DON’T LET TECH DEBT STAND IN THE WAY OF DATA-DRIVEN INSIGHT

Technical debt can put organizations in a headlock, both in the short and long term. Almost nothing casts a bigger, scarier shadow for decision makers — the perception of the time and cost necessary to overcome tech debt looms large, keeping entire companies frozen in fear.

This burden makes it difficult to efficiently extract insights from data. It’s a recipe for stifled growth.

We’re here with a message of hope: you don’t have to dive into a resource-intensive, five-year transformation project in order to manage your technical debt and realize your data potential. You have other options, and it all comes down to prioritization.

What is tech debt?

Technical debt is often defined as the cost incurred when you repeatedly choose short-term solutions rather than doing the (larger, more expensive) work of tackling the big-picture causes of your problems.

But let’s look at the issue through a different lens: what is the nature of technical debt?

Because new solutions are built and deployed every day, all organizations incur tech debt, to some degree, with every system and process implementation decision they make. Even if you implement a new, innovative solution today, there will be a better one available tomorrow. In this scenario, you will still incur tech debt — just less than an organization that makes no updates.

Too many organizations think of tech debt as a problem that can be permanently solved. In reality, it’s a constant that’s renewed continuously by change and growth, and trying to “solve” it completely is a futile pursuit.

While you can’t make tech debt vanish into thin air, you can certainly make it more manageable. If you focus on managing its impacts in an ongoing way, you can deflate its looming, monstrous reputation and get to work on making meaningful improvements in the here and now.

Is tech debt destroying your data-driven dreams?

Analytics bottlenecks are a common issue related to tech debt. Silos slow down the analytics process; if only one person knows where a spreadsheet is and how to extract meaningful data from it, they become the bottleneck.

With each short-term fix and siloed process, data becomes harder to manage, access, and analyze. In turn, drawing insights from that data requires more time and effort, the insights become less timely and less reliable, and informed decision making becomes more challenging.

In other words, tech debt has a way of draining value from data — and the longer you let that debt accrue, the more value you’re losing. Using a prioritized approach to managing tech debt can help you cover more ground right out of the gate, so you don’t lose any more value than you have to.

One way to apply this prioritized approach is with backlog grooming, the periodic process of reviewing and prioritizing backlog tasks (and removing unnecessary or outdated tasks).

How do you prioritize what areas to address?

There is a lot of information available on how to tackle tech debt. Unfortunately, most of it is theoretical. While the abstract stuff can be valuable, if you’re looking for a practical way forward, you need to bring your considerations back down to earth and fold in the business perspective to create a technical debt prioritization plan.

You probably have a lot of tools at your disposal, internally and externally, and resources to leverage. Take a look at what you need to have happen — not theoretically (e.g. eliminating all technical debt by some point in the future) — but actually.

For example, The Gunter Group recently worked with a retail automotive company that was struggling with data debt. It was impacting every area of their business, including employee satisfaction, customer satisfaction, and profit margin. They needed a new approach, but with such a vast problem, it was difficult for them to know where to start.

We worked with multiple teams within the company, including manufacturing, HR, marketing, and technology innovation to create a prioritization plan. High priority initiatives included redefining company-wide KPIs, designing and implementing machine learning algorithms, and improving data literacy across departments.

Though they still have a long way to go on their data maturity journey, this company was able to start making changes where it mattered most, rather than remaining paralyzed by the challenge ahead.

How we work with clients to tackle tech debt

Remediating data-related tech debt requires far more than just technical skills — it requires asking the right questions, gaining a holistic understanding of your organization’s business goals (as well as how they may vary across different departments), and creating a dialogue to explore possible solutions.

Each of these components requires a tremendous amount of time, which internal teams rarely have. In most cases, managing ongoing operational struggles takes priority over transformation, and team members don’t have the capacity to focus all their energy on addressing tech debt. Meanwhile, recruiting new team members is a time-consuming, resource-intensive process, and thanks to the tech talent shortage, it’s more challenging than ever.

Turning to outside help can get the data transformation ball rolling without overwhelming internal teams or opening a can of recruitment worms.

At The Gunter Group, we leverage a multidisciplinary approach (technology, people, strategy, and execution) that enables us to see the long-term big picture while solving the highest-priority problems in the short term.

Combined with our extensive technical capabilities, this approach allows our clients to chip away at their technical debt and reclaim the value of their data as quickly as possible — without the burden of hiring a new team.

Conclusion

Think about a meaningful, specific problem you’re facing right now that’s rooted in technical debt, and what you would be able to accomplish if this problem was being managed proactively.

If you set your sights on eliminating tech debt across your entire organization, you’ll likely get caught up in a complex tangle of issues — and that one major problem that’s holding you back now will still be holding you back in six months.

To accelerate your progress, identify your most pressing issues, and reach out to expert help if you need it. With the right strategy and the right partner, you can mitigate tech debt and use your data to its fullest potential.

Is technical debt slowing you down? Discover how to improve your data infrastructure and decision making with workshops hosted by The Gunter Group.

