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This is the fourth and final installment of our “Process for Business Transformation” series. If you’ve not already read the earlier installments, our introductory article can be found here, and additional supporting articles on process and people can be found here and here.

As a quick summary, this series addresses the need to define and mature a process for designing and implementing business transformations. This need is driven by two observations; first, the business environment is increasingly dynamic, which means transformation is now a key business competency; and second, a significant number of transformation projects fail to meet initial expectations or even fail entirely. Every transformation project needs to begin with a clear understanding of the activities required to run the business and add value. In other words, “what we need to do.” After establishing the activity demand, our focus shifts to satisfying that demand in an efficient way. This second step answers the key question, “who does what?” Without clear directives on goals and role definition, there is no way forward. This final article continues to explore the best avenues for satisfying activity demands, bringing us to digital transformation.

Digital systems have various purposes in business transformation. For the sake of simplicity, we find it most useful to think of systems as supporting activity completion in the following ways:

1. Making activities easier to complete (access and communication of information)
   
2. As a tool for completing activities
   
3. Performing activities

Through one of these three uses, our goal is to drive performance in an organization by reducing the time to complete any given activity, improve the consistency of an output, or lower the cost of “labor” required to perform the activity.

In the next process steps, we will cover some key considerations and linkages to the larger Business Transformation process for Digital tool design and implementation.

Step 9. Review and Prioritize Technology Gaps

Like any business decision, the first step in this process is to review and prioritize objectives. In this case we ask, what technology gaps are imposing the most significant limit to business performance? Systems and digital tools serve a variety of purposes in the modern business environment. Much focus has been on purely digital or digitally enhanced solution offerings, instead, in this article we will focus on the internal digital environment.

What exactly defines a technology gap? From an internal perspective, system gaps typically take place in the form of data gathering, management, processing, and accessibility. Using the activity assessment performed at the beginning of the transformation process, each activity should be evaluated if a gap exists in one or more of the system gap classifications. This classification of gaps will help to identify the form of the digital solution that will provide the greatest benefit. Classification of gaps and accompanying solutions should be performed in parallel with the activity review steps, as the two are closely linked. We use data gathered in the initial steps of the transformation to understand the following aspects of a perceived technology gap:

1. What activities will be impacted?
   
2. Who needs to provide inputs and have access to the system and activity outputs?
   
3. How will a digital solution improve the performance of the activity?
   
4. What is the cost to the organization to perform those activities?
   
5. What is the value proposition to digitize an activity?
   

Answering these questions will provide direction as to which activities will benefit most from digitization and what exact form of digital improvement is required to make the change.

Common Pitfalls

Properly identifying the system gaps to desired future capabilities is often a source of failure for the digital dimension of business transformations. Activities are central to transformation initiatives and gaps must be linked back to activities; this is the most common misstep in designing a digital transformation. Systems support processes, not the other way around. Not taking this step will, at best, result in a suboptimal outcome from implementation and, at worst, the designed solution hurts the business by not supporting business processes. Leadership will also need to sift through what will undoubtedly be a mountain of technology suggestions from within the organization. IT systems are faceless and as a result often become a target for frustration related to business performance. Leadership must take the time to perform a thorough investigation of root causes in the activity assessment phase leading into the classification of system gaps. This means not only gathering qualitative feedback, but also verifying these perceptions using quantitative data and analysis.

Best Practices

Successful digital transformations need to begin with the vision for the future. Without this defined at the outset, it is impossible to define technology gaps. Setting goals for the future state of the business is imperative. While the business environment is becoming exceedingly dynamic, it is important that infrastructure is in place to support the business long after the initial transformation project is complete. Like the benefit provided by activity and role assessments, it pays dividends in the long run to maintain key discussion and decision points from this part of the process for future reference. Identifying gaps is not an activity that should be taken lightly, as it will set the direction for subsequent steps. Without a clear understanding of these gaps, the organization can find itself investing in needless solutions while failing to address the actual root obstacles to future operational goals.

