The Enterprise Leader's Guide to
How to determine the right approach for scalability and increased profits
It’s hard not to feel like you’re stuck in the stone age when an ancient system solves one problem but can’t solve others. To make matters worse, an overwhelming amount of data with poor strategy can clog up your process flow, causing a domino effect of issues. Then, you’re expected to communicate that data but end up with more of a mess than an opportunity to provide clarity and strategy.
If you need to modernize your data system, you’re in the right place. But should you buy? Or build?
“60% of senior executives believe that digital transformation will be critical for business growth in 2022.” - A 2022 PwC report.
Forbes goes on to say, “In particular, businesses are poised to make technology investments, especially in cloud-related transformations as well as betting on trends in AI, digital identity, 5G, and IoT. “
Business survival is dependent on making smarter decisions with the resources and data you have right now.
Companies come to a fork in the road when their existing data solutions are outdated, or they’ve been outgrown, and it’s time to consider off-the-shelf (OTS) or completely custom data solutions.
It can be difficult for most leaders to know where to begin, but it’s necessary to find the right approach for your particular enterprise, team structure, and data needs and implement it well. In a year fraught with global shortages and logistical challenges, the companies that can innovate better than their peers will be the ones to shine and drive impact at every level of their business.
Why assessing your current tech is essential to deciding on build vs. buy
It’s time for organizations to modernize, but before you determine next steps on your efforts to transform your digital solution, you need to assess whether your current technology is adequately meeting your needs, and if it isn’t sufficient, you need to understand not only why it falls short, but also how it can be addressed and improved with a new build or buy approach, or some other model. There are a variety of common roadblocks and other issues organizations can encounter when they rigidly adhere to their own internally built digital solution – so let’s jump into them.
One of the most problematic issues a team with an internally built solution can face is that there may be one expert in your organization that knows the solution inside and out, but when they’re out of the office or they move on to another organization, you and your team are suddenly in the dark with processes and functions of your own internal technology. Without additional internal resources or adequate talent to provide upkeep for your current system, this “gatekeeper” can pose considerable challenges when they are unavailable.
Disparate data can also pose a challenge with your internal solution. Systems can’t connect and effectively talk to each other; your teams will have differing aims with this disparate data – making silos a more common occurrence.
By that same token, the daily demands of your business won’t be able to be supported with an internal system that’s antiquated, outdated, or outgrown. This issue and others like it can require a fair amount of internal maintenance on your systems – which can come with a considerable cost to your business.
Current off-the-shelf and SaaS solutions can be susceptible to problems as well. In some cases, they simply don’t provide all of the data that an organization may need – making it feel like just another disparate, out-of-date system. There’s also the misconception that off-the-shelf solutions can be simply applied and should serve as a “quick fix”. The reality is they often aren’t, and companies end up having to splice together multiple systems or create imperfect workarounds.
Continued licensing fees also present a problem to companies currently using off-the-shelf solutions. If the given solution isn’t adequately serving your needs, or the vendor providing it is unwilling or unable to customize it to the needs of your business, it certainly can be difficult to justify the recurring costs if you may have just as much success by bringing your solution in house.
For its part, RevUnit worked with a multibillion-dollar retailer who’s original assortment tool was created as a centralized environment for the front-end of the product life cycle, but it was too complex for widespread, frequent adoption by decision-makers. Users lacked guidance around how to leverage features within the tool, data was not updated dynamically, and the tool required dedicated technical assistance. We created a custom tool that condenses large amounts of information to at-a-glance overviews which allow users to easily orient themselves, determine next steps, and resume workflows — leading to faster in-store impact, less guesswork and decreased manual data entry.
Ultimately, it’s up to you and your teams to quickly and effectively identify whether your current system is affected by these issues, and seek to address them by creating an improved internal solution, seek out a different off-the-shelf solution (OTS) that better suits your organization, or devise some custom approach that satisfies your business needs.
Why choosing the right approach is critical to the success of your business
If your business checks certain boxes (or doesn’t) it can make the process of determining whether you are better suited for an off-the-shelf solution, one that’s built in house, or a hybrid format far easier. By identifying these key circumstances, you can make a far more informed decision as to what kind of approach will set your business up for long-term success and not create additional silos or waste resources.
Typically, off-the-shelf and SaaS data solutions are optimal for businesses that completely lack a data team or department. Many mid-market organizations often fall into this category, as they usually don’t have the available resources to complete a custom build. These mid-market organizations rely on OTS solutions to get them close enough to what they need – solutions like Salesforce, for example.
On the other end of the spectrum, OTS solutions are also particularly well-suited for businesses with very large tech ecosystems, in addition to companies capable of building out a team with the ability to internally customize their chosen solution.
Also, similarly to how mid-market organizations can rely on OTS when they don’t need a fully-customized solution, businesses can also implement a solution with a large enough SaaS company to the point where they have integration partners (Oracle, Salesforce, etc.) to help them along the way.
