Digital transformation can seem like such a big undertaking that it's hard to know what to focus on amidst all the shiny objects and distractors clamoring for your attention.
Here are some numbers that offer a clue.
According to Flexera's 2022 survey of IT executives around the world on the state of tech spending, 74% cited digital transformation as a top priority for technology initiatives, just ahead of cybersecurity (73%) and cloud migration (65%).
So far, so good. We've discussed in previous articles how digital transformation is essential to survive, grow and thrive in the current era.
The same study also noted that:
82% said that not enough good quality data was one of their biggest challenges in decision-making, with 54% calling it "very much a challenge."
So, as you're setting out on this journey, if you're looking for a North Star to guide you, let it be this: data quality.
You can't make good decisions based on bad data. Bad data leads to bad analysis, incorrect decisions and poor outcomes. And if you're in a place where your data is siloed, inaccessible to those who need it, incomplete or incorrect, you're working at a disadvantage.
In fact, one very apt analogy for digital transformation is that it's a little like redoing your house. You can make piecemeal changes like putting up new paneling, installing new lighting or even rewiring the electricity. But if you don't have a quality foundation in your house to build it up from — what the house flippers call "good bones" — then you're going to be hindered in your efforts. And when you try to make transformative changes to the structure itself, there's a disturbing possibility that the whole thing might cave in on you.
When it comes to digital transformation, a strong foundation of solid data is essential. For digital initiatives, good data means good bones.
Mapping Your Data Journey
Most organizations recognized the importance of data, but figuring out how to successfully become a data-driven company is easier said than done.
A successful data journey has four key elements:
- Determine your roadmap. You'll need to start with an honest and thorough assessment of where your company currently is in terms of digital maturity, and what your needs are for the future.
The scale and complexity of digital transformation will vary with the size and mission of the organization, and you don't have to take on more than you're ready for. With careful planning now, you can create the kind of good bones that allow you to add more complexity as you go, gradually and only when it's needed.
That said, most organizations will be looking at getting to a place where cloud-based analytics tools and machine learning can help with statistical analysis, forecasting and optimization.
And of course, getting all of your data into a modern ERP system so you have a single source of truth is a prerequisite for making sure your digital initiatives live up to their potential.2. Capture Data, and Build Processes and Procedures
This phase of the journey is about how you handle all of the data your organization has access to, which may be coming from many different sources and directions. It's time to take a look at how you collect data, pre-process it and store it.
A related concept that should come into play here is governance. This refers to the processes, policies and technologies needed to manage data and ensure the availability, usability, consistency, integrity and security of the data. If you don’t manage data proactively, you can't be sure you're delivering reliable information to the front lines of your organization.
It's important to make sure everyone within the organization is playing by the same rules, following the same policies and rowing in the same direction — otherwise you wind up with conflicting approaches, missed opportunities, wasted resources and security risks.
According to a 2019 study conducted by North Carolina State, “siloed data, a lack of standards and a lack of skills remain the most significant challenges for improving data governance.”
3. Make Data Accessible to Business Users
Your data does you no good if it's not available to the team members who need it, as well as those who might be able to open new doors if they had access to it. Democratizing your data means allowing business users from every corner of the organization, from procurement to sales and marketing, to use that data in the process of achieving your business goals.
Getting your data out of siloes also means it can be analyzed by data science tools to yield powerful insights that can be turned to your advantage.
4. Change Company Culture for Full Adoption
You won't achieve the dream of a digitally transformed organization without a team that fully embraces a data-driven culture and commits to using digital tools intelligently and effectively.
Creating that buy-in means training your team to understand how to use these tools. But it also means understanding their needs well enough that you can show them how embracing technology will ease their pain points and empower them to accomplish more in new and exciting ways.
Data is your organization's most valuable asset. But its value is directly proportional to how well managed it is. Dirty, disparate, disorganized data will hold you back. Clean, consistent and standardized data will propel you forward.
Putting a high priority on data quality allows everyone to trust the reports they're seeing and make sound decisions based on full and accurate information.
This brings us back to the concept of governance and why it's important — to help guard against the factors that can compromise the quality of your data. Some of these preventable bugaboos include:
- Inconsistent data-entry standards
- Poor data integration
- Not keeping data up to date
And of course, human error is hard to eliminate entirely. But having strong governance in place helps mitigate the damage it can do.
Here's a three-step process for getting a handle on the situation:
- Start by declaring your intention to achieve good data governance. This is something every organization has to grapple with on some level; there's no shame in admitting you've got room for improvement, and everything to gain from tackling it head on.
- Get help from an outside source. Trying to solve all the issues on your own can be like trying to spot your own typos. An outside set of eyes can often surface the issues you miss because you take them for granted and propose new approaches. And a trusted partner like Columbus with deep expertise and experience in this area can make lighter work of an otherwise daunting task.
- Make sure that management takes ownership of your data and how it's handled. It's not enough to leave it in the hands of IT and let them deal with it. You need to understand how your data is being managed so you can both participate in decision-making and find ways to assist them with the challenges they face.
Developing Your Data Strategy
Start by focusing on your data strategy goals:
- To build a single enterprise destination
- To connect data from disparate silos
- To power responsible data democratization
- To drive efficiency gains
- To meet or exceed compliance and regulatory requirements
Remember that the value of data depends on the number of people who can connect to and utilize it in meaningful ways. To evolve from unit-level intelligence to a more all-inclusive and connected enterprise intelligence, we need to invest in the elements of the Enterprise Data Strategy.
Investments in these foundational elements are usually iterative, and each builds on the last.
- The data foundation provides secure, high-quality discoverable data.
- Scorecards measure the impact of that data.
- Analytics extract insights from it.
- Machine learning (ML) and AI transform it into intelligent experiences.
All these elements are linked by governance services designed to foster the responsible democratization of access to and use of data.
Ultimately, the foundation you want to put in place looks like this:
- Trusted data services to ensure data quality, security, compliance and governance
- A single source of truth where connected enterprise data is collected, shaped into trusted forms, secured, made accessible and conformed to applicable governance controls
- Connected data products, including unified master data, data from disparate sources conformed to common enterprise data models and entity hierarchies
- Modern systems and tools to build and operate data products with sufficient guardrails to prevent improper data proliferation to edge systems and application
- A unified data catalog for democratized access to the data and data products that teams require to power their own digital transformation
With those good bones in place, you'll have a solid base to build from as you pursue your digital transformation and the new achievements it makes possible.
Want to learn more about how Columbus can help your company plan and execute a successful strategy for digital transformation? Get in touch with us today.