Step 10. Select Solutions

Identifying and prioritizing technology gaps from the prior step of the process reveals the best way to fill those gaps. For each type of gap, any number of potential solutions exist. Technology gaps typically fall in an area of the data lifecycle: gathering, management, processing, and accessibility. Gathering data can be simultaneously the simplest and most difficult gap to fill, depending on whether the data is internal or external, quantitative or qualitative, etc. For internal transaction level data, closing a gap can be as simple as adding a field or making a connection to achieve a quick form of automation. For example, transferring customer data from an eCRM to an ERP transaction is one common solution. Closing gaps for internal and external non-transactional data can be more complex, but solutions do exist to gather data inputs. These solutions include task tracking/tracing and web traffic data analysis among others.

For data management, the most common gap is in linking multiple data sources to identify new insights. For most organizations, their primary data source has already been sliced, diced and analyzed from every possible angle. As a result, multi-data source analytics are required to find new insights. Organizations struggle to achieve this through a lack of connectivity between data sets. This is a common gap. Traditional systems were designed to provide base level data processing and are largely native to any new ERP system. Gaps tend to be found when organizations seek to perform more advanced analytics.

No shortage of applications exists to perform advanced data processing and analytics, from integrated and API linked applications to internally developed applications and open-source code (Python, R, TensorFlow). Ultimately though, the success of advanced analysis comes more from an organization’s data management and accessibility than from the application itself. Finally, but by far the most critical gap in solution selection, is regarding accessibility. Too often we see well designed systems go underutilized because they are difficult to use or lack access to the right information. No matter how intelligently a digital solution is configured, if the user interface is poor, the solution will not be used by the organization and the gaps intended to be closed will remain open.

Common Pitfalls

A common mistake that leads to an incorrect solution selection is that of not defining data sources and uses prior to selecting a solution. Organizations have access to and can collect a near unfathomable amount of data about their business. In this process, they run the risk of losing the forest for the trees. By identifying data sources and how data will be used prior to implementing a digital solution, an organization will not only be saved from Big Data becoming Big Analysis but will also be pointed to the solution that is really required to close the gap.

When it comes to data management, the most common mistake is with regards to unregulated data capture. After the bulk of effort spent in designing an integrated system infrastructure, it is easy to overlook data entry controls and, while most systems and applications have personnel access controls, we have noticed a lack of data entry controls in many cases. Any solution that is selected should support strong data entry input controls, or at the very least help identify outliers, exceptions, or erroneous entries.

Automation and advanced analytics are some of the hottest topics in business transformation. We have seen this hype result in ambitious automation and advanced analytics goals, and investment dollars follow. But desire alone is not enough to provide the environment required to make these goals pay dividends to the organization. Returns from automation depend on many variables, but among the most critical are degree of activity standardization, volume of activity automated, and the selection of an appropriate level of automation. Automation can range from simple to intelligent to cognitive and selecting a level of automation that fits the constraints of the environment and is appropriate for the activity being automated will reduce costs and increase the return from the project.

In a similar vein, advanced analytics require a mature data management environment to provide value. We have found over and over when applying our own advanced analytics for clients we eventually spend 80% of our efforts cleaning data. This is not sustainable for a tool to provide value. Before investing in advanced analytics, an organization is far better off ensuring they have a data management strategy in place to support these tools.

Finally, in selecting a solution, an organization should select an option that is easily accessible to the organization and, at the very minimum, has an adaptable user interface. While all other aspects of a particular solution may support the business goals of gathering, managing and processing data, if the solution does not have a front interface, then the frustration of using the tool will outweigh its benefit.

Best Practices

The combination of solutions available to modern business leaders is near limitless. Successful solution selection follows a defined decision process. This process forces leadership teams to identify and score each option’s ability to close the perceived technology and digital gaps. For the purpose of proper evaluation, systems should be reviewed based on stock capabilities. Customizations may be necessary to achieve a desired outcome, but a balance needs to be struck between the intended benefits and the future cost of maintaining and testing customized capabilities. Solution selection should also be consolidated to a team with both visibility and authority across the entire business. Opening solution selection at lower levels inevitably leads to local optimization, in which each business unit has a separate solution. Identifying gaps and potential solutions is the time for democracy in the selection process. This situation leads to analysis and data access nightmares at higher levels in the organization.

