information helps limit the risk of data being mishandled or left unreliable.
That is why we have made the governance capabilities of our solution so comprehensive; mistakes may not only stunt an organisation’s growth, but cause them to fail compliance, which can be massively consequential for those responsible for individuals’ financial portfolio.
The Signs of Data Mismanagement
What are the red flags that should indicate that data is being mismanaged in an organisation? According to the 2019 Global Data Management Benchmark Report, the predominant causes of inaccurate data are:
- Human Error
- Too many Data Sources
- Lack of Department-Wide Communication
- Inadequate Data Strategy
- Current Relevant Tech
These are the mistakes and complacencies that businesses need to avoid or be wary of when managing the data available to them. And these issues have risen in parallel to the abundance of data that companies now have to hand and are responsible for applying correctly.
With these causes of inconsistencies in mind, here are 3 signals that can indicate that data mismanagement is taking place within an organisation.
- Spreadsheets are the predominant means to manage and store data
While spreadsheets still have their place in the workplace, when the need to keep the volume of data within an organisation accurate, secure and digestible, a more robust, future-proof system is typically required.
Due to the manual steps involved in overseeing and updating spreadsheets, be it duplicating errors or fixing errors, this renders this approach to data management typically slow, unrepeatable and prone to human error. This has led to ‘inconsistency’ being the most painful challenge of utilising spreadsheets for this all-encompassing task.
- An incohesive data strategy is resulting in ineffective teamwork
Research suggests that the knowledge of data sets comes from various forms of company-wide communications, such as email, internal networks and word of mouth. And while this a good sign that teammates are collaborating, these channels are not great options for data-driven decision making.
Using these unofficial and disparate channels to manage data leaves an organisation open to inconsistencies, governance gaps and regulatory problems, as well as an inability to track and record this information in one, universally accessible resource. That means information can easily be lost or mistranslated, and when members of staff leave the company, valuable knowledge regarding this data may depart with them.
A company’s approach to communicating data processes comes from having a coherent, unified strategy at the top – without this, deviations can quickly creep in.
- Decisions are being led by instinct rather than verifiable data
Thirdly, the incredible potential that data can provide in guiding an organisation forward is immediately lost when key personnel overlook this in favour of their internal instincts. This can be due to management believing they know what’s best for business regardless of information to the contrary, or they do not trust the data they are being supplied.
The latter scenario is more typical of an environment where data mismanagement is prevalent. With only 17% of capable of determining data lineage without specialist IT support, having technology in place that can make information more manageable and easy to understand is crucial to ensuring everyone associated with an organisation can make a meaningful, data-driven contribution to its direction moving forward.
Finding Resolutions for Data Mismanagement
Now the signs of data mismanagement have been addressed, what can an organisation do to respond to these concerns?
With the impact that poor quality data can have on progress firmly in mind, it is important to address each of the key concerns identified one-by-one.
Beginning with removing the reliance on spreadsheets, it is a wise investment for companies to invest in self-service, all-encompassing solutions that allow users to share information and capably assess how the data can inform better practice within the organisation.
Introducing comprehensive systems, such as our dedicated fund data management solution, will play a key role in making data management more reliable and efficient. When you consider that companies can lose up to 20% of their revenue as a result of poor data quality, this is typically an investment worth making.
Next, the issue of communication. As alluded to, this will stem from your overarching data management strategy. It is imperative that an organisation establishes formal channels and processes for sharing data, potentially in the form of a Master Data Management (MDM) system.
The right technology can offer valuable support in this area as well. But fundamentally this is about determining an approach that all members of the organisation are aware of and can use to collaborate and exchange knowledge simply and quickly, meaning no misunderstandings or duplication of efforts.
Finally, reducing the tendency to follow our gut. In this instance, appointing an experienced, skilled Chief Data Officer (CDO) or dedicated IT professional can help to ensure the validity of a company’s data and point people towards trusted sources.
Through this, employees can feel confident that the information they have access to will have real potential to introduce meaningful improvements to the company structure, processes or outcomes.
Take Control of Your Data
We hope that this article has provided a deeper understanding of the risks associated with data mismanagement, how to spot instances in an organisation, and how you can address these red flags to ensure data going forward is reliable, accessible and geared to helping your business evolve.
While with the excess of data across the entire business landscape getting larger with each passing day, with the right tools, personnel and strategies in place, it is possible to minimise the presence of data mismanagement and harness information to push your company forward.