WHY ISN’T YOUR DATA TRANSFORMATION PROGRAM TRANSFORMING ANYTHING?

It’s a familiar tale — you’ve embarked on a journey to transform the way your company uses data, but all you have to show for it is a lot of very ambitious documentation and hundreds of progress update meetings where time feels like it’s standing still.

Why isn’t your in-progress data transformation program producing tangible results? Here are three common reasons why your efforts might be failing to deliver:

1. Your approach isn’t incremental.

We recently wrote about data maturity models and how they can actually hinder data transformation if you don’t apply them correctly. To summarize, organizations tend to focus too much on the brass ring (reaching some proverbial data maturity nirvana) and not enough on the details (getting more value from data along the way).

Often, the goal is a total overhaul of how data is used from the top to bottom of the business, delivering unimaginable value to everyone, everywhere — an ambitious transformation that will take years to achieve. Even if you’ve had a few updates and helpful process changes along the way, most of the value remains locked behind the “project completion” door.

What does that mean for those who are trying to get some incremental improvement and use data more effectively in the near term? It means they have to just sit tight and wait for the big reveal — otherwise, they’ll be doing work that’s not aligned with the broader strategy.

It’s important to consider the folks in your organization who use data to complete everyday tasks, and how you can make their jobs easier, not harder, during the data transformation process.

2. Technical debt is handcuffing you.

Individual innovation can be a huge asset for an organization. You want people to take initiative, solve problems, and make it happen. But when it comes to managing data, all that individual problem solving can add up to huge technical debt, and make organization-wide data transformation efforts feel insurmountable.

When everyone has their own unique, siloed quick fixes and band-aid solutions, there’s no more unifying structure left to transform — so where do you even start? Think of the chaos you’d unleash by pulling at even one loose thread; mission-critical systems that were crudely patched together would come tumbling down.

As an additional challenge, there will always be responsibilities and processes that can’t be switched off while things are fine tuned. For example, if you’re using your existing data systems to calculate monthly commissions, that presents a huge barrier to making any meaningful changes — you can’t stop paying out commissions until changes are implemented, and it would be risky to just cross your fingers and hope that brand new systems produce accurate results in time for you to cut checks.

Getting out from under technical debt isn’t impossible — it just requires a lot of effort. It’s also infinitely easier to achieve with the right combination of planning, skill, and resources, which is why many companies partner with firms that specialize in tackling technical debt.

It’s also important to remember that tech debt isn’t something you can escape completely, but a challenge that needs to be continually addressed. Good solution design assumes that today’s new solution is tomorrow’s tech debt, everything is eventually deprecated, and all solutions incur maintenance and upkeep. Finding the balance between standardization and innovation is important, as too much of either can be stifling.

3. You don’t have the right people.

Pulling off a successful data transformation project takes a lot of skill sets (strategic planning, project management, change management, ETL development, data science, etc.), and it’s highly unlikely that you’re going to find a single person who can do them all well. It’s also unrealistic to expect your current staff to sustain day-to-day operations and magically find the time to make changes. In 99% of cases, you’ll need outside help.

Trying to build an in-house team is difficult, especially in the midst of a data analytics talent shortage. Planning and recruiting for a team can take anywhere from six months to a year, plus the time it takes to get everyone up and running. If your organizational culture (or even just a particular decision maker) is change-resistant, this process can take even longer — and feel like pulling teeth.

Technical leaders often have to spend a large amount of time jockeying for resources and pitching projects. You may have to argue and advocate for three months to hire one person that was needed to solve a problem three months ago. By the time you get a decision, you’re going through the same cycle with a different problem.

It’s easy to see how years can go by with little to no progress.

This is another situation where it can be helpful to work with a data transformation partner, which gives you access to highly skilled, experienced people, without the pressure or long timeline of trying to build an in-house team.

Conclusion

Our general advice for data transformation can be summed up in two words: don’t wait. Every day you remain stalled out, you acquire more technical debt, and your problems get more complex. You lose more business, you gain less on your competition, and your company loses value.

If you need to see real outcomes from a data transformation project, focus on incremental improvements, and find a partner who can help you overcome the challenges we’ve outlined here.

Above all, remember that data transformation isn’t a “project” that begins and ends. It’s a decision to become a data-oriented organization — and it takes continuous effort and agility.

Not seeing results from your data transformation initiatives? Discover how to improve your data infrastructure and decision making during our upcoming Data Maturity workshop on December 15th at 11:30am Pacific Time.

TGG PARTNER Q&A:
2022 CONSULTING MAGAZINE BEST FIRMS TO WORK FOR

This fall The Gunter Group was recognized as a “Best Small Firm to Work For” by Consulting Magazine for the fourth consecutive year. This marks the fourteenth workplace award that TGG has received in the last eight years.

We visited with TGG partner and head of TGG’s Nevada team, Tony Schweiss to hear more about the award and the significance of being honored nationally for The Gunter Group’s culture and workplace.

