Bridging Silos and Managing Change During Digital Transformations

“There’s No Budget for the Common Good”

Organizations have been using digital technologies for decades, but the last several years have seen some remarkable leaps in computing capabilities that have led directly to cost reductions and vast increases in processing power, speed, and storage. With constantly connected mobile devices that place the power of prior era supercomputers into our hands, our lives have been transformed by digital technology. New data sources and the constant stream of behavioral and social media data add layers of complexity for enterprise marketers and those responsible for maintaining capabilities, but they also have created new opportunities for understanding customers and their needs. With real-time data available, the cycle for innovation can be accelerated.

The rapid transformation in the enterprise technology landscape has exacerbated the challenges that still burden large organizations with siloed departments, functions, and applications. Adding technologies – and lately more advanced AI and machine learning capabilities – has led to even greater complexity and more fragmentation of data sources and applications. Customer engagement is spread across every process and system at each stage of the customer lifecycle, leading to problems with integration, inconsistent data, and slower adoption of new tools at scale.  

These limitations hamper effective customer engagement to a striking degree, since customers want a seamless experience--they no longer accept being transferred from department to department, for example. They demand instantaneous access to their information no matter how they are approaching the organization, and they expect that every touchpoint will be aware of their profile, preferences, and history. Siloed information does not allow this level of responsiveness.

Balancing Efficiency With Flexibility

However, siloed structures are also a natural result of business evolution, and they do have some advantages. Specialization and differentiation allow people and departments to do specific things really well and gain efficiencies over time. Developing efficiencies comes from repetition, ingrained habit, and consistent processes.

Inevitably, however, changes in the marketplace mean that processes within the organization must change. Business conditions also continually change, and typically they change so fast that neither people nor technical infrastructure are able to keep up. Therein lies the rub. Organizations must balance the efficiencies that can be gained by specialization with the need to integrate across functions, while fostering the flexibility to adapt to a changing market. In order to achieve this balance, which is likely to fluctuate over time, change management is an essential ingredient.

I recently spent some time speaking with the CIO of a large manufacturer about transformation of processes and supporting technology, and asked how his organization dealt with the necessity of change. He responded that organizations need to manage change proactively and on a continuous basis. However, many people perceive continuous change to be both more difficult and less interesting than buying and deploying new technology. Therefore, the emphasis is often put on technology rather than on change management.

Getting Employee Buy-in

The first thing to remember is that decisions about change usually come from C-level decisions, not from employees. The CEO, CMO, and CFO may conclude after monitoring market trends, profits, and customer retention and realize that without some action, the company may no longer be competitive. So the executives develop a strategic plan that is designed to address these concerns. The plan may be designed to improve customer service, or increase the rate of innovation, or reduce the time to market for new products. If the plan depends on bridging silos of information to support a digital transformation, then the CTO is likely to get involved.

But these individuals are not the ones who are actually going to carry out the plan. The employees will do that. So from the beginning, a clear articulation of the plan enterprise-wise is essential. The employees need to become stakeholders in the new vision and understand why it is being done. In addition, a digital transformation often involves a built-in ability to be more agile in the future. Employees need to move toward a view of the organization as an evolving entity, not a static operation.

After the strategic plan is described and broadly understood, then the tools for implementing it need to be provided in order to produce a successful outcome. In many cases creating these capabilities may require new or improved business processes, supported by additional software. Significant end user training may be needed. Leadership for change management will be needed not just at the C-level but at the departmental level. Again, the mental model should include the concept that change is the new norm.

One way to get people on board in this way is to sponsor “domain modeling sessions.”  These sessions help participants understand how information flows in their part of the organization impact other processes and departments. When this perspective is understood and concrete, it helps everyone achieve a shared vision for moving forward.

Not Sexy But It Must Be Done

“Change management is not the sexy part of the job,” he said, “but you still need to do it. You need to show people that the organization is progressing and succeeding. When people feel that they are making progress and their efforts are turning into something, the momentum keeps them focused.  Show how the pieces are working together, and communicate like crazy. As a leader, you have to be an evangelist. Make sure the senior team and stakeholders communicate so that people feel your passion and drive, and they will feed off of it. In two or three years, they will understand how important this change really is.”

It's difficult to maintain energy and focus (not to mention funding) over multi-year initiatives. The organization needs to see progress as the efforts unfold, which is why “quick wins” and metrics are so important. Even if the program is long-range, some payoff needs to be visible in the short term. This can be achieved by building in incremental milestones in which the most acute pain points are alleviated, while moving forward on the path toward the larger goals. 

Staying Motivated

For example, an enterprise knowledge management program could select a high value or high profile process and make the assets that support it more accessible. Metrics are important, to demonstrate progress against baselines. A data governance project could measure data fill, data quality, or data usage as interim measures, on the way to completing a full governance program. This information could then be communicated back to employees.

Website product hierarchies can start with high-volume or high-profit categories to show improvements in usability or conversions that can then be extrapolated. At the same time, it is essential for these fixes to be built on a foundation that can later support other initiatives. In order for this type of change to occur, stakeholders will need to be convinced that identifying a product category and improving tagging of product attributes (for example) is a productive activity and is directly tied to improved business outcomes.

I had another conversation with the CIO of an insurance company who pointed out the lack of foundational efforts as a key deficiency in many enterprise programs. He said, “Most organizations don’t have the patience to do things correctly from the perspective of foundational capabilities – like enterprise architectures that save time and money down the road. They do things to satisfy the immediate needs of their projects and budget without considering the larger picture across multiple business units and processes.” Or, as a colleague says, “there’s no budget for the common good.”

In digital transformation programs, “budgeting for the common good” has to be the norm. Understanding information flows across the customer lifecycle will reveal opportunities to solve other problems that may not be on the immediate horizon or part of the immediate program. Those projects can tag along with the larger vision. The more people who understand the customer lifecycle, the more they can contribute with innovative solutions.  The question is really how to focus organizational time, attention, and resources at the correct level to achieve meaningful progress so that people don’t lose interest, but not focus entirely on short-term objectives and sacrifice the longer term vision in the process.

Anything Worth Doing Is Hard

This delicate balancing act is not easy to achieve. However, some organizations are doing so, and they are seeing significant competitive advantages as a result. Well thought out approaches can provide long-term roadmaps that align with future capabilities while achieving short-term wins along the way. Every digital transformation program has the potential to include short term wins along with a long-term vision.

The way to build this mix into your program is to take a holistic approach to understanding how silos need to communicate in the future and select some initiatives that meet interim milestones. Base the selection on the customer journey and stay focused on baseline metrics that can guide the organization along the path. An example might be to implement self-service for one aspect of the business in which customer service representatives are overburdened, and planning to roll it out to the whole enterprise at a future date. If metrics show a change such as improved customer service in terms of time to resolve a problem via self-service, or shorter wait times for a human representative when needed, and that information is communicated, then the idea of change can gain momentum.

Interested in learning if a domain modeling session makes sense for your organization?  Give us a shout.

Meet the Author
Seth Earley

Seth Earley is the Founder & CEO of Earley Information Science and the author of the award winning book The AI-Powered Enterprise: Harness the Power of Ontologies to Make Your Business Smarter, Faster, and More Profitable. An expert with 20+ years experience in Knowledge Strategy, Data and Information Architecture, Search-based Applications and Information Findability solutions. He has worked with a diverse roster of Fortune 1000 companies helping them to achieve higher levels of operating performance.