Thriving in Digitalisation with Less-than-Perfect Data
In today’s fast-paced digital age, data is often considered the lifeblood of a company, fueling critical decision-making processes and driving growth. While it is true that digitalization thrives on clean data, there is a prevailing misconception that without pristine data, the process of digitizing is simply not feasible. However, in this article, we will debunk this notion and shed light on how companies can indeed do good work with bad data, especially when it comes to procurement and CFOs, and how such an approach can be advantageous.
Digitalization Requires Clean Data:
The importance of clean data cannot be understated when it comes to digitalization. Accurate, consistent, and reliable data is essential to making well-informed decisions, optimizing resource allocation, and seizing opportunities for growth. As a result, companies often prioritize data quality, investing in robust data cleansing, governance, and management strategies. This emphasis on clean data is understandable, given the potential consequences of working with inaccurate or inconsistent information.
You Do Not Have Clean Data and Do Not Have Time to Clean:
In reality, many companies find themselves facing the challenge of dealing with bad or incomplete data. Several factors contribute to this predicament, including the presence of legacy systems, manual processes, data silos, and sometimes, a lack of resources. Furthermore, the process of cleaning and refining data can be arduous, time-consuming, and resource-intensive, leading to delays in digitalisation efforts or even discouraging companies from embarking on the journey.
Yes, You Can Do Good Work with Bad Data:
Despite the apparent hurdles presented by bad data, it is possible to make significant progress in digitalization even under these circumstances. The key lies in recognizing that digitalization need not be an all-or-nothing endeavor. Companies can adopt a phased approach, starting small and focusing on specific areas or use cases where data quality is less critical. For instance, implementing digital tools for procurement or financial management can be pursued even if the available data is not entirely pristine. Additionally, companies can harness the power of machine learning and artificial intelligence algorithms to cleanse or enrich the data and make informed predictions based on the available information.
Benefits for Procurement and CFOs:
Even with bad data, digitalization offers considerable benefits to procurement and CFOs. Embracing digital tools and processes in procurement can lead to enhanced efficiency, streamlined supplier management, and improved visibility into spending patterns. For CFOs, digitalization can translate to better financial analysis, more accurate forecasting, and ultimately, more informed decision-making. By taking incremental steps and leveraging targeted digital solutions, procurement and CFOs can overcome the obstacles posed by bad data and still achieve substantial improvements in their respective domains.
While digitalization thrives on clean data, it should not become a stumbling block preventing companies from embarking on their digital transformation journey. The reality is that businesses can still do commendable work with bad data, particularly by adopting a pragmatic approach that starts small and focuses on specific use cases. Both procurement and CFOs stand to gain significant advantages from digitalization, even with imperfect data. By embracing digital tools thoughtfully and investing in a gradual transformation, companies can surmount the challenges of bad data and reap the numerous rewards that digitalization has to offer.
