90% of all innovation projects fail because companies don't take the time to figure out if their current data assets will help them meet their strategic goals. Data audits can shorten your path to data value extraction by uncovering issues such as data accuracy, security, breadth and reap the benefits of confronting problems head on. Nakala Analytics, a leading data analytics startup company from Kenya, has been ranked top among 482 startups that are transforming the data audit space using data analytics.
Today's leaders are in charge of companies that operate in overly complex, diverse, and internationally competitive environments. The world is becoming more data-driven by the day in this era of data. A data audit for data innovation using technology aims to quickly diagnose issues and make suggestions in order to support preparation, collection, processing, use, delivery, and storage of data in a way that encourages affluent innovation and achieves anticipated ROI.
Why a data audit?
A data audit for data innovation from Nakala aims to diagnose and then provide recommendations that make it easier to obtain, process, use, secure, transmit, and store data in a way that encourages affluent innovation and achieves anticipated ROI. Most analytic heavy programmes fail because companies don't take the time to figure out if their current data assets will help them meet their strategic goals. Both components involved in the collection, storage, and consumption of business process outputs, which may be an application output file, log, database, or teams that businesses use to collect data, are referred to as data properties.
The ability to use both internal and external data is a required skill for solving business challenges and preventing the insanity of doing the same action and expecting different outcomes. Only leaders who have a razor-sharp ability to ingest and analyse data-rich environments and accurately convert it into functional strategic decisions will be able to command potential market leadership and competitive supremacy.
Inefficient data auditing processes are a common cause of data analytics programmes failing. Startups create auditing solutions to examine data collection, storage, protection, and processing in order to improve data effectiveness. The solutions assist businesses in developing data usage guidelines that increase revenue by maximising the use of all available data properties.
Nakala Analytics, a Kenyan startup, provides data inventory solutions for data-driven innovation. The company assists in determining if current data assets are adequate for successful innovation. Furthermore, Nakala Analytics detects anomalies and the data's potential, as well as evaluating the efficiency of data collection.
Ensure access to quality
It's important that your team has access to full and reliable data. This is what allows you to analyse in-scope business processes in great detail. However, when it comes to data analytics, this is also the most daunting hurdle to overcome. The front end is where the heavy lifting takes place: defining data, ensuring its accuracy, completeness, and availability, as well as standardising it as required. Internal audit departments that are in charge of internal auditing always start with a single business process (for example, procurement) and work with IT to explain the data. They use business intelligence software, data warehouses, and other tools that are already in use in other areas of the company to continuously provide data to internal audit.
Team work
Some are worried that emerging technology tools (automation) and the experts required to help them would result in job losses in internal audit. You can be assured that the internal auditor's job is secure. There isn't, and never will be, a replacement for their intelligence and judgement. Auditors, on the other hand, must have a strong knowledge of evidence as well as the ability to think critically. They must be able to rapidly understand emerging business processes and use data analytics to develop procedures to mitigate the threats they've found. They must also be taught how to use analytics software and resources. Internal audit groups that are best in class take various approaches to developing an analytics-ready internal audit programme.
Conclusion
Internal audit has the potential to be transformed by data analytics, elevating the position to a senior strategic role within the company. CAEs, on the other hand, must take great care to ensure that implementation is achieved in a calculated, thoughtful, and well-planned way, with the right technology resources, staff, and training in place.
If you're just getting started with any data innovation project, now is a perfect time to perform a Data Audit for Data Innovation. This is the first and most effective step towards data monetization and data value realization.
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