No matter the industry, every company strives to stay abreast of developments in the wider market, make correct and actionable decisions about its future direction, and provide customers with the products and services they most need. To these ends, contemporary businesses depend more heavily on data than ever before. Having speedy access to clean, high-quality information can, and frequently does, make or break a company’s efforts to respond to changing market conditions and meet business goals.
In spite of the inarguable importance of quality data, many companies today still struggle to acquire, analyze, and act upon their data efficiently. They may also have to funnel significant time and resources into rectifying duplicated, incomplete, or inaccurate information. Most of the time, these data management problems are caused or exacerbated by outdated and fragmented technologies and methodologies.
In many cases, the road to smoother and more efficient data management lies in developing and utilizing a unified data foundation. Modern data management solutions can make this possible for companies, and, in the process, help them avoid the major pain points that arise from dependence on legacy systems. The following four pain points, for instance, are among the most common:
- Legacy systems frequently rely on siloed processes that spread the work of data collection, reconciliation, and analysis across many discrete systems and teams. The fragmented nature of this process makes data management a slow, labor-intensive, and often costly process, as data reconciliation under such systems is usually performed multiple times by individual teams. Data silos also tend to impede interdepartmental communication and may thus lead to erroneous or redundant data input, such as when customer queries are recorded in the system multiple times with different details.
- Contemporary data management software eschews siloed systems in favor of creating a single source of information from which all stakeholders within the company can draw. A unified data foundation allows companies to reconcile and standardize data in a fraction of the time and at significantly reduced cost than it would have taken under a legacy system. This store of clean and complete information can then be utilized efficiently by the teams that need it most, whether they’re working in finance, compliance, risk management, or some other essential sector.
Manual Basic Reconciliation Processes
- A significant number of companies operating today still make the mistake of allocating large amounts of time and resources to manual data reconciliation. They may, for instance, hire large accounting teams whose sole function is to perform everyday calculations, reconcile balance sheets, and execute other fundamental data management functions manually. Depending on manual labor at such a large scale, however, makes inconsistencies and errors all but an inevitability even with a well-trained workforce.
- Automating basic data reconciliation processes accelerates data management and also guarantees more accurate information. Teams that would ordinarily have spent their days verifying and analyzing data are then freed up to devote themselves to taking effective action, as well as engaging in more challenging analytical and predictive tasks. Automation also helps companies uncover a greater number of quality business insights, as many leading software solutions are capable of picking up correlations, irregularities, or biases in data that might often be missed during manual analysis.
Inflexible Data Infrastructure
- In the current business environment, organizations have access to more information about their client and market demands than ever before, and they are also in a position to observe those demands in real time. Without appropriate flexible data infrastructure, however, they will be hard-pressed to act on that information in a timely and effective manner. Many legacy systems, however, lack the agility to address a company’s contemporary business needs. The outdated technology they employ may also be incapable of adapting and scaling itself as those needs change from day to day.
- To address this problem, it’s imperative for companies to turn to cloud-based software solutions for managing and storing data. Data stored in the cloud can be retrieved, stored, sorted through, and disseminated easily. Cloud capability also lets users access necessary information across multiple locations and devices, facilitating efficient coordination between teams when required. Cloud-based software is also capable of reflecting and documenting changes made to files in real time, which protects data integrity and encourages greater transparency and accountability.
- Any technology needs to be constantly updated and upgraded in order to contend with rapidly proliferating and evolving cybersecurity threats. In light of this, it’s but logical to conclude that antiquated legacy technology will have more security vulnerabilities than more modern systems. Since software developers tend to withdraw support for their earlier products over time, it’s highly likely that older software will simply be unable to run crucial security updates past a certain point.
- Data breaches can lead to lost profits, reputational damage, legal problems, and other severe repercussions for companies. Hence, it’s in companies’ best interest to invest in highly secure, modern data management technology, as well as to ensure that these systems are consistently maintained and kept up to date.
- Many companies are reluctant to upgrade their data management systems because of the significant cost it seems to involve. There are abundant case studies to show, however, that contending with the many pitfalls and inefficiencies of legacy systems costs enterprises more in the long run. Embracing a modern data foundation is thus a crucial step for contemporary businesses to achieve their fullest potential.