Digital transformation is hardly a new concept. With 91% of businesses engaged in some form of digital initiative, it’s widely understood that upgrading technology stacks is essential to remain competitive in today’s landscape. 

The problem, however, is how many organizations begin the digital transformation process only for it to fail—84%, in fact. While there’s a variety of reasons behind failure, here at Kenway Consulting, we’ve been helping organizations conduct successful digital transformations for decades. 

As an organization begins to digitally transform its business processes and data into more actionable states of being, roadblocks and unforeseen challenges tend to arise. There are a myriad of reasons organizations can struggle to achieve a successful digital transformation, but there are two that stick out:

1. 1. Fragmented, disjointed data processes were in place from the beginning of a company’s transformation
   2. Strategy for the transformation was an afterthought, causing major disruptions as organizations underwent a faulty transformation 

In this blog, we will focus on a vital aspect of digital transformations: the evolution of data processes. A data process transformation is one of the most difficult, yet critical, parts of a digital transformation journey—and having poor data quality comes with a major cost for an organization. Here, we will share key insights we’ve learned throughout our years of experience in helping organizations with transforming their data processes and developing a sound strategy so that they may ultimately reap the benefits rather than fail.

What is Digital Transformation?

Digital transformation is the process of leveraging technology, organizational processes and people to develop or enhance existing business models and revenue streams. 

One of the most popular types of digital transformation is data process transformation, mainly consisting of the movement of data to the cloud. Moving data from legacy systems to the cloud is typically unique to each use case and factors in many intricacies that need to be strategized and prepared for ahead of migration. 

When undergoing data process transformation, there are several main considerations for success. Below are a handful of influential steps when undergoing a transformation of a company’s data processes:

1. 1. 1. Data Discovery: The identification and understanding of the data being transferred from the legacy system to the new platform. This step is essential in an organization’s comprehension of the data that is being moved and why it is important to current business processes to ensure it is leveraged correctly
      2. Data Governance: The collection of clearly defined policies, procedures, standards, processes, roles, and responsibilities that ensure the effective and efficient use of data in enabling an organization to achieve its goals. At this stage, business and data quality rules are defined 
      3. Data Migration: The design and development of data migration and transformation process to take the data from its current format within the present state solution, and transform it to fit the structure of the future solution
      4. Data Review & Correction: Data steward review and correction of data issues resulting from the data quality rules applied during the data migration and transformation process
      5. Ongoing Data Assessment: The development of an ongoing process for new scenarios and escalation to the Data Governance Committee to confirm the appropriate application of business rules 

It’s common for an organization to run into disruptions during a data process transformation—expecting the unexpected is crucial, but also comes with its own set of challenges. As teams navigate how to best approach the evolution of their data processes, seeking external guidance from a group of experts could be the difference between a company’s success or failure. Hiring an expert team of corporate technology consultants to ensure digital transformation success helps organizations put their best foot forward when undergoing such an important process.

In a recent case study, Kenway Consulting defined and implemented Data Transformation to support an improved future state for an industry-leading healthcare solutions provider. Read the full data process transformation case study here. 

Benefits of Digital Transformation

Whether consumer habits are shifting or a global pandemic occurs, undergoing a digital transformation, specifically a data process transformation, can quickly become a priority to fit current and upcoming business needs. While there are many, the benefits of digital transformation include more accurate forecasting of market trends, improving internal processes, and making more data-driven decisions. Here are a few more:

1. Keeps organizations competitive

Utilization of Business Intelligence (BI) tools to functionally organize data provides companies with insight into everyday activities, allowing leaders to identify more productive operations methods, price risks, and forecast market patterns ahead of their competitors. This kind of visibility into a company’s data pays off as data-driven businesses are 58% more likely to beat revenue goals than those who do not prioritize optimizing their data. 

Data-centric companies have data easily accessible and organized in a way that supports business objectives, further encouraging employees to be able to deliver the best possible product/service to the end-user. This is why data-driven companies are 23 times more likely to acquire customers than their peers. If the data being used to make big-picture decisions is easy to gather and analyze, businesses can be better equipped to deliver the best possible product for their customers.

2. Improved data quality

In our experience, we’ve observed that seamlessly undergoing a data process transformation is a major hurdle for our clients—specifically when assessing a business’s data quality. 