This is the fourth consecutive year TGG has been recognized as a Best Small Firm to Work For by Consulting Magazine. What does this consistency and recognition mean to the team?  

Tony: It’s a reflection of the amount of effort, energy and thought that we put into building a team that is aligning its culture to the work that we do and the outcomes we are trying to deliver as a team. It’s also a reflection of the caliber of people that we have on our team and the commitment our team has to do high quality work for our clients, to support each other, to collaborate and live out our Non-Negotiables, and hold ourselves accountable.   

The consistency, year-in and year-out is amazing and is incredibly exciting in terms of the ongoing acknowledgement of the effort we put into our culture on a yearly, monthly, weekly, daily basis and I think everyone on the team should be really proud of it.  

Not only has The Gunter Group’s team grown geographically over the past 24 months but the location of clients has been broadening as well. How does the Consulting Magazine honor validate these geographic developments? 

Tony: For us it is an essential priority that as we expand as a company and our footprint grows, that we stay culturally committed to what makes us a great team. The pursuit of excellence and the goal over time to create an engaged team no matter where they are, has been a driving requirement for us as we grow.  

To be recognized for this award four years in a row as we continue to grow geographically proves that it is possible to create highly engaging cultural value as we scale up as a firm. The recognition also validates the effort and resources we have dedicated to our team and organization, and serves as a celebration opportunity as well.

You are located in Nevada, what is it like for you to work with individuals across the country in different hubs/areas and how does TGG develop and maintain its strong organizational culture with geographically dispersed team members?

Tony: For me, I think it’s really exciting to work with team members from so many different areas.  Whether it’s the Denver area, Southern California, the Salt Lake City area, the East Coast, or the Pacific Northwest, the variety of experiences and perspectives that generate from a collection of unique locations is exciting to be a part of and see benefit our client partners. 

It’s been fun to experience but also presents a challenge: how do we maintain the value of our culture in a more virtual environment and dispersed geographies.  

Having been geographically removed from our main hub for a while now, the best version of an engaging team and workplace is one that is aligned in terms of its goals and mission as an organization. And for us it’s about helping our clients achieve their goals in a way that is better and faster than what they could have done on their own.  

I think it’s helped bring into focus opportunities for engagement with each other and how we’re doing our work but also how we are connecting as a team. It has forced us to try new things, evaluate quickly and then double down on methods that have really added to our cultural foundation across multiple geographies. As much as possible we continue to utilize not only virtual opportunities to engage with teammates but also encourage our local teammate hubs to spend time together in person and support that activity from an investment perspective.  

What are you most excited about for the TGG team and culture in the coming year?  

Tony: At the end of the day we’ve grown a lot over the last 3-4 years and we’ve grown purposefully so that our team has new and interesting opportunities in the future. As we grow we have to continue to be thoughtful about how we do our work internally, engage and connect with one another, how we collaborate, and how we deliver our work as a team. 

What I’m really excited about over the next year is to continue to mature how our employee experience presents itself and matures across geographies so we can ensure a great professional opportunity for our entire team regardless of where they are located. I think it’s the most crucial work we have in front of us but it will also be the most rewarding for our entire organization in the months and years to come.  

CHANGE MANAGEMENT:
THE PAST, PRESENT, AND TGG

People are hardwired to be cautious of change. However, in today’s rapidly-evolving business climate, organizations must find ways to support employees through inevitable changes. From operational restructuring to software implementations and everything in between, the field (and process) of change management is complex. 

With the numerous methods, techniques, and approaches to change management how does an organization identify and pinpoint the best path forward? 

It will help to briefly travel back in time to understand the roots of the formalized practices that flourish today and break down three foundational pillars of change management that organizations can utilize today.  

The Migration From Psychology To Business

Change management has roots in the study of human behavior. The intellectual beginnings trace to the early 1900’s, into the work of the anthropologist Arnold van Gennep. When looking at rites of passage in different cultures, Gennep began to notice common behaviors. 

Even though he was looking at a variety of different cultures, he noticed that there were three overall states that ran common in the experience of social change. The first state was a “pre-liminal” stage, where the coming change was acknowledged and prepared for by the community. 

The middle state was the “liminal” stage, which he defined as a threshold of ambiguity and disorientation. Change managers everywhere will chuckle at the accuracy of adjectives like “ambiguity” and “disorientation” when describing the liminality of change. 

The final state in a rite of passage was “post-liminal,” where the transition in status was recognized and normalized in the community. Across cultures and belief systems, Gennep was able to identify these common movements in the human experience of change. 

By the mid-20th century, when psychology began to blossom into a robust and complex discipline of study, Gennep’s three states gained popularity. In the 1940’s, Kurt Lewin became a pioneer in social and organizational psychology by turning his attention to understanding change.  Lewin borrowed from Gennep’s structure and described a three step process for change: unfreezing, changing, and refreezing.

There was some academic buzz from several sources in the years following Lewin’s work, but no substantial leap from psychology to business had yet been made. This changed in 1982, when a consultant at McKinsey named Julien Phillips published an article in the journal Human Resource Management. 

