Perspectives
Is outcome-aligned data really the future of data management?
5 September, 2022 | Written by: Alex Solly
Categorized: Perspectives
Share this post:
For years, data has dictated the objectives set by businesses. Firms across all industries have gathered data sets and used the information to mould overall business targets and outcomes. However, times are changing; technological pioneers like IBM and Global Elite IBM Business Partner Mastech InfoTrellis (MIT) are adopting a new method of utilising data to the advantage of clients – the data fabric approach; focused on reversing the previous trend, this style ensures the data does the work for the organisation.
This evolution was the topic of discussion by IBM’s Data & AI Synergy Leader, Brendan Buckingham and Kevin Burnley, EMEA Director of Sales from Mastech InfoTrellis (MIT) at IBM Think UKI 2022 earlier in the summer.
During the session they explored how together IBM and MIT are supporting customers using IBM technology to achieve business outcomes through the assistance of data.
They outlined the three areas that business objectives clients are concerned with fall in to:
- To increase revenues
- Lower costs and
- Comply with regulatory obligations
For each of these, identifying and extracting the value of data being the key to success. Creating informed data-based decisions on overall business outcomes was identified as the main driving force for both IBM & MIT, with ways of improving the effectiveness of data gathering being the principal motivations of both companies.
The session further explored how data fabric architecture harmonises business functions with stakeholder requirements to deliver decentralised access to business consumable data without compromising business controls – the data fabric approach.
By utilising this outcome led approach, business functions can identify their needs and the data can be used as contextually informed support systems to reach that outcome. This approach has drastically altered from previous ways of working. Typically, a data architect would design a solution based on previous experience or methods, when in fact a focus on business outcome to inform such approaches is needed. The more developed outcome led approach allows use of existing assets to uncover what is needed to achieve the overall business aims.
The rising cost of employing data scientists due to the scale of data growing at simply too great at a rate was also discussed, driving the development of automation as a key component in data management. IBM’s focus on creating more automated, digital systems rather than the traditional style of an employee managing the data was pinpointed as a beneficial step for clients. The process of data capture, storage and sharing is often ‘unstructured’ and hard to manage so the progress of automation that IBM and MIT are focussing on ensures a much smoother storage operation, benefitting clients.
The Q&A at the end of the session bought forth a question regarding how trustful data can be assured. Tying the data into the overall business objectives was pinpointed as the key. Whilst IT teams perhaps think they know the best way to manage the data, sometimes these methods are not aligned with the overall aims of the organisation. Looking at how the problems outlined by the business can be solved through data points ensures that value is added and therefore the data is more trusted.
The session highlighted the progress IBM is making in creating more relevant data sets with hugely valuable smaller data points being extrapolated over less relevant larger quantities. By aligning these with outcomes, the data clients receive is ensured to be more trustworthy than before, but also far more efficient in its collecting. In addition to this, areas IBM have identified as needing improvement were equally as prominent throughout. Automation was identified as a crucial progressive element. Due to the level of data storage needed by firms being so vast, it is critical automation of previously manual processes is needed to ensure success in managing these data sets. This is an aspect IBM and trusted advisors MIT look to develop, helping to support their clients further into the future.
About Mastech:
Mastech Infotrellis are a Global Elite IBM Business Partner skilled and experienced practitioners in all aspects of Data Governance who deliver the benefits of using a data fabric approach to clients.
Mastech InfoTrellis partners with enterprises to help them achieve their business objectives by leveraging the power of data to derive deep, analytical insights about their business and its operations.
‘We accelerate business velocity, minimize costs, and drastically improve corporate resiliency through personalized, process-oriented programs, consisting of strategy, data management (including master data management), business intelligence and reporting, data engineering, predictive analytics, and advanced analytics.’
More detail on the benefits of adopting a data fabric approach can be found on Mastech’s ‘Deep Dive’ podcast – https://mastechinfotrellis.com/podcast-details/deep-dive-into-data-fabric-the-benefits-of-a-data-fabric-architecture
UKI Ecosystem Co Marketing
Frontier Fusion: Accelerating the Path to Net Zero with Next Generation Innovation
Delivering the world’s first fusion powerplants has long been referred to as a grand challenge – requiring international collaboration across a broad range of technical disciplines at the forefront of science and engineering. To recreate a star here on Earth requires a complex piece of engineering called a “tokamak” essentially, a “magnetic bottle”. Our […]
Safer Technology Change in the Financial Services Industry
Many thanks to Benita Kailey for their review feedback and contributions to this blog. Safe change is critical in keeping the trust of customers, protecting a bank’s brand, and maintaining compliance with regulatory requirements. The pace of change is never going to be this slow again. The pace of technology innovation, business […]
Unlocking Digital Transformation in Government
As the UK government embarks on its digital transformation journey, the challenges of adopting new technologies such as artificial intelligence (AI) and data-driven solutions are becoming more evident. From managing public trust to overcoming fragmented systems, the path is complex. Blake Bower and Giles Hartwright review the unique obstacles that the government faces and […]