The desire to analyze data that will drive insights and competitive differentiation is older than computing itself. Digitization just speeded things up. Richard Miller Devens used the term \u201cbusiness intelligence\u201d as far back as 1865. The LEO computer was calculating optimal inventory deliveries based on shop performance and generating management reports for the Lyons\u2019 tea rooms chain from 1951. And the very first edition of CIO magazine, published in 1987, included an editorial on \u201can increasing cadre of increasingly demanding customers seeking faster access to information\u201d.\nFast-forward to today, and the dreary meme of \u201cdata is the new oil\u201d that must be chanted at every tech conference by rule of law. The power of data is better understood than ever, but for many, harnessing data, checking its quality, and applying context to assist decision-making remains challenging. CIOs report fragmentation, slowness and silos, even as digital transformation has been accelerated by the pandemic. But there is cause for optimism, in the form of broad modern data pipelines that drive activity and allow what Qlik calls \u201cActive Intelligence\u201d \u2013 the ability to act on reliable data with a rich supporting fabric of context and collaboration to support the right decisions and take informed actions in the right moment. By assembling joined-up processes, companies are following the path from uncovering data to delivering it where it needs to go, governing it through data catalogs, understanding it, augmenting it, and putting it to use via context-sensitive alerts and actions taken in close to real time.\nThe 1990s rise of databases that cleaved to structured query language (SQL) led to a glut of developers and specialists and created a boom in analytics activities. But the dirty secret of SQL is that \u201cit\u2019s great for moving data, but not analytics\u201d, says Mike Potter Chief Technology Officer at Qlik, so we\u2019ve ended up using the wrong tool for the job.\n\u201cFor change, you need to capture data and lay the foundations for an analytics supply chain and a pipeline that builds on this to enable Active Intelligence,\u201d Potter explains. \u201cYou can\u2019t create value in any business process unless you do something. If you believe analytics is all about driving change, increasing revenues and profits, and enabling digital transformation, none of that can occur unless you take action.\u201d\n\nToday\u2019s decision-makers have a lot of tools to work with \u2013 from cloud platforms\u2019 massive elastic compute power and the Internet of Things generating sensor-data that supplements existing sources to networks that carry data instantly to the locations where decisions are made. But Potter is surely correct in highlighting the link between information overload and paralysis in decision-making.\nSo, we need systems that advise, working alongside smart human beings who understand business domain, context, and risk. Whether these are progressive (\u201cit\u2019s a great time to build a shop that sells finger spinners in New York\u201d) or defensive (\u201cthis service level agreement is very close to breaking so we need to address it now\u201d), decisions must be taken quickly before context has changed and the moment is gone. Seize that moment and the promise is enormous.\nThe importance of velocity and first steps can\u2019t be overstated. We must be able to free data, find it and only then invest in data quality processes and add value via augmented data on the fly, to create a holistic, contextual basis for actions. At credit reporting giant Experian, for example, data integration has been critical to ensuring that data is dynamic and fresh to incorporate up-to-the-second verification.\nThen, of course, we must be able to interrogate data and build insights, going beyond dashboards and adding the convenience and immediacy of natural language support, so that non-specialists can ask questions and receive sensible answers without drowning in jargon. As more data sources are added in, unforeseen connections are traced, leading to \u201ca-ha\u201d moments of serendipitous revelation. To that end, chief data officers are becoming popular appointments, and DataOps teams are becoming mainstream; but there must be buy-in across the company to build a culture for data success.\nAssemble that supply chain of elements, and we begin to realize the promise of real-time analytics. In practice, it may not always be truly real-time, but if you can make a better decision, faster than your rival, you are fulfilling IT\u2019s age-old pledge to provide an auditable end-to-end decision-support platform on which great decisions are made in a business moment.\nFor too long, we\u2019ve struggled to connect the dots between what\u2019s needed for a holistic approach to data and analytics, but today there\u2019s no excuse as all the technology components are available. Now, it\u2019s incumbent on leaders to lead. As Clayton Christensen wrote in The Innovator\u2019s Dilemma, many companies have failed because they stuck to the road that had made them successful when they should have realized they were heading for a dead-end. Analysis paralysis is a silent killer for innovation and strategic change.\nFor dynamic companies, however, the rewards are large. For example, Schneider Electric\u2019s finance department is able to predict some quarterly financial performance to within one per cent using analytics.\n\u201cData is the thing that determines how bright the signal is in the fog of uncertainty,\u201d says Clint Clark, the company\u2019s Vice President, Finance Performance Systems and Data, Global Finance. \u201cWhen you build a pipeline that\u2019s robust, you can illuminate those signals clearer and with better timing, and people can make better decisions quicker.\n\u201cYou need to build a culture of trust and show that data has value through repeated demonstrations,\u201d he adds. \u201cYou have to find a way to put data at the center of your decision-making process and be honest about what you\u2019re doing, including understanding your own hidden assumptions and biases.\u201d\nWhat can get neglected? Clark advises not to underplay the importance of data governance to avoid the \u201cgarbage in, garbage out\u201d effect. Also, he says, watch out for the potential \u201ctragedy of the commons\u201d, where people act in individualistic, self-interested ways or use data to back up their prejudices.\n\nBy synthesizing all the assets we have to hand, we can create a new wave of data-empowered companies that make the right decisions at the right time.\nElif Tutuk, Vice President, Innovation and Design at Qlik, believes we can advance enormously if we combine the best of tools, humans, and robots working side by side using natural language for interactions. \u201cThere\u2019s a need to select a business moment to match the data. Active Intelligence enables the right action at the right moment \u2026 and gives users superpowers,\u201d she says.\nNow we just need men and women to apply that advice. Ready, set\u2026 action!\nFor more on this and for the latest trends, visit Qlik\u2019s Executive Insights Center qlik.com\/executiveinsights.