Finance managers share responsibility for ensuring that all assets in the organization are delivering full value. As intangible assets become more critical to organizational success it is more challenging than ever to measure and manage those invisible resources that are seldom represented on the balance sheet or tracked in financial accounts.
Intangible assets are not all managed with the same level of attention. Human capital is managed with the guidance of the human resources department and brand assets are the responsibility of the marketing department. However, in many organizations, the invisible asset class known as data has no clear owner or champion. All too often information technology managers are more interested in technology than information. They take responsibility for the processing, safekeeping and distribution of data but will defer to other departments on issues related to data ownership, data quality, privacy and access. As a result, who owns the data can be unclear. This split responsibility can result in inconsistent policies and missed opportunities when it comes to the full realization of value from data.
Why is this an issue? A constellation of forces are at work. The volume of data being created is exploding, doubling globally every year. Data is no longer stored in one place but resides across the organization and up and down supply chains. Organizational data is in data centres but also in the cloud, on desktops and on mobile devices. Moreover, relevant third-party data that can enhance the value of internal data is available for free or to purchase. With so much data accumulating, many organizations have failed to keep pace.
Yet many leading organizations have recognized the competitive value inherent in their data. They have exploited recent advances in data analytics and data science. They have applied machine learning and artificial intelligence to define new products and services. More than just reporting historical performance data, these organizations are predicting the future, optimizing operations to deal with continuous change and developing innovative offerings based on newfound insights from previously ignored data.
What are the keys to driving value from data? Data needs to be managed as rigorously as traditional asset classes like cash, receivables and fixed assets. Responsibility for data governance and custody needs to be assigned, with appropriate metrics and rewards for managing the performance of the data custodians. New investments in data, including efforts to improve data quality and usability needs to be part of overall investment planning. Since not all data initiatives deliver the same yield, so potential rewards and associated risks should inform all data investment decisions.
As part of any strategy to enhance yields from data, the organization needs to consider investing in new talent with roles such as data analyst, data architect, data engineer and data scientist. Beyond traditional spreadsheet and business intelligence systems these new team members will be most productive when equipped with more advanced tools for data exploration, data visualization and self-service data analytics. Managing these new resources falls to managers who understand this work and can drive meaningful change. Business analysts will also be critical to ensuring that teams focus on the most promising opportunities. The key is teamwork.
For smaller organizations the stakes are higher as they have less tolerance for experiments that might fail. They are more vulnerable to the larger players in their industry and to disruptions from outside. The path forward demands increased management education and discipline as well as support from experienced outside advisors. As with all organizations, there are no silver bullets and the pitfalls are numerous, particularly when it comes to translating insights into action.
Professional accountants and responsible finance managers share a bias tends towards control, cost containment and cost reduction. While this is familiar ground and a valuable place to begin, realizing significant value from data more often comes from product and service innovations. This means having a clear understanding of customer needs so that data insights can be used to shape and enhance customer experiences. Where to start? There are some obvious steps to take. Tackle your data governance challenges first. Establish data custodianship, define data quality standards and privacy policies. Take a full inventory of the organization’s data assets. Learn where in the organization work on analytics is playing a meaningful role and find the data analytics champions. In many organizations the most sophisticated talent can be found in the marketing department, but they could be anywhere. Research your industry to understand how data is shaping the competitive landscape and driving innovation. Finally, educate yourself on the fundamentals of managing data for value. With this preparation you are ready to mobilize the organization to drive value from data. An earlier version of this article was published in 2019 by the Chartered Professional Accountants of British Columbia.