In his article, Phillips introduced a model for organizational change management specifically designed with businesses in mind. His model defines four steps that were intended to build momentum for change within an organization: creating a sense of concern, developing a specific commitment to change, pushing for major change, and reinforcing the new course of action. 

In the years following, change management took off. Books were published; articles became more frequent; new models were advanced. Businesses were in need of assistance with change, and consultants pursued thought leadership that would help address this need and grow their business. Peters, Waterman, Kotter, and dozens more developed robust philosophies and methods for change, and organizations bought in and helped the field to grow.

Today, there are as many models for change management as there are consulting organizations. Looking for a 4 step process? Try PDCA. Interested in 5 steps? Try ADKAR. How about a 6 step approach? Try Pulse. Need more? Try Kotter’s 8 Steps, or Prosci’s 9 Steps. There are symposiums and communities of practice such as Prosci and ACMP; and naturally a veritable cornucopia of certifications abound. Change management is so saturated with models and approaches that some even try to push “beyond change management.” 

100 Frameworks, 1 Idea

The Gunter Group does not subscribe to any one framework. Our clients are too unique for a single set of steps to be the answer. We proudly proclaim ourselves to be “methodologically agnostic,” much more interested in understanding the organization than blindly peddling a process that fails to fit the people it is meant to help. 

That is not to say that we don’t know the methods. Our consultants have expertise in Prosci and ADKAR; and we have a number of tangentially relevant certifications (Six Sigma, SAFe, PMP, and HCD to name a few); we attend local ACMP events. We do not, however, learn a method to become disciples. Rather, we expose ourselves to frameworks and study methodological vocabulary to leverage those aspects of the frameworks that might be helpful for our work. Our clients appreciate a tailored approach that is grounded in the best practices of 100 frameworks.

This approach to consulting reveals something obvious: all change management methods are basically the same. Decades of scholarship and praxis have not changed the core phases of change, and wisdom that dates back a century still lies at the heart of responsible change. There are 3 basic phases in change (before, during, and after), and every change management framework simply iterates on the approach taken within those three phases.

So what runs common throughout all change management? What activities should you keep in mind as you tailor the process to your specific organization? We’ll run through the basics below.

Step 1: Pre-Change

Change is coming. Perhaps it is a changing regulation, a new technology, an upcoming merger, or a poor quarterly report; whatever the reason, you see change on the horizon and understand that you will need to prepare for it. Though the various frameworks approach preparing for change differently, three key activities take place during pre-change: analysis, planning, and influencing.

Analysis comes first. Before you can plan for change, you have to understand the people and processes that will be impacted. Who will be your champions, sponsors, and resistors? Helpful tools for this phase include stakeholder matrices, current state and future state process maps, and change impact assessments. The change manager must also understand the change itself. Without a powerful grasp on the “why” that is driving the change, planning and execution will fall short. 

Planning comes next. Change management occurs somewhere between the intersection of strategy, people, and execution, and planning is the bridge that brings these three elements into alignment. This includes planning for the change itself, communication that will accompany the change, and the training that will make the change possible. 

Influencing should follow. ADKAR describes this as fostering awareness and desire. Prosci speaks of sponsors and champions. Other schools of thought suggest using concepts like vision or need. We have found that a cocktail of all these approaches is usually the best way forward.

Step 2: Change

You’ve spent time interviewing stakeholders, mapping processes, and planning training sessions; now it’s time to introduce the change. This is messy, confusing, and difficult for the people impacted so change managers often rely most heavily on a methodology in this phase. However, mid-change is where a generalist approach could be most advantageous, adapting to the ongoing needs of the situation. There are four activities that always occur in any well-managed change approach: communication, training, changing, and reinforcement.

The most important activity surrounding change is communication. This is where you lean heavily on the results of your analyses. You know who needs communication, what they need to hear, and how it will affect their work flow. Armed with this information, you can plan accordingly, communicating the upcoming movements to the right people, early and often.

Another essential activity is training. This often goes hand-in-hand with communication, and is best when designed from the viewpoint of those impacted. Recent developments of tools such as Human Centered Design help maximize the value of training.

At a certain point, the change will happen. Kotter recommends an approach of small-slicing the change to create short term wins, but often the change manager is not the one driving the project timeline. When it comes to go-lives, change managers serve a thousand roles. They become SME’s for elements of the change impact; they attempt to remove obstacles from stakeholders; they act as cheerleaders or bulldogs, whatever is called for in the moment. 

As change occurs, another important activity is reinforcement. A big part of this is engaging program or organizational-wide leadership to enforce the change. This activity truly begins in pre-change and extends through the end of post-change, but it becomes extremely important in the midst of the change. There are approaches coming out of organizational psychology that can be helpful here, such as Vroom’s Theory of Motivation, McClellan’s Theory of Three Needs, or McGregor’s Theory X and Theory Y.

