Recently, we visited with several dozen CIOs and IT leaders, across all industries, to learn more about the challenges they are experiencing in their current transformation initiatives. The focus of our discussions was on promoting and enabling digitally driven outcomes and quicker business decisions. The conversations reminded everyone that there isn’t a one-size-fits-all approach to the journey and that each organization should focus on its operating model, the architecture of the organization, and the availability, accessibility and necessity for data to help inform the decision-making processes.
A few key themes emerged:
- Legacy technology continues to hinder the ability to operate at the pace business needs. The complexity of an organization’s application landscape, along with the lack of perceived value in modernizing core applications to introduce new capabilities and enhance existing capabilities, introduces risk to both internal colleagues and external customers. Organizations struggle with trade-off decisions on the ROI to move to the cloud while upskilling their IT organizations to support the new capabilities.
- The voice of the customer needs to be core to the ability to align business and technology in delivery. Without attributing IT investment and IT development to the value it drives for the business, organizations struggle with delivering meaningful capabilities to the internal organization and their external customers. The risk of shadow IT and the loss of faith in IT’s ability to deliver to the enterprise creates redundancy in the environment, rogue decision-making in application investment and overburdened cost and complexity in running the organization.
- While the organization wants access to more data, more frequently, there are challenges with exposing all data without the proper business cases. While data is one of the strongest assets of an organization, exposing that data for meaningful decision-making comes with challenges. How much data does technology expose to the business? What is their confidence in the quality of the data? How do companies ensure the data used by the business has the right governance around it to have a common meaning across departments? Does all data need to be tied to a business case? Our discussions highlighted a variety of challenges – including the concern that the business truly does not have the right business cases in mind to give technology direction in what type of data would fulfill the needs.
- Forward-looking organizations are leveraging the promise of productizing their data and investing in data governance as a key to that productization, whether for internal use or for opportunities to monetize/commercialize data products. Organizations with strong data governance practices are more equipped to empower citizen data scientists/analysts and enhance the speed and effectiveness of decision-making.
There isn’t a simple solution to these themes. Having the right technology operating model that’s fit for purpose for the organization, coupled with the right governance processes and equitable representation in strategic decision-making is a foundational step towards enabling technology to be a partner to the business. Leveraging that operating model to align strategic objectives to business requirements and technology capabilities will allow organizations to deliver using existing technologies while also building a roadmap of technology investment that is transparent and drives trust and an improved partnership.
Additionally, organizations should seek out the voice of the customer by understanding how delivery of products and services align with the desires of an ever-fragmented customer journey. Defining customer journeys for both internal customers of technology and external customers of products can help identify moments in that journey where technology or process can have a significant impact. Business architects in the technology organization can bridge the gap between business domain leaders and technology experts and speak a core language that’s common between the domains.
From a data perspective, not every data request needs to be tied to a business case, but providing the guardrails around how data is used for exploratory purposes vs exposing data to make decisions that can alter the business of the organization is important. Developing data architectures that align to the organization’s broader enterprise architecture standards and collaborating with the enterprise to educate them on the sources of data, the quality of the data, and the governance around the data can improve the business domain’s confidence in the decisions or analysis done with the data.