Enterprise agility is the key to navigating disruption and building resilience, and it depends on the organisation’s ability to use data.
1 in 4
business leaders surveyed had lost customer information through cybersecurity incidents
the media attention in the month following a data breach
Today’s most resilient organisations have mastered the proactive use of data science to identify future risks, manage reputation and empower the workforce to perform better. They invest in data competency and embed AI into core processes across major functions to inform decision-making and shape customer experience.
Other organisations are striving to catch up. For example, according to the recent Resilience Barometer, 97% of business leaders are under pressure to integrate innovative technology into their business model; data use is certainly one of the objectives. About 67% of leaders are involved in data and security at their firms – more than get involved in marketing (62%) or finance (61%).
In spite of this level of attention, more needs to be done. Worryingly, more than 1 in 4 companies have lost customer data as a result of cyber attacks in the past year – a sign that all is not well even at the most basic level.
Businesses now need to build on the experience of the pioneers who have already brought real-time data analytics into the core of their day-to-day operations.
Use all relevant data sources. Looking beyond traditional financial data can transform a business’s understanding of its competitive environment and reputation. For example, clickstream data sheds light on the customer journey, and on barriers to completing a purchase. Social media conversations reveal customer and public perceptions, as well as evolving market needs and societal trends. Open Source websites provide a window to regulatory thinking and research. Employee chat exchanges can be monitored to help the business guard against misconduct.
Convert data into information. Data analytics can convert raw data into signals that alert the business to new behaviours or patterns, identify risks such as unprotected personal data, and highlight problems and opportunities. With the help of AI, these signals can describe the past, predict likely outcomes, and prescribe appropriate courses of action.
Democratise data access. Maximising agility depends on pervasive use of real-time data to drive decision-making. This in turn requires actionable data to be available to front-line workers and support functions, not just to users of executive dashboards.
Introduce effective governance. Data breaches and misuse cause untold reputational damage. Information governance is the way to manage such risks. Personal or high-value data can be protected and secured, with measures like data tagging enabling safe data exploitation. Data that no longer has value to the business can be identified and removed.