Step 3: Post-Change

Follow-through is a must. As Gennep would say: the new status must be confirmed and the change must be reincorporated as the new norm. This is done a little differently in each framework, but necessary activities include reinforcement and reanalysis. 

As said above, reinforcement is heavily featured in post-change activities. The goal is longevity, driving the change through ongoing champions and dwindling resistance. Success is celebrated, momentum is reinforced, and improvements are consolidated. Through these activities, the new order is anchored in behavior.

One often-forgotten activity that takes place after the change occurs is reanalysis. Throughout this whole process, you’ve generated a mountain of information, from stakeholder input to process metrics. Current-state assessments performed before, during, and after the change are a great way to analyze that information, evaluating the effect of the change. 

Change management is the study of human behavior. Change is inevitably difficult for humans, yet change is unavoidable. As professionals in change management, we bring a people-centered approach to our work. We partner with clients to ensure employees and stakeholders understand, support, and adopt the desired change and it starts with a very critical element: listening.  We view our clients’ change as if it was our change, and their people, as if they were our people, with a foundation of respect. 

WHAT MAKES FOR AN IMPACTFUL CHANGE LEADER?

Impactful change leaders understand not only the holistic process of change but also the simple process of change, disruption, adaptation, and confirmation. They know the tools and the steps to help guide them in executing that change. 

Great change leaders think systematically. They’re fluent in the interwoven nature of change. For example, the reliance on, and the potential impact to, a long-term strategy: the new business opportunities that are presented, the operational impacts, the cost impacts and implications, and the efficiencies that could be gained from a change. 

The best change leaders are those who recognize that there’s an absolute, inextricable, undeniable criticality of engaging their people and their teams in bringing about change. No process, no strategy, no business model, no ROI, no calculations will matter if there’s an absence of engagement on the team.

When faced with challenging situations effective change leaders have the ability to:

1. Respond in a timely manner to a market force or operational inefficiency. 

2. Understand that change is a necessary process, and that it will happen again.

3. Learn from the challenges in front of their organization and learn from the change process they undertake.

4. Challenge the status quo and ask strategic unbiased questions with a focus on improvement and solutions.

5. See how change can and will impact their organization at an enterprise level.

6. Explore new processes and tools to support and scale change and improvement.

7. Communicate clearly and effectively to their team so that team members know the “why” behind the change and understand how their role fits into both the process and the outcome.

Large-scale change takes place across all industries with some of it intentional, and some of it unexpected. Regardless of the forcing mechanism, effective change leaders find ways to engage teams at a more human level, and in doing so choose engagement over exclusion and as a result prioritize organizational health and success.  

As professionals in change management, we bring a people-centered approach to our work. We partner with clients to ensure employees and stakeholders understand, support, and adopt the desired change and it starts with a very critical element: listening.  We view our clients’ change as if it was our change, and their people, as if they were our people, with a foundation of respect. 

A QUICK AND DIRTY GUIDE
TO DATA MATURITY

You’re probably familiar with the concept of data maturity — a measurement of how well an organization uses its data — and the maturity models that go along with it.

Understanding your current level of data maturity is the first step toward improving it. But the way you interpret and apply data maturity models might actually be hindering your success.

It’s tempting to look at a maturity model as a straightforward tiered system — your organization exists in one category, and your goal is to move up to the most mature category. But particularly for larger organizations, things aren’t so clear-cut. It’s common for different departments or business units to be at different maturity levels. Additionally, too many organizations get caught up in the long-term goal of data maturity and miss out on opportunities to create value at every maturity level.

In this article, we’ll go over the four categories we use to assess data maturity, give examples of challenges that arise in each category, and offer recommendations for driving more value at that level.

Before we get started, here’s a summary of each category for context:

Note: As you consider where you fall, it’s important to be realistic — think about where you are right now, not where you hope to be after completing a particular project. It’s also helpful to remember that it’s rare for an entire organization to exist within a single category. In most cases, different departments and teams will have different maturity levels.

Siloed

What it looks like:
Point-in-time data is manually exported from various applications and pulled into spreadsheets on an ad hoc basis. Team members compile and analyze data in their own individual workspaces (e.g. a spreadsheet only you have access to, or a platform that’s only used by one particular team).

Finding data requires some exploration — team members are not always sure where to look or who to ask for the data they need. They often end up emailing or asking around until they find someone who has what they’re looking for.

Example of a challenge:
You’re planning to hire people for a new team, and want to use a data-driven recruiting approach. You need access to key data about past recruiting efforts, like cost per hire, time to fill, recruiting yield ratios, and first-year attrition, so you send an email to HR requesting the information. HR then needs to take the time to locate and compile the data into a spreadsheet and send it to you.

Because you don’t have immediate access to the data you need, the recruiting process is already slowed down, and it will take longer to get your new team filled.

How to drive more value:
The importance of business process management can’t be overstated. For a process that will undoubtedly need to be repeated in the future (like looking at recruiting data), it’s important to start out with a deep, thorough understanding of the process itself. The first step to creating a repeatable environment is understanding what you want to repeat and why — then you can work on implementing more efficient processes.

