OPINION: Better decision making: less conversation and more action
Competing with analytics is the new mantra for many major financial institutions, articulating corporate strategies to include specific initiatives for information management, business intelligence and business analytics, according to Paul Franks.
While effective decision-making and reducing the risk of getting it wrong are top-of-mind for boards and senior management, we continue to see many challenges arising in financial services in respect of technology which is able to both provide insights and guide decision makers by using available information assets.
The main challenges often encountered are:
- Effective information management and governance principles and practices, including access, ownership and usage of data
- Confusion between operational reporting, business intelligence and analytics and what each of these capabilities does and can deliver to decision makers
- Foundation technologies and infrastructure to support and enable data to be captured and aggregated from multiple data sources for use across the enterprise, including data from social media
- Limited knowledge of the technologies available and how they inter-operate and are fit for business purpose
- Big data as a catch-all for business intelligence and increasingly, analytics
Given these challenges, it is unsurprising that it remains difficult for
many organisations to recognise and understand the transformative value
of better business intelligence and analytics to improve business
decisions and performance. The end result is often continual inspection,
repeated assessment, lots of dialogue, frustration and – regrettably –
Services, SAS Australia & NZ
What is really missing for many organisations which genuinely desire to be savvier with their valuable customer and operational information are answers to the questions: Where can we realistically start? What does good look like? And how can we get there? The conversations are well known to many of us yet acting on them by providing answers is often where the rubber should hit the road. How can you gain traction in becoming an analytically capable organisation? Let us consider three important steps.
Understanding the higher intent
A good place to start for any organisation seeking to develop its business intelligence and analytics capability is an understanding of its current strengths and the stages of development for data, process, people and technology which can be undertaken to deliver early results and which consider operational and cultural change within acceptable levels of risk.
This is best achieved with a simple capability continuum which permits discussion and consideration of the key operational and functional business requirements for business intelligence and analytics capabilities. Early agreement on where the organisation can readily address capability gaps at relatively modest levels of investment and gain early results is the ideal outcome. This then allows for a more considered and deeper assessment of areas requiring significant investment and increased change management for adoption of new business processes and enabling technology.
Developing capabilities on solid foundations
Any organisational capability should be designed and built on solid foundations and business intelligence and analytics is no different. Nobody builds a house on sinking sand yet all too often business requirements are poorly defined and missed altogether. It is vital to get business requirements on the correct footing from the outset and then take them from a conceptual to a technical level which is understood and supported by all business and technology stakeholders. In defining requirements, identifying existing technology infrastructure which can be leveraged or enhanced and deliver required elements of functionality is well worth the time investment.
Often, this infrastructure can offer a base for further developing your business intelligence and analytics platform if there is sufficient performance capacity in the earlier stages. This allows available funds to then be used for enabling or advanced technologies in the later stages. Finally, technology architecture at a conceptual and technical level is essential, particularly where developmental technologies are being considered for purposes they were not originally designed to perform.
A new approach to data management
In previous articles, we spoke of big data as a relative term where the volume, velocity and variety of organisational data exceed its storage or compute capacity for accurate and timely decision making. The added dimension is that more of this data is unstructured or externally sourced, including from social media, and matters of relevance and utility are topical. Being able to separate the good from the bad and focusing on information that counts is critical. This calls for a holistic approach at the enterprise level for information governance and data management. Embracing this holistic approach and treating data as a core enterprise asset calls for rethinking existing data management strategies.
Using traditional data management practices to harness and extract value from big data will only confirm that accepted rules no longer apply. The days of data integration as a standalone discipline are going and in its place is a mindset where data integration, data quality, metadata management and data governance are considered and designed for use together. Traditional data extraction approaches are being augmented with those that minimise data movement and improve processing power.
There are indeed organisations that took a purposeful step and invested in business intelligence and analytics to transform their business decision making and operational capability. They did discuss their business needs and requirements at sufficient depth and length as would be expected before making any significant investment. However, the big difference for these organisations is that they went from conversation to action. Having done so, they are gaining genuine business benefits which deliver value to their customers and shareholders.
After all, being able to predict the future with greater confidence is what good businesses should be able to do. Transforming your business with better business intelligence and predictive analytics is how financial institutions can gain these capabilities. Isn’t it now time for a little less conversation and more action?
- Paul Franks, SAS Australia & NZ, big data, analytics, decision making, information management, business intelligence, business analytics
- AB+F Online
- Article Posted:
- February 01, 2013
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