31 January, 2017
Companies often refer to their data as assets, using the same term that is often also used to indicate people, expertise, machinery, or facilities. The implied value of these data assets, however, remains passive until you realize it through an effective strategy and the right leadership.
In an article reflecting on the 2017 Consumer Electronics Show (CES), the management consulting and recruiting company SpencerStuart notes that many companies struggle with effectively monetizing data. That’s something we come across in many different organizations. By any measure, most businesses are generating and storing far greater masses of data than ever before. If they use or make products that are connected to the internet of things (IoT), they receive data from yet another source in addition to the personnel, operational, transactional, and historical data they already own.
Traditionally, the storage, maintenance, and protection of data was a responsibility of the IT department. IT would choose and implement the best tools and practices to manage data lifecycles. The business groups had their own applications to access and analyze data subsets, and they could request assistance from IT when they needed more comprehensive reporting.
That model might have worked reasonably well when only certain executives and managers needed to make decisions or perform planning and forecasting for which data were essential, and when data sources themselves were limited. Today, however, when almost any process and activity generates data that could potentially be valuable, and when many more business roles are expected to think, decide, and plan based on data evidence, your data practice needs to evolve and expand. Ever-increasing data masses will demand more powerful technology for storing, managing, and safeguarding them, but, even more important: You require a strategy that determines how you translate that data into tangible business value.
Your data strategy needs to meet companywide insight and decision-making needs, which means connecting data closely with your goals and with the business roles and processes that create customer value. To help people make sense of data, you need to equip them with meaningful metrics and analytical tools that help them gain intelligence. If your company is taking advantage of the scalability and elasticity of the cloud to process and store data, you will be able to benefit from the cloud-based analytical tools offered by leading cloud services.
When data becomes reliable, actionable intelligence, it leaves the confines of IT and becomes increasingly valuable for executives and many other contributors. It requires solid leadership – as SpencerStuart points out – and planning to make this happen. You also need to consider that different types of data can help people accomplish different things, but connecting them with other data categories can be more impactful yet. For example, IoT data that tell you how certain machines perform under real-life workloads can help you prevent breakdowns and improve the productivity of the equipment. This could apply to your own machinery as well as to machines you deliver to customers. When you connect that data with engineering, materials planning, and purchasing information from the ERP system, for instance, you may also find ways to design or procure better equipment parts, or identify raw materials that work better in your application. What’s more, your data insight can also highlight possible process improvements. To implement those strategically and meaningfully, again needs smart leadership and intelligent process modeling and planning.
We are in the business of helping companies address their strategic and leadership challenges when it comes to transforming your company based on data insight. If you’d like to have a conversation, please contact me.
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