Standardized

What it looks like:
Your organization has standard, scheduled operational reporting. You don’t have to go on an expedition every time you need data, because you know that you can find it in the most recent report (however, you’re still manually pulling data from that report). Even if you’re creating useful insights, they tend to stay with you — they’re not shared with other teams or business units.

Example of a challenge:
Each week, everyone in your department receives an email with an automated report that covers POS data. Most of the time, you don’t find anything in the report that’s actionable for you, so you sometimes don’t even open it.

When you do read it, you have to comb through tons of data to find anything relevant and manually extract it, which is time-consuming and inefficient. You complete analyses that are important to you within your own workspace, and the results aren’t usually shared outside of your immediate department.

How to drive more value:
Once you know where to find your data, determine what makes it actionable and relevant — and who needs to see it. As a starting point, ask yourself the following questions:

• What decisions do I need to make, and how can this data inform those decisions?
• What’s the ideal way for me to receive and view this data? 
• Who else would benefit from seeing this data?
• How can data be efficiently shared across departments so everyone has access to what they need?

Enterprised

What it looks like:
When a particular threshold that’s relevant to your job is met, you automatically receive the relevant information. Rather than getting a standardized report that may or may not contain information you care about, you get notified only when there is data pertinent to a decision you need to make or action you need to take — whether that data is related to a budget milestone, warehouse stock, page views, or something else.

Sources of data are aggregated, so when you need insights, you don’t have to manually combine and analyze data. However, the reporting is still fundamentally historical and often comes too late to help you make informed decisions.

Example of a challenge:
You’re responsible for mapping out an upcoming seasonal campaign and need sales data to inform your plan. Each week, you receive an automatic report containing data that helps you shape the campaign, but you have no way of looking forward in time — you’re stuck with a decision-making process that is reactive, not proactive.

How to drive more value:
With the right timing, data can be leveraged to achieve better outcomes (and predict possible future outcomes). Don’t just think about what data you need and where to find it — think about when it will have the biggest impact on decision-making, and how it can help you course correct before things get off track.

Actualized

What it looks like:
Your data is set up to model and predict future outcomes, perhaps using AI tools like predictive analytics and decision algorithms. Analysts and data scientists are an integral part of the business vision, and insights are created by the company (not requested by specific business leaders).

For many companies in this realm, the data model is inextricably linked with the product or service they provide. For example, platforms like Netflix and Spotify are rooted in predictive data analytics and the ability to make personalized recommendations to customers.

Very few companies reach this level of data maturity — and the reality is, not every company needs to. It takes continuous investment to maintain an Actualized data system and depending on the products and/or services you provide, it might not deliver enough ROI to justify spending the resources and effort.

Example of a challenge:
Your organization is experiencing a slight decrease in customer retention. You already have access to real-time data and analytics that help you understand the problem, but you want to leverage that data in new ways in order to make more informed decisions.

How to drive more value:
Being an Actualized organization doesn’t mean you’ve crossed the data maturity finish line — in fact, there is no finish line.

Only the most advanced companies make it to this level, which means competition is stiff. And considering the incredibly fast pace of data technology, companies that don’t continuously innovate will be left behind.

At this stage, optimization is key. Consider how data can better drive decisions and open up new opportunities for your organization. In the case of the challenge above, building new algorithms for churn models could help guide decision-making and reveal more actionable data.

Conclusion

Identifying your current data maturity level and setting goals for improvement is all well and good, but without taking steps to get more value from your data at your current level, your long-term progress may stall out.

Rather than thinking of data maturity models as rigid paths with set destinations, use them as way-finding tools. Once you understand where you are, you can move forward — no matter what “forward” looks like for your organization.

Regardless of your maturity level, we can help you get more value from your data. Discover how to improve your data infrastructure and decision-making with our Data Maturity Assessment.

5 KEYS FOR TACKLING
FAST TRACK PROJECTS

“Expect the unexpected.” We have all heard the saying countless times not only in personal settings but professional environments as well. For an organization “expecting the unexpected” can involve economic developments, industry shifts, operational circumstances, and of course, people dynamics.  

Oftentimes these unexpected situations can involve more than one of the above categories and create an organizational scenario that is heavy on importance and light on time. 

If this sounds familiar, then you may have a critical, fast track project.

Whether you’re faced with a crisis now, or looking to be prepared for anything unexpected in the future, here are five keys our team utilizes to help organizations move forward with critical, fast track projects.

1. Work Horizontally & Vertically. Disruption knows no boundaries. Leaders who can bridge communication gaps both horizontally and vertically within an organization will break down barriers and drive focus. Consider a generalist who can bring a holistic perspective. 

2. Ramp Up Quickly: Uncertainty creates a vortex of need. Seek people who love learning. People accustomed to diving into new disciplines are skilled at the process of learning and can move from beginner to expert (or close to it!) at a rapid pace. 