Data quality issues can come in many forms, such as misplaced data, human error, and formatting inconsistencies. In fact, 41% of companies say inconsistent data across their tech stack is their biggest challenge. And as data grows over the years, it becomes harder to draw correlations between data sets, resulting in less effective analytics and insights, as well as a diminished business-user trust. 

Through the data transformation process, organizations have the opportunity to clean their data and implement more resilient data governance frameworks that ensure accuracy and establish a single source of truth. 

3. Increased data usage

Companies are collecting an overabundance of data on a daily basis, leaving a majority of it under-utilized. In fact, 60-73% of all organizational data is never analyzed for Business Intelligence purposes. As a result, organizations are paying the price in the form of missed revenue opportunities, lower efficiency, and productivity/quality issues. With a Business Intelligence tool, organizational leaders and employees can use data to improve efficiencies and make more informed decisions. In fact, 74% of business leaders expect long-term gains in productivity by making data insights available to frontline employees.

Key Insights for Ensuring Digital Transformation Success

While there are many benefits of digital transformation that pay off in the long term, there are also a variety of risks that are important to mitigate upfront. The biggest risk of all is the high probability of failure with 70% of all major business transformations being unsuccessful.

As organizations discuss data process transformations and run risk assessments, here are some key considerations to have when developing a migration strategy:  

1. Have a plan to ensure internal adoption

Only 37.8% of organizations report having a data-driven organization. Many organizations’ internal team members will face a massive learning curve when learning how to properly manage, store and utilize data to make decisions. 

If a company’s team does not embrace the new technology, their digital transformation will result in a failure to adopt it. To help employees not only accept, but fully embrace new data processes, a change management strategy is necessary. Successful change management ensures:

• • • Risks are evaluated prior to digital transformation
    • Organizations have a plan for rolling out the new processes and technologies to the entire organization 
    • Team members are communicated with clearly and trained appropriately
    • Companies have a sustainment plan to ensure the transformation is fully adopted and embraced by employees

Companies that invested in a rigorous change management approach reported a 79% success rate—three times the average for all other initiatives. 

2. Evaluate all potential costs 

The average digital transformation budget for mid-large scale companies is $14 million. Because of this, the cost of investing in data process transformation is a common concern for business leaders. But the truth is, while transformation is not cheap, the long-term savings far outweigh the upfront costs. In fact, data-driven companies are 162% more likely to outperform laggards.

3. Assess your resources

From lack of data process transformation expertise to the absence of trained staff to manage the change, there are numerous ways an organization can experience a shortage of adequate resources when developing and rolling out new data processes. 

This lack of expertise can lead to several roadblocks when refining data processes: unclear goals, poor planning, and little to no risk assessment are a few that can make an organization’s data transformation collapse. Not to mention, companies can’t stop running just because they are transforming their data processes—the show must go on. Hiring a corporate consultant can help provide the resources a company needs to ensure its digital transformation is a success. Plus, while the consultants work as an extension of a company’s team, employees can better use their time to focus on the day-to-day. 

Additionally, data isn’t the only process that needs to be transformed—team structures need to evolve as well. Oftentimes, the maintenance required to support an ongoing data process transformation is typically overlooked. Organizations need to have a team in place to maintain new data processes once they’ve been integrated. It’s critical for teams to be adequately trained to actively embrace the technology and for new hires to be made to fill the gaps necessary to ensure successful adoption. 

Ace Your Digital Transformation with a Partner You Can Trust

Data process transformation is no longer a want for organizations hoping to remain competitive, it’s a requirement. With so many risks that go into the digital transformation process, hiring a management and technology consulting company that has proven experience in helping organizations with data transformation can help avoid bottlenecks and accelerate success. 

At Kenway Consulting, we lead businesses to victory by integrating our guiding principles into everything we do. These guiding principles lead how we approach our interactions with our consultants, clients, recruits, and those with whom we network. At Kenway Consulting, we believe that the means to success is actually more important than success itself. Our principles focus on the following themes: 

1. 1. 1. Treat each individual with respect
      2. Integrity
      3. Means over outcomes
      4. Communication
      5. Entrepreneurial spirit & tenacity
      6. Value & quality

We’ve been helping organizations successfully implement modern data platforms for nearly two decades. Our team specializes in helping organizations build their IT strategy and build the data architecture & design required to support it. Connect with us to learn about how we can help with your data process transformation needs.