Organisations understand the importance of having an analytics tool that gives them a complete understanding of their customers, and the ability to communicate those insights and act on them at-scale across the organisation. Indeed, according to Adobe’s Digital Trends 2019 report, the ability to prioritise customer intelligence and insights for a holistic customer view was a top three marketing priority.
The challenge for many brands is that the people who touch the data – data scientists – are often siloed within an organisation. Those who could need to leverage the data in meaningful ways, such as IT employees, might not have access. Businesses grapple with scarce resources, against the need to analyse the incredible amount of data that is collected – and the need for business insights to drive efficiencies and growth.
It’s clear that the data scientist role has become increasingly important for any brand looking to stay relevant. But as more data becomes readily available, and brands are able to understand that full customer journey, the focus will shift from data scientist to IT. The data science skillset is no longer important just for employees that work within data, but also for anyone in the IT world – and it’s an opportunity for the IT organisation to shine.
Here are seven key trends that we see reshaping the world of data and IT:
- IT’s data estate will continue to grow. As a stakeholder for all other orgs, IT is the most logical group to have responsibility for breaking down data silos and bringing everything together in one place for analysis and action. As IT organisations look outward, they will find that disparate teams have a lot more customer, operations, and transactional data than they imagined. IT will need strong data strategy and governance to bring all of these points together.
- IT is best positioned to take the lead on issues of consumer privacy and data security. As a traditionally governance-oriented organisation, IT can bring much to the table to ensure that all other teams are following both best practices and legal requirements around the collection, storage, and use of customer data.
- CIOs should grab the bull by the horns and take ownership of bringing together customer data. Earlier this year, HBR reported that 72% of C-level executives said that they have yet to forge a data culture, and 69% have not yet created a data-driven organisation. In many companies, there is a vacuum of centralised data leadership, often despite the efforts of a Chief Data Officer. IT, with its technical aptitude and focus on process, is best equipped to step into this leadership role.
- IT should become familiar with stakeholders’ data needs and use cases. Your data strategy will not succeed if stakeholders do not believe their needs will be met by an IT effort to enable data-driven decision making. If marketing’s priority is cross-channel personalisation using machine learning models to determine next best offer, then IT must seek to understand and prioritise that use case against other company priorities. Simply tossing a bunch of data into a lake isn’t enough. IT’s approach should be based in a multi-year view of what other teams need to be able to do with data and the ROI that teams expect to achieve from these activities; investments should align with that view such that IT is headed in the same direction as its stakeholders.
- The customer intelligence revolution positions the IT organisation to increase in value. The customer intelligence revolution may sound like a marketing- or product-led trend, but it may be the IT organisation that has the most to gain. Bring all of the company’s data together in one place and facilitating reporting, analysis, and insight puts the CIO squarely at the front of establishing a data-driven culture and improving the customer experience. Investing in breaking down data silos and taking the lead on bringing peers to the table to design/implement a strong corporate data strategy is fully in the CIO’s grasp, and will only raise the importance and value of the IT organisation.
- IT needs to ramp up its data science chops for data governance as well as obtaining value from combined data sets. While many IT organizations possess deep technical knowledge, the challenge of bringing together massive and complex data sets from a wide variety of peer teams may require investment in new skill sets. Data science is a lot more than machine learning, although stakeholders will require ML/AI help as well—it includes data wrangling and data visualisation skill sets which may be shorter supply in some IT organizations.
- Brands will increasingly move customer data to the cloud to take advantage of its scale and services. Five years ago, many brands swore they would never move customer or operations data to the cloud. This reticence was grounded in security concerns and the inability of cloud vendors to solve certain key use cases, leading brands to wonder why they would bother to move all of that data elsewhere. More recently, cloud vendors have made huge leaps forwards in addressing both of these areas. This has included adding numerous services both to connect data to decision-making and real-time actioning both for internal as well as customer-facing use cases. It has also included enhancing the security of customer and key business data in the cloud through enhancements like shielded VMs and credential management tools. While there may still be some advantages to an on-premise data store, these are dwindling as cloud vendors see the value of securing and scaling data for brands.
Data is becoming more important than ever. As companies struggles to mobilise their siloed organisations around a common focus on customer intelligence, it’s IT’s moment to shine. The data revolution is calling on business to take ownership of data to unlock its full value, and IT is perfectly placed to rise up to the task.