3. Navigate Ambiguity. Projects that surface quickly are usually highly ambiguous. Seek people who are energized by the unknown. They have confidence from years of working in uncharted territory to know that they are capable of figuring things out. 

4. Embrace Your Culture: Your culture is the key to “how things get done around here” and when time is limited, it is important to have someone who can adapt quickly. Whether considering internal or external support, ensure they have chameleon-like qualities to reflect your company and departmental norms. 

5. Tailored Solutions. Solutions need to make sense for your company and situation. Prioritize tailored approaches over cookie-cutter solutions.  

Critical, fast track projects are a constant as organizations frequently experience disruption whether by instigating or reacting to circumstances. A strong project leader with these five traits will help teams navigate uncertainty while achieving desired outcomes.

Check out these client outcomes to discover real world examples, and see how we successfully partner with our clients to help them navigate challenges and drive toward solutions.  

SURVEYING THE DATA LANDSCAPE IN 2022

In the past, data wasn’t necessarily important to every person within a company. It was used primarily by analysts, accountants, and other specialists.

But in 2022, companies are learning that becoming a data-driven organization means incorporating data into every aspect of their business — from talent management to customer engagement and beyond — and continuously optimizing how they use data with new innovations and process improvements.

What does being data-driven look like in action? Here’s an example: a west coast retail automotive company employing over 7,000 people across 9 states came to us with the goal of implementing a mixture of data science and machine learning to identify, implement, and improve safety, employee satisfaction, customer satisfaction, and profit margin. The client asked us to work with multiple teams within manufacturing, HR, marketing, and technology innovation to build out the desired capability.

To help this company reach their goals, we provided high-level strategic insight for new initiatives, built out proof of concepts, made recommendations for innovative methodologies, designed machine learning algorithms, helped them redefine company-wide KPIs, and trained their staff on new processes.

As a result, executives are better able to make key strategic decisions and further company goals based on data-driven insights, and the entire organization’s data literacy has improved.

A shifting mindset

A few years ago, the goal for many companies was “fixing” their data processes (a reactive way of looking at data management), with a focus that was often confined to specific departments. In 2022, most organizations are approaching data management differently. They’re aiming to be far more proactive — and to stay competitive, they have to be.

It’s less about simply “cleaning up” messy data, and more about creating meaningful, long-lasting, company-wide change that will continue to drive value and inform decision making in the future. In other words, it’s all about becoming data driven across the board.

Here’s an infographic that breaks down this change in mindset and some common challenges that are forcing companies to rethink the way they approach data:

Approaching data reactively and in silos is a way of the past. To keep up with the intense pace of change, constant innovation, and evolving customer expectations in 2022, a proactive, holistic, organization-wide strategy is required.

This change is positive on multiple levels. It’s not just good for staying competitive — it’s also a way to ensure that each of the common challenges described above (talent optimization, business insights, technical debt, etc.) get addressed so you can reap the benefits of becoming a data-driven organization.

That said, embarking on a large data transformation project can sometimes feel impossible, especially if you can’t promise ROI until months (or years) down the road. At The Gunter Group, we believe in taking a different, more iterative approach that enables organizations to realize immediate value while still keeping their larger goals — and the overall data landscape — in mind.

Ready to reframe the way your organization thinks about data? Talk to the experts at The Gunter Group.

What is tech debt?

Technical debt is often defined as the cost incurred when you repeatedly choose short-term solutions rather than doing the (larger, more expensive) work of tackling the big-picture causes of your problems.

But let’s look at the issue through a different lens: what is the nature of technical debt?

Because new solutions are built and deployed every day, all organizations incur tech debt, to some degree, with every system and process implementation decision they make. Even if you implement a new, innovative solution today, there will be a better one available tomorrow. In this scenario, you will still incur tech debt — just less than an organization that makes no updates.

Too many organizations think of tech debt as a problem that can be permanently solved. In reality, it’s a constant that’s renewed continuously by change and growth, and trying to “solve” it completely is a futile pursuit.

While you can’t make tech debt vanish into thin air, you can certainly make it more manageable. If you focus on managing its impacts in an ongoing way, you can deflate its looming, monstrous reputation and get to work on making meaningful improvements in the here and now.

Is tech debt destroying your data-driven dreams?

Analytics bottlenecks are a common issue related to tech debt. Silos slow down the analytics process; if only one person knows where a spreadsheet is and how to extract meaningful data from it, they become the bottleneck.

With each short-term fix and siloed process, data becomes harder to manage, access, and analyze. In turn, drawing insights from that data requires more time and effort, the insights become less timely and less reliable, and informed decision making becomes more challenging.

In other words, tech debt has a way of draining value from data — and the longer you let that debt accrue, the more value you’re losing. Using a prioritized approach to managing tech debt can help you cover more ground right out of the gate, so you don’t lose any more value than you have to.

One way to apply this prioritized approach is with backlog grooming, the periodic process of reviewing and prioritizing backlog tasks (and removing unnecessary or outdated tasks).

How do you prioritize what areas to address?

There is a lot of information available on how to tackle tech debt. Unfortunately, most of it is theoretical. While the abstract stuff can be valuable, if you’re looking for a practical way forward, you need to bring your considerations back down to earth and fold in the business perspective to create a technical debt prioritization plan.

You probably have a lot of tools at your disposal, internally and externally, and resources to leverage. Take a look at what you need to have happen — not theoretically (e.g. eliminating all technical debt by some point in the future) — but actually.

For example, The Gunter Group recently worked with a retail automotive company that was struggling with data debt. It was impacting every area of their business, including employee satisfaction, customer satisfaction, and profit margin. They needed a new approach, but with such a vast problem, it was difficult for them to know where to start.

We worked with multiple teams within the company, including manufacturing, HR, marketing, and technology innovation to create a prioritization plan. High priority initiatives included redefining company-wide KPIs, designing and implementing machine learning algorithms, and improving data literacy across departments.

Though they still have a long way to go on their data maturity journey, this company was able to start making changes where it mattered most, rather than remaining paralyzed by the challenge ahead.

How we work with clients to tackle tech debt

Remediating data-related tech debt requires far more than just technical skills — it requires asking the right questions, gaining a holistic understanding of your organization’s business goals (as well as how they may vary across different departments), and creating a dialogue to explore possible solutions.

Each of these components requires a tremendous amount of time, which internal teams rarely have. In most cases, managing ongoing operational struggles takes priority over transformation, and team members don’t have the capacity to focus all their energy on addressing tech debt. Meanwhile, recruiting new team members is a time-consuming, resource-intensive process, and thanks to the tech talent shortage, it’s more challenging than ever.

Turning to outside help can get the data transformation ball rolling without overwhelming internal teams or opening a can of recruitment worms.

At The Gunter Group, we leverage a multidisciplinary approach (technology, people, strategy, and execution) that enables us to see the long-term big picture while solving the highest-priority problems in the short term.

Combined with our extensive technical capabilities, this approach allows our clients to chip away at their technical debt and reclaim the value of their data as quickly as possible — without the burden of hiring a new team.

Conclusion

Think about a meaningful, specific problem you’re facing right now that’s rooted in technical debt, and what you would be able to accomplish if this problem was being managed proactively.

If you set your sights on eliminating tech debt across your entire organization, you’ll likely get caught up in a complex tangle of issues — and that one major problem that’s holding you back now will still be holding you back in six months.

To accelerate your progress, identify your most pressing issues, and reach out to expert help if you need it. With the right strategy and the right partner, you can mitigate tech debt and use your data to its fullest potential.

Is technical debt slowing you down? Discover how to improve your data infrastructure and decision making with workshops hosted by The Gunter Group.

BEHIND THE SCENES:
JOINING THE TGG TEAM

TGG Team Members Annie Cha, Nate Ferguson, Janice Lefebvre, Danny Quarrell, and Samya Thangaraj have been with The Gunter Group for varying periods of time and each one of them has a unique story in regards to their transition to The Gunter Group. 

Today, with their help, we are going to take a behind the scenes look at what it’s like to join the TGG team and become part of the TGG culture.  

Let’s start here:  What was your background prior to becoming a Consultant at TGG?   

Janice: I worked for a health insurance carrier.

Nate: Previously I had worked as an analyst and did some account management as well.  

Samya: I was a generalist consultant.

Danny: I did Director of IT and CTO type roles, mostly.

Most of you came from non-Consultant career paths. What was that like during the hiring process? 

Annie: I was actually a little bit intimidated because consulting wasn’t my background but what’s unique about the culture at TGG is that you don’t have to be from a consultant background to really thrive here.

Nate: In my case, TGG really helped me see the parallels with the core competencies I had from my experiences.

Samya: I realized and appreciated that they’re not focused on what you’re missing, but they’re focused on what you’re bringing.

Janice: For me, I appreciated that TGG found value in the idea that every person comes to the table with a different personality, different skill sets. 

During the transition, what about the TGG culture was supportive and helped you develop in your new role?  

Danny: What I loved seeing was that if a teammate wanted to expand their knowledge and experience in an area, TGG helped them learn it, and other people here with that specific skill or expertise, were more than willing to assist along the way.

Annie: Knowing without a doubt that I could reach out to any of my colleagues here and they would be ready and willing to help. 

Samya: I was told early on that it’s more of a family culture, and that definitely held true during my transition and has continued on a daily basis.  

Janice: I love how the team is close-knit and really cares about each person as an individual. This has been evident since day one, and it’s not only supportive but it helps everyone be successful as well.  

Thank you again to each of you for taking the time to share and reflect on your transition and time with TGG. We look forward to more opportunities to support our authentic culture and deliver impactful work together.  

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Interested in learning more about how our great culture comes to life? Click here and see what fuels our team, our relationships, and our work. 

Ready to jump in? Our TGG team is growing and we are currently hiring! Click here to see our open positions and apply.