Traditional vs. Minimalist. Which Analytics is right for you?

What's in this for you?

There are so many tools, technologies, and buzz words in data and analytics that it can easily make your head spin. The challenge is in understanding which of these are right for your business. In the early days, companies chose their tools before their strategy. This usually happens because departments would buy their own tools independent of one another—a very “bottom-up” approach that can lead a company down an expensive path.

In this article we’ll explore two, high-level approaches that companies can take when embarking on their data strategy—the Traditional Approach and the Minimalist Approach. After we define these two data analytics services, or approaches, we’ll help you choose between them to find the best solutions for your company’s specific needs. Here at TypeSift we’ll help you understand which tools are best for accurate, efficient, streamlined analytical data.

Traditional vs. Minimalist Analytics

Traditional. As you may have guessed, the Traditional Approach to analytics has been around for decades. At a very high level, when adopting this approach, you do the following:

This approach typically suits businesses that require highly bespoke and customized systems.

Minimalist. The Minimalist Approach, unlike the Traditional, is a fresh and remodeled take on business data analytics. At a high level, the Minimalist Approach to analytics requires the following:

A favouring of configuration over customization to keep costs down and implementation times short.

This often leaves leaders asking: Which one is right for us? It’s easy to think that your business needs a highly bespoke solution. After all, who knows your data better than you? But it’s a little more nuanced than that.

Our Secret to Choosing the Right Approach

Picking between Traditional and Minimalist Approaches isn’t difficult, but it can be a little unintuitive. When reflecting on which companies need a completely bespoke (Traditional) versus a turnkey (Minimalist) solution, we were surprised to discover that the difference came from a company’s revenue model.

Yes, their revenue model. But what models are we talking about?

Usage-based revenue. This is any product or service where you pay more for it the more you use it.

Ticket-based revenue. This is most commonly seen in consumer goods and services, and professional services. A ticket is a receipt you get from the Point-of-Sale or an invoice issued after a project is complete.

Here’s the secret: If you’re usage-based, go Traditional. If you’re ticket-based, go Minimalist.

Why would the revenue model have any impact on the analytics approach?

Think about the kinds of companies who have a usage-based revenue model:

These companies’ revenues are tied to how much their products are used—the more they’re used, the more they make. So, they’re very keen on keeping you tied to their platform, increasing daily usage, and reducing churn. They can’t know how much they’ve made until after the product has been consumed, and they need to mine their massive amounts of usage data and route that through their billing and accounting systems to get a clear picture of their finances. This means their architecture tends to be bespoke and highly complicated, and could look completely different from one company to the next, even within the same industry.

Now let’s look at companies that are more ticket-based, such as:

For companies with ticket-based revenue models, you know the cost of a product or service up front. Whether you receive the ticket after payment (receipt) or before payment (invoice) is irrelevant. Unlike in the former model, these are discrete, self-contained transactions. And in all of these cases we’ve found that their internal data architecture looks 80%–90% the same, even across industries.

This distinction helps sort the vast majority of companies into one of two camps. If your revenue is usage-based, you’ll probably need a bespoke solution. In this case, pick the Traditional Approach. If your revenue is ticket-based, you’ll fare better with a turnkey solution. Pick the Minimalist Approach.

Another good question to ask is: Who is the primary stakeholder and what are they trying to optimize? If you’re trying to maximize usage and minimize churn under the Traditional Approach, then the increase in top-line sales should more than offset the fixed cost of an in-house team. This is because you have the scale to do it. On the other hand, while optimizing top-line is still important, it may not always be enough to offset fixed costs. In this case the stakeholder is the CFO who’s trying to maximize earnings before interest, taxes, depreciation, and amortization (EBITDA), and would benefit from a Minimalist Approach.

Strange Exceptions to the Rules

We described the above revenue models as two “camps”, but they’re less discrete than that. Some companies don’t fit neatly into either, while others may fall somewhere in between. Here are some examples of companies that don’t quite fit the mold:

Mega retailers. Think of huge companies like Walmart and Amazon. These businesses are obviously ticket-based, but they have such a mass volume of data that centralization into one, 360-degree view of the business is impractical. So, they have to hire an internal team to build bespoke solutions for each line of business.