Step 11. Blueprint Transformation

Similarly to how a good blueprint is vital for building a home that is completed in accordance with planned cost, time, and resources, a business transformation requires a clear blueprint. A well laid out blueprint becomes the centerpiece that ties the why, what, and how together by becoming the communication tool for the organization.

The blueprint must be simple enough to be understood by every employee, not just senior leadership, yet it should be detailed enough to serve as a call to action for the organization in order to support the transformation team. Depending on organizational complexity, a good blueprint may require several tiers that are linked together to create a cohesive story.

A good blueprint is the most effective change management tool that an organization’s management can have to ensure the success of any given business transformation.

Common Pitfalls

The most common pitfall here is blueprint that does not speak the language of the frontline staff. While transformations are designed at the corporate level, they are often executed by staff on the ground floor. It is the primary responsibility of the business leaders to ensure that blueprint is not ambiguous and is commonly understood to secure success. Rather than jamming too much information onto a single page or into a single document, a gradual build based on describing objectives, desired outcomes, and necessary behavioral changes in order to reach those goals is helpful to all stakeholders within an organization.

Well laid out blueprints fail to make an impact unless the leadership makes concerted efforts to take it to the organization through repeated communications and at a level that can be understood by everyone within the organization. The success of a transformation depends on actions taken from the C-suite and beyond. A passive posting on a corporate website or an organization wide e-mail is ineffectual and will not bring about lasting change.

Like any building blueprint, changes may be required once the build begins and knowledge is gained. Practicality and flexibility are required elements of success. An overly rigid business transformation blueprint can even stifle constructive contributions. Transformation sponsors must steer practical change requests in the most efficient manner to ensure a favorable outcome for the organization’s plan.

Best Practices

Good blueprints are accompanied by Frequently Asked Questions (FAQs). This improves buy-in and avoids rumors. This tool avoids the of sapping or misdirecting of organizational energy by preventing ambiguity and uncertainty.

Good blueprints are drafted in coordination with change and communication management plans. The more communication channels and mediums that leadership can deploy to propagate the blueprint, the better. This may include creating a dedicated web portal, informative e-mails, and explanatory videos in local languages that employees can consume at their own pace, followed by interactive delivery sessions. For example, in-person townhalls, brown bag meetings, and virtual forums are all critical success factors. We recommend avoiding live chats to avoid reactionary feedback, as these situations can be difficult to manage in a positive and thoughtful way.

Transformation efforts succeed when the blueprint becomes a safe environment for two-way communication versus a one-way mouthpiece for the leadership. Getting employee feedback on the blueprint and acknowledging this feedback through blogs and other forms of outreach is a productive approach that improves the success of the transformation in the implementation phase and keeps all stakeholders at ease.

Conclusion

As the business environment becomes increasingly dynamic, the ability for organizations to transform and adapt to new environments will need to become a core competency. Redefining strategies, products, and key differentiators will require business operations to keep pace. Historically, transformations have been performed as one-off initiatives to be completed and define the business into the coming decade. In today’s environment it is not only difficult, but also potentially dangerous to attempt to define the trajectory of a business more than a few years into the future with any degree of certainty.

Our series, “A Process for Business Transformation,” is intended to help organizations define a way to consistently transform as the need to do so emerges. This process begins by evaluating activities as those that add value, add low value, or add no value. Once the new activity landscape has been defined, the next step is to identify who will perform the work required. To optimize the benefit to the organization, determining who performs work starts by combining activities into defined roles, defining the scope of activities, and finally managing the relationship between role and scope to define a position in the organizational structure. Finally, digital tools and systems are applied to activities and people to lower the cost of performing activities and generate better business outputs. With the application of this process, the business will have decisions with a much broader range of variables to consider. While this series cannot begin to opine on each, what we can say is this: the start of a consistent, high quality output is process and this process’ output is transformation.

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