Many businesses find that the data they collect has limited reliability.鈥♀�痳ecent鈥�痓y Experian highlighted 鈥痶hat鈥�55% of business leaders do not trust their data, ultimately impacting the confidence that business leaders have over the data they collect.鈥�&苍产蝉辫;
Bad data can have significant business consequences鈥痜or companies.鈥疪esearch by鈥� found that approximately 77% of companies鈥痟ave the belief that their bottom line is affected by inaccurate and incomplete data, with a further 12%鈥痮f revenue being believed to be wasted due to poor data quality. Nevertheless, companies that did put a focus on high-quality data saw a revenue increase of 15% to 20%.鈥�&苍产蝉辫;
So let鈥檚 unpack in more detail those reasons why Data Quality is important:
1) Business Decision Making鈥�鈥�&苍产蝉辫;
The usage of a data quality vendor ensures ongoing data quality checks, which ultimately make sure that enterprises have cleaner, safer, and high-quality data. This offers organisations more accurate analytics, clearer insights, and predictive advantages.鈥疧verall,鈥痩eaders can have greater confidence in their business decision making.鈥�&苍产蝉辫;
2) Helps with scalability鈥�鈥�&苍产蝉辫;
Firms鈥痑re able to鈥痵cale more quickly with a strategic鈥痑nd effective data quality model in place. If infrastructure operates automatically, it also becomes a possibility to scale up without the need to increase manpower.鈥�&苍产蝉辫;
3) Operational Efficiency and Productivity鈥�鈥�&苍产蝉辫;
A data quality tool鈥痯rovides an effective way of removing the need for firms to manually verify large volumes of data. This is often resource heavy, laborious and can lead to duplicate investigations. High quality data overall helps to reduce mistakes鈥痺ith less time needed to manually fix inconsistencies.鈥�&苍产蝉辫;
4) Regulatory Compliance鈥�&苍产蝉辫;
Regulators demand high quality, accurate data specifically measured for a vast array of regulations 鈥� including BCBS 239, a data-driven regulation in and of itself. Businesses need a technology framework that enables rapid delivery of鈥�data quality鈥�measurement and remediation鈥痶o ensure ongoing compliance. It also needs to save time and effort and鈥痯rovide results to senior management that can demonstrate compliance with regulations driven by robust鈥� data quality management.鈥�&苍产蝉辫;
For organisations that have cultural problems around data, how best can they address these?鈥�鈥�
A lot of people associate owning data or being a data steward with being鈥痳esponsible or鈥痟eld to account in a negative way. As the banking and financial services sector is underpinned by risk management, a common challenge is overcoming people鈥檚 fears around taking responsibility for data.
础鈥�culture shift鈥痭eeds to happen to ensure that people鈥痜ocus on better鈥痙elivery,鈥痳ather than being afraid of responsibility.聽We asked Head of Sales at 糖心传媒, to comment on this further.聽
鈥淥ne of our聽London-based聽wealth management clients鈥痟as gone about this鈥痠n鈥痶he best way,鈥痓ecause they have a senior leadership team that really understands the criticality of data to the business. They understand鈥痠t is鈥痑bout听别尘辫辞飞别谤颈苍驳聽those鈥痳esponsible to invest in the quality of data.鈥澛�
This could mean, for example, being able to鈥痵ay鈥�淚f鈥痶he鈥痙ata鈥痺as 30% better on client information, I would expect to see a 5% increase in revenue鈥痮r in鈥痬argin.鈥濃�疞inking the information to business outcomes can help people understand the importance of driving up the quality of information relied鈥痷pon,鈥痑nd how it can help to drive a long-term revenue strategy.鈥���&苍产蝉辫;
Many of the businesses being built today that鈥痙on鈥檛鈥痟ave鈥�榖ad data debt鈥欌�痑re in a great position to benefit from modern techniques from the word go-鈥痶his鈥痵tarting point is what many banks鈥痑spire鈥痶o鈥痳eplicate. It can be said that if you鈥痙on鈥檛鈥痑ddress cultural issues, there is a risk that the business will end up totally disintermediated and losing what made them great to begin with.鈥�&苍产蝉辫;
To have further conversations about why Data Quality is important to an organisation, reach out to