Turning company data into an asset is critical, it gives business leaders unprecedented insights. Data offers numerous opportunities across all industries, from healthcare to manufacturing to financial services, to name only a few.
Most companies own loads of data and for it to be useful, it is imperative that they ensure that it is clean data.
The potential of big data is rather elusive and still not highly prioritised. The truth is, due to legacy systems and accumulating of big and ‘dirty’ data, prioritising data projects can be seen as a long-winded and costly journey.
Importance of data cleaning
Data cannot always be used as it is and needs preparation in a way that it can be considered an asset.
However, this exercise can be a slow tedious manual process that shows no immediate value. The importance of data cleaning mustn’t be underestimated, it plays a significant role in the journey of better understanding customer behaviour and making calculated decisions.
Data cleaning is considered to be a challenge due to the already high and increasing volume, variety and velocity of data in several databases, applications and in physical documents.
With a lot of company data being traditionally messy due to legacy challenges, data cleaning can become costly when left unattended for a long time.
Therefore, the significance of investing in a data journey that benefits a business becomes futile.
The first step in a data journey is cleaning the data. It’s a procedure of correcting or removing inaccurate and corrupt data. This process is crucial and if not done correctly, can lead to a lot of problems. It could lead to uninformed business decisions or affect client records and profiles.
More importantly, businesses could fail to take advantage of many opportunities or under service clients due to lack of a single client view.
Many businesses are losing massive revenues due to big, yet bad data. Data cleansing can filter out bad data, structure and enrich it with accurate data that is useful. Inaccurate data usually includes duplicate records, missing or incorrect information and poorly formatted data sets.
Better quality data impacts every activity that includes better decision making. A business that invests in enriching its data records by fixing outdated data can go a long way in unlocking opportunities. Almost all modern business processes involve data.
When data cleaning is seen as an important organisational effort, it can lead to a wide range of benefits for all.
Some of the biggest advantages include:
- Streamlined business practices: Imagine how much more efficient all your key daily activities would become if there were no duplicates, errors or inconsistencies in any of your data records.
- Increased productivity: Clean data helps one focus on key tasks instead of looking for the right data or having to make corrections because of incorrect data. This could be a game-changer.
- Faster sales cycles: Marketing decisions, using accurate data, can sharpen the approach as to what to sell, who to sell to and how to sell it. Giving your marketing department the best quality data means better and more leads for your sales team to convert.
- Better decisions: Better data equals better informed decision making.
Understanding the granularity of the data
Use data to rationalise the irrational and enhance the qualitative views of business decisions. The only way you can do that is by understanding the granularity of the data.
Instead of applying a one-size-fits-all technique that might even have the highest success rate, we need to understand the specific challenges.
Apply bespoke thinking with befitted data and digital tools to provide scalable, feasible and effective solutions. The reason for our approach is that we find that not all problems are the same.
For example, a regulation challenge at one company can be different from the next – it might be the same in principle but the actual data will reveal what the challenges are.
Good data can lead to a better bottom line. This is not only because of better external sales efforts, but also because of more efficient internal efforts and operations driven by optimised solutions using machine learning, RPA, data science and digitisation techniques, all of which have a massive underlying component of good quality and clean data.
Having data that is of good integrity can evolve to having a well-defined digitisation journey, it allows for digital solutions that are custom and purposefully engineered to help businesses function optimally, improve service delivery, maximise profitability and gain or retain their competitive edge, both locally and globally.
One needs a 360-degree solution that includes understanding the end-to-end processes, the data and its flow, the people involved and what platforms are necessary to empower the overall operations.
By doing so, one can maximise the lifetime value of data and help companies to compete head on with industry disruptors.
It will also increase business agility, convert hindsight to foresight and will unlock new opportunities. Finally, it will reduce exposure to regulatory sanctions and protect the brand from reputational risks associated with fraud and corruption.