7 Core Tenets to Know Before You Develop Data & Analytics Products
Do you follow the 4S Model?
Businesses around the world are adopting cloud technologies in order to accelerate business outcomes in data and analytics. As a systems integrator and consulting services company, Hashmap works with a variety of clients, from startups to Fortune 10 global enterprises, across a multitude of industries.
In my role as a business development representative, I talk to clients daily about the challenges of developing data and analytics products. I try to help them understand the value in following seven core tenets that we’ve seen help accelerate new technology initiatives and ensure that business outcomes are the primary focus.
1. Keep it Simple. . . Until You Can’t
One of the first steps I take when opening up a dialogue with a new client is to help assess and evaluate high priority use cases and understand current pain points and gaps. This can help provide a better overall picture of the exact business outcomes that they desire so that we can begin developing a solution approach together. In a basic sense, our job as a solution consultant is to help our clients avoid common pitfalls while helping them choose the correct services/products to drive business outcomes. Ultimately, we design, architect, deploy, and deliver the underlying pipelines and frameworks for their data and analytics ecosystems. One of the problems I often encounter is that the focus of the conversation turns to architectural details and becomes overly complex as clients lose sight of the original business outcomes they were looking to achieve. Understanding this, it is vitally important to have a validated use case, a tangible business outcome, and a reasonable ROI in place to move beyond simple. In pizza terms (which I’m a fan of), a pizza restaurant would not purchase another oven (add new technology to the architecture) unless the demand for their pizza outweighed the output of their current oven — otherwise, no matter how good the new oven (tech) it’s still tech debt and not required.
2. Avoid Option Fatigue
The majority of customers that I speak with have another condition — they are weighed down by too many tool options, a situation we refer to as “option fatigue”. There is an almost unlimited variety of choices available when it comes to data storage, data access, data integration, data infrastructure, data enrichment, data quality, data security, etc. Many vendors are even promoting that they can “do it all”. These choices become even more confusing when you toss in the non-technical aspects, such as the long term viability of a company, ease of doing business, pricing models, and size and complexity of deployments. With this in mind, it is vitally important to have a clear view when choosing a service or product in this space. Because we don’t resell any products or services at Hashmap, I tend to spend, as do our consultants, a great deal of time helping clients understand the pros and cons of various competing or complementary products/services as it relates to the specific use case that they are targeting.
3. Focus on Outcomes, not Infrastructure
When I speak with a company that has dealt with challenging data and analytics infrastructure for a couple of years, a number of common themes tend to repeat. “We can’t keep anything up and running”, “it takes us so long to deliver a new data product to our users”, “we haven’t delivered much at all in the last 3 years”, “our users have to learn new tools to access the data”, and so on. Data and analytics programs flounder when more time is spent managing the underlying infrastructure than actually achieving meaningful business outcomes that drive value. In fact, it seems to me that patience has been completely exhausted for customers that have been burdened with a heavy dose of technical debt and infrastructure management. With this in mind, it is important to choose services and solutions that not only work in the short term (and meet the right value/risk profile) but will also hold up over the long term. Simply stated, you want to avoid a complete solution redesign every time your business outcomes change and instead choose solutions that adapt easily to your ever-changing business needs. It is important to note that no single technology is perfect; the industry is always evolving.
4. Choose a SaaS or Cloud-Native Solution
One thing that has risen to prominence in the last few years has been the increased demand for cloud and SaaS (Software as a Service) services. As a technology company, we are huge fans of both. We also recommend solutions that work, and ultimately those solutions are overwhelmingly cloud-native, SaaS, and/or a combination of both. Within Hashmap, for instance, we make use of Hubspot as our CRM (Customer Relationship Management) solution. The beauty of Hubspot lies in the fact that it is a SaaS service, which means that there is absolutely no underlying operational overhead needed to run or use their service. Hubspot manages all of the infrastructure effort associated with keeping their service up and running. Better yet, I don’t even have to install anything on my laptop because Hubspot is delivered right through my browser. I can simply log into my Hubspot account from anywhere, and as a user, the only thing I really care about is whether or not the service is delivering the expected value and that is works — every time. Applying another pizza analogy, I would rather just purchase a pizza and have it delivered to my house rather than having to source all the ingredients, roll out the dough, and build my pizza only to come to the realization that it would have been less time consuming, cheaper, and tastier if I had used the local pizza service.
If you are in need of a platform to manage your sales cycle, keep track of your current deals, run marketing campaigns, set up workflows, and build intuitive reports, etc, then I cannot recommend Hubspot enough. Hubspot has the best customer service that I have ever experienced. Their service lets me focus on business-related outcomes for my sales and marketing campaigns. With this in mind, I would suggest strongly considering the outcomes that you are looking to drive, and the company that you are considering doing business with before purchasing any new technologies or signing any contracts.
5. Stop Looking for Unicorns
The days of expecting a single solution to solve all business challenges as it relates to cloud, data, and analytics are over. Likewise, no single individual is going to have knowledge across all clouds and cloud services, development languages, data science tools, and AI/ML algorithms. This is because the cloud, data, and analytics ecosystems are becoming exceedingly complex and they are evolving faster than ever before. In our experience, technology solutions and individuals that claim to be able to do everything, end up doing nothing very well. One of our core strengths at Hashmap lies in our ability to deliver customized solutions that are tailor-made by our consultants who are individually chosen based on their expertise for the solutions that they will be implementing.
6. Avoid the Technology Rabbit Hole
We all love to talk about the merits of various technologies, and we all have our favorites. Most likely, you’ve talked to friends about how technology can be used for the betterment of humanity. In the case of most people, this can be exemplified by the recent SpaceX launch and the impressive advancements in space technology compared to the early days. When looking into new technologies for internal business purposes, it is vitally important to understand how a specific technology will help drive business outcomes and create value. This is addressed in detail in one of our previous blog posts, but ultimately you should be asking the question of why? Look around and identify your current pain points, figure out how that specific technology will provide value, and measure its effectiveness. In most cases, the overall value of a product or service can be evaluated at a smaller scale before being fully implemented. In fact, quite often, I talk to customers about building out different environments on a micro-scale so they can figure out which one best suits their needs.
7. Apply the 4S Model
Solutions in the data and analytics space can (and should, in many cases) be simple; it’s best to avoid incurring technical debt unless it’s absolutely necessary. Likewise, run from any solutions that require your end-users to learn new tools just to consume data. Additionally, solutions should be speedy, not in terms of performance (although that is always important), but with regard to “time to value” — long drawn out deployments without incremental value being delivered shouldn’t even be considered. Solutions need to be ultra-sustainable, meaning that they should not be brittle, breakable, or prone to downtime, and certainly not require the proverbial baling wire and duct tape to keep them up and running. SaaS solutions really move the needle in all these areas. Lastly, solutions should be self-serve, and not require a multi-month IT project each time a new feature or dataset is required. Apply the 4S model and you can really shift the focus in your program to helping accelerate data and analytics value creation for your end-users and key stakeholders.
Final Thoughts
I hope these perspectives have given you some new insight that will benefit you in your own projects and initiatives. If you only take one thing away from this post, remember the 4S model in your solution approach: simple, speedy, sustainable, and self-serve. These four solution tenets will help keep your strategic data and analytics initiatives on track and moving forward.
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Luke Kline is a Sales Development Representative with Hashmap using HubSpot, data, and the cloud every day while helping customers and partners deliver meaningful business outcomes with data and cloud-driven solutions.
