Large-scale, long-term business transformation projects have gone the way of the dinosaurs – the pandemic was the meteor that brought the final killer blow. As Peter Ruffley, CEO of Zizo, insists, it is now the era of instant data analytics, with short, highly measurable, rapidly deployed projects that bring answers to data problems quickly.
Despite the ubiquity of large-scale projects for the past few decades, few organisations ever really reaped the benefits promised at the outset. Years-long data warehouse developments, for example, were hugely expensive and resource intensive, yet failed to deliver any valuable business insight. And yet, consultancies continued to win new business; software developers reaped extensive – even excessive – licence fees; and the behemoth data projects continued with the advent of Big Data and the creation of Data Lakes. The last hurrah of the internal IT department, there are no happy business HADOOP customers.
In the new era of a hyper-mobile, hybrid business workforce, information needs have changed fundamentally. Without face-to-face interaction, remote workers have far less trust in the information provided by distant colleagues – or distant business partners/ suppliers/ customers. Younger generations also have zero appetite for long projects; wanting to make a fast impact on the business before moving on to the next challenge.
Companies also need to respond to a very different era of business relationships at a time of extraordinary operational challenges. From managing the impact of inflationary pressures to continued global supply chain disruption, organisations need to be more agile than ever in their decision-making, change direction quickly, and create an environment of incremental gains.
Demand for fast access to trusted information is nothing new. What has changed is the attitude and expectation. There is no tolerance or budget for long-drawn-out, IT-led projects. Indeed, IT teams no longer have the skills or desire to tackle such projects. There is no appetite for extensive data restructuring exercises, or budget to invest in expensive tools with huge licence, implementation and training costs.
Furthermore, ambitious IT individuals don’t want to be tied to some endless development with no expectation of tangible deliverables in the next few years: how would that look on the CV? The current generation of IT and business professionals want quick wins and a way to demonstrate incremental digital transformation – and that means taking a very different approach to data analytics projects.
The new mantra is not just fast change and confidence in tangible deliverables but: can this be done now? ‘Is the data in place to support this objective?’ is the most important question to ask – and answer. This model is nothing like the ‘build it and they will come’ approach of data warehouse projects that spent years collating data resources before the business even had a chance to verify the relevance of what was being collected, let alone determine whether the information could support business change. In the case of Big Data projects, fishing meaningful insights out of vast data lakes proved to be time-consumingly expensive, even for the biggest corporations that tried it. Instant data analytics projects must be able to answer the data question within days, assessing whether the data is of high enough quality and completeness to answer the business question.
The difficulty of unlocking data from systems both old and new has been driving a wedge between IT and the business for decades. The pandemic has now pushed the business over the edge: there is no acceptance for long-drawn-out projects with no end date and no guarantee of value. No tolerance for lumbering consultancies and software houses that demand long contracts and huge licence fees – on projects that will be inevitably derailed by staff turnover and the loss of a project sponsor.
Managers at every level of the business are not only motivated to make their mark faster; they want a business-driven project that accurately reflects priorities. And they want smaller projects that deliver meaningful business information – quickly and at a price point that makes sense. By consigning outdated mega projects to history, companies can rapidly create a new era of fast, incremental data-led business improvements and, in the process, start to rebuild essential trust.