Companies must develop capabilities to analyse data and to ensure survival in these disruptive environments. They require forewarning and strategic priorities in realtime. This is lacking in most companies with the current epidemic exposing the limitations of and shown them incapable of predicting remedies for such disruptions. Companies must develop their analytic capabilities and develop a strong data model when tested by disruptive events.
Companies need to develop greater agility to proactively detect trends and respond to new challenges. This should come from strengthening three areas - improving the quality and connections of the data; augmenting the analytical capability; leveraging talent capable of bridging the business needs with analytics and find opportunity in data.
The answer is in the data
The need for data is ever increasing and this becomes even more critical in times of crisis. Gaps in data in terms of quality - disconnected, poor granularity, inadequate curation become major roadblocks when companies must act quickly. A crisis can become opportunities to augment data quality and enrich data to better serve customers and the company. Monetising data comes from four different sources.
- Connect data with other data in a different way
- get new sources or new levels of the same data.
- Put the data to quick use
- Get data faster.
Leaders must prioritise investments judiciously by taking a total view of what is happening across functions. The quick collection of data combined with other economic factors allow companies to better serve their customers in times of crisis. New sources of information can help ensure the customer is protected and prevent frauds.
As is the case for all business units, the requirement of funds far exceeds what is available, and investments in data management are not given its due importance because ts value is difficult to articulate. Use the crisis to enrich your data and understanding of the customer.
Augment analytics
Analysis of data is a blend of art and science. But the nature of a crisis and the events that follow do not permit an analyst to build their typical projections and formulate baselines. Rapidly changing market conditions require constant fine-tuning of models and analytics to stay current. This requires proper data sense to set the right parameters and optimise.
Business rules are often said to be the opposite of data-driven models as hey have a subjectivity associated with these decisions. In a crisis, the basic parameters become vital for a business to function properly. The whole approach to customers may need to be recalibrated based on daily changes. This requires an augmented approach to analytics and a greater blend of man and machine and of business rules and models to navigate new, unexplored areas.
Business-analytics hybrids
Responding to changes during uncertain teams requires an additional level with a superior blend of business with technical capabilities to transform data. Businesses need hybrid teams capable of fonding opportunity in data and executing quickly and accurately.
Data and its analytics can overwhelm leaders from acting quickly due to the volume of data. To breakdown data, identify trends and contextualise them the different functions of business must come together. While the virtual and remote workforce has been accepted as the norm today, the intense collaboration among the people has formed strong networks that are at the heart of survival.
A culture of analytics and business collaboration
When teams come together to analyse data from different perspectives, they gain comfort in establishing more knowns in an unknown world. this helps leaders make decisions quickly. This will help companies gain a competitive advantage and thrive in the disruption.
It is important to ensure that this collaboration is continuous, interactive and inclusive with both teams present to interpret data properly and all stakeholders understand the actions required.
To detect disruptive events with agility, companies must develop their analytical ability. An agile approach to data and analytics is a prime requite for companies to navigate through uncertainties.
How Organizations Can Build Analytics Agility
Lori S Beida MITSMR 202010
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