- September 1, 2022
- Posted by: Bernard Mallia
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Data as the Currency
Even though new methods have been developed to make AI work reasonably well with restricted datasets, data remains the currency on which AI is premised. However, the role of data goes much further beyond AI alone. In the shorter term, organisations that are driven by data-based insights can turn decision-making into a strategic advantage by uncovering market insights that their competitors might lack, or would enable them to catch up with firms that have already capitalised on that advantage. When such insights can be made to feed back into processes, procedures and the directional strategy of an organisation, however, data-based insights can become a source of almost-instantaneous competitive advantage.
In a business world increasingly inundated by data, where changes occur at break-neck speed and abrupt, ground-shattering disruption coming from low-probability, high-impact events is becoming the norm (just think about Covid-19 or the Russia-Ukraine war as examples), organisations that have been encumbered with legacy systems are realising that approaching analytics and strategy as functions that are separate from the rest of the business, while being certainly better than not having analytics or strategy at all, is, in most cases not the best approach. Instead, they are looking to turn analytics and AI into a core capability across the enterprise by promoting a culture of data-driven decision-making, decision-support and strategy formulation and by automating processes from data capture all the way to data-based decision-making. This is where AI comes in. Its ability to mine data, interpret it and formulate insights and predictions go beyond what humans are currently capable of.
The biggest strength of data and analytics rests in its potential to guide and assist executives in making more informed, effective, and intelligent business decisions. This is the benefit of becoming a data-driven organisation. Organisations frequently struggle to see meaningful results from their analytics investments. Most of the time, this happens because turning data into insight, which is already a big organisational milestone, is no longer enough; you also need the capacity to turn knowledge into action. An organisation that infuses analytic insight into the decisions it takes making use of data, statistical and quantitative analysis, as well as visualisation tools and techniques to empower its systems (which include to varying degrees people and robots) can use the insights thus garnered to improve the way it does business. If on top of that, the organisation manages to build a higher AI layer, most of this empowerment can be put on steroids and on autopilot.
There are eleven essential building blocks to become a data-driven organisation:
1. Defined business objectives that are not only aligned with, but also integrated into the organisation’s vision and strategy;
2. The right leadership;
3. The right data governance framework and processes;
4. A data strategy that is aligned with business objectives and that does not limit itself to structured internally-generated data while providing assurance that pooled data is of a high-quality while ensuring regulatory compliance;
5. The right technologies and data management platform;
6. The right data analytics tools, techniques and business processes, as well as delivery model to disseminate insights across the organisation;
7. The right people, particularly when it comes to the data science team;
8. The right skills and continuous training;
9. The right organisation structure;
10. The right corporate culture; and
11. The right partnerships.
The results of becoming data-driven organisation are that:
1. The organisation will have a clear understanding of its customers, their needs and preferences;
2. The organisation will be able to make decisions based on data rather than intuition or gut feeling;
3. The organisation will be able to track the performance of its marketing campaigns and make necessary adjustments to improve results in a shorter timespan;
4. The organisation will be able to develop more targeted and personalised marketing campaigns that are more likely to convert into sales;
5. The organisation will have a better understanding of its own business operations and be able to identify areas where improvements can be made;
6. The organisation will create one source of the truth; All employees will be accessing data from the same data repository, which will help to make better business decisions;
7. The organisation will become more agile and responsive to change as it will be able to make decisions quickly based on data rather than having to wait for reports that take time to compile;
8. The organisation will save costs as it will be able to identify areas where improvements can be made more easily and thus avoid wastage;
9. The quality of data will improve over time as the organisation becomes more experienced in collecting and analysing it, and as the AI algorithms learn over time;
10. The organisation will develop a competitive advantage over its rivals who are not using data effectively; and
11. The organisation gains the ability to grow revenues, reduce costs, mitigate risk and compete more effectively.
Organisations and service providers that do not include analytics into their daily operations and applications are at a significant disadvantage relative to their competitors. Organisations doing business today can profit from human collaboration enhanced by AI and analytics by focusing on education, enrolling executive sponsors, and modelling and rewarding the correct data-driven behaviours.