Unfortunately, buying software off-the-shelf is never just that. Organizations afterward are often forced to choose between retraining their staff to conform to the new software, rewriting procedures so that they are in line with the software’s functions, and ultimately becoming subservient to the processes laid out by the software they just bought. Your organization will have far less autonomy when you choose to buy instead of build, or craft some hybrid option – your organization will only be as flexible as the system that you purchase.
A single, off-the-shelf solution doesn’t typically solve challenges, and even if it does, organizations still struggle with disparate systems and redundant data and processes.
When purchasing support and services is required to bring the generic software you bought into line with your specific processes and procedures, your organization can become tied to purchasing support from the selling organization itself, or a set of certified partners — you are rarely allowed to adapt the software yourself.
Another important concern – will the company you partner with for SaaS exist in 10 years? Will the platform you choose exist, or will you be pushed to a different offering? Even large companies such as Microsoft and Google may exist 'forever', but can capture or kill platforms you may depend on. There's even a list of platforms that have been killed. When deciding on a completely off-the-shelf solution, you should expect to have to strictly adhere to its specific processes if your business doesn’t possess the necessary customization capabilities in house.
To understand the ideal conditions for choosing to build your own data solution in house, you first need to have a deep, nuanced understanding of your company’s needs, the capabilities of your data team, and whether they are equipped to address those needs.
Obviously you will experience fewer dependencies with your own software as opposed to relying on others, and you will always have more autonomy and added decision-making capabilities around the technology or tools that you create yourself. It also provides your respective team with the space to innovate, fine tune, and push the edge with their solution (like exploring IoT), as opposed to attempting to leverage an existing system. If you’re interested in innovation, you simply won’t find it off-the-shelf.
This drive for innovation also allows for “first-to-market” opportunities, allowing businesses who take this approach the chance to have an edge over their competitors, who may still be choosing to operate with a SaaS business or off-the-shelf solution themselves.
The advantages of build over buy are quite apparent – building affords your business more control, maintenance fees can be brought in house, and software development can be capitalized on as a tax writeoff. Unfortunately, the common challenge here is that most internal teams are not equipped for this type of large-scale software undertaking all on their own.
This is the first question you need to ask of your organization – do you have the team to build the solution you want? If not, is your organization even able to invest both the necessary time and money to establish such a team?
Essentially, building a completely custom data solution in house is only really useful (and even possible) for organizations that are large enough and already have a designated technology team to tackle the challenge. If you are a mid-market organization or smaller enterprise, the costs of identifying and capturing the talent required will likely be too great. If you choose to go this route, you will want to perform a thorough analysis of your data team’s capabilities to ensure you can even get this approach off the ground.
How creating a bespoke data solution benefits organizations and their users
With SaaS companies trying to provide you with their solution (at a cost) and building in-house being a potentially cost-effective option (but only if you have the necessary infrastructure already in place) it can feel that build vs. buy is a moot argument if neither effectively addresses the data needs of your organization. The fact is you have more options than just build or buy — bespoke solutions that combine the best of both worlds on the spectrum of build-to-buy.
Some organizations you can partner with provide access to a “packaged core” that can be tailored specifically to your business. If you opted to try building in-house on your own and discovered technology talent is what’s keeping you from this, you can find a partner with the bandwidth and expertise to supplement your teams with the required talent. These same experts–like RevUnit– can also carry out what is known as a teach-and-do model, in which this outside partner is responsible for upskilling your own teams, working quickly to bring best practices (with which they’ve already seen success) to those same internal teams. With this approach, your partner doesn’t just leave you with a solution you can’t maintain.
Through this hybrid partnership dynamic, your teams are able to make their own tech decisions without being dependent on third party software. With this autonomy also comes increased flexibility, as you can more easily respond to the changing demands of your business, your customers, and the market.
RevUnit’s approach to assisting organizations with modernizing their data systems focuses on natural integration into existing workflows – no SaaS tool here. We integrate semi-custom or fully custom solutions into client’s existing systems with a data-first approach so we can help our clients build a strong foundation that will continue to scale.
Naturally, we are big proponents of a teach-and-do approach. We don’t just build our clients a solution that their data teams can’t maintain alone. We work in partnership with enterprise businesses, bringing clients along with us and embedding ourselves within their teams in order to bring over skills they don’t possess internally. This way we build exactly what they need and craft our solution so it can plug into a larger system or be expanded upon for continued scalability.
RevUnit also has significant experience implementing hybrid data system modernization with multiple companies in varying industries – we’ve provided some examples below.
It’s up to you and your data teams to determine what kind of approach is most fitting in order to modernize your current data systems, but you also need to make an accurate assessment of whether your organization is set up to succeed with your particular choice of building, buying, or calling on a partner to create a hybrid data solution at all.
Customization is essential to adapting a generic product to your specific needs – is your team capable of this? When you will be dependent on people who know the inner workings of your business, will you want them to be in-house or working for a SaaS company?
A source of truth for both day-to-day operations as well as overall performance is crucial. The challenge comes when off-the-shelf solutions don’t meet the needs of the business, and internal teams lack the resources to create a single custom, scalable solution. Good approaches exist for both large and small organizations, but to avoid issues inherent to certain approaches, you need to adequately determine which one is right for your business based on your available resources and team capabilities.