Public sector. This one is a bit trickier, as the public sector doesn’t generate “revenue” per se, and each ministry may be different. In this case it’s best to consider if there’s any legislation that requires a ministry’s data be centralized and integrated. If so, choose the Minimalist Approach.

Charities. Just like the public sector, charities don’t really generate “revenue”, although they do raise funds through various means. They may, however, have mandated reporting requirements.

Real estate. Another odd-duck is the real estate sector, which operates on extended time horizons, have massive returns, and may not feel the pressure to optimize EBITDA over a short time frame. But their revenues remain project- (ticket-) oriented.

In all of these cases you have to dig a little deeper than simply identifying the revenue model and ask, “Is there a need or mandate to centralize the data?” The need may come from making decisions on a weekly basis. The mandate could be a piece of legislation.

The second question to ask is, “Can this practically be done with as little customization as possible?” For big businesses with legacy systems, the answer could be no. But if there’s a strong need or mandate to centralize data, and it is a feasible endeavour, then the Minimalist Approach is a strong candidate.

Traditional vs. Minimalist Pros & Cons

There are pros and cons to each approach. And to be clear, even though TypeSift helps companies adopt a Minimalist Approach, we see merit in both approaches. It truly does depend on your business and its specific needs. If you make the wrong choice, you’ll be trying to stuff a round peg into a square hole. Choose correctly and you’ll enjoy a higher return on investment, whether that means higher revenues (under the Traditional Approach) or higher EBITDA (under the Minimalist Approach). See Table 1 for a breakdown of the different approaches.

Traditional Minimalist
Bespoke Turnkey
Full-time, In-house team Outsourced & Fractional
Great for Usage-based revenue models Great for ticket-based revenue models
For companies who ARE data & software experts For companies who are NOT data & software experts
More moving parts, higher maintenance cost, longer implementation times Fewer moving parts, lower maintenance costs, shorter implementation times
Truly big data (Terrabytes and billions of log records) Small to Medium data (Gigaybtes and < 1B records)
Customization over Configuration Configuration over Customization
Optimize Daily active usage, customer lifetime value, lower churn. Used to increase traffic (frequency of tickets) and/or ticket size (Average Order Value).

A Combined Approach?

It is possible to combine a Traditional and Minimalist Approach, but you should have a very specific reason for doing so. From our experience we’ve seen companies successfully combine these two approaches for one of three reasons:

  1. To avoid a sunk cost. You may have bought some of the tools and hired some of the people for a Traditional Approach, but now you want to make a pivot part way through. Rather than burn your past investment in the Traditional Approach, you can fit the Minimalist system into the established architecture. We do recommend striving to go completely Minimalist in the long term so that you can get the full benefit of it.
  2. To get the most out of your Data Scientists. Use a Minimalist Approach for the core RP&A but then hire skilled Data Scientists and Software Engineers to build artificial intelligence (AI) and machine learning (ML) solutions on top of that. In this case, Data Scientists can benefit from starting from the same foundation of cleaned and consolidated data as everyone else without having to do work they don’t like to do (i.e., reporting and data cleaning). Again, the Minimalist Approach helps you get the most out of your Data Scientists.
  3. To create a split revenue model. If your business makes some money from usage and some from tickets, then, depending on what your revenue split between usage and tickets looks like, you may split between the Minimalist and Traditional Approaches. For example, you may take a Minimalist Approach just for Finance, and a Traditional Approach for everyone else. Or you may do the opposite, with everyone going Minimalist except one department (like Product or Operations). In this case, the Minimalist and Traditional Approaches are fairly self-contained.

Get Our Help

Are you considering a Reporting, Planning, and Analytics implementation? Do you want some help in deciding on a strategy? Then get in touch with us—book a 20-minute discovery call and we’ll help you decide if a Traditional or Minimalist Approach is right for you. If it’s Traditional, we’ll recommend vendors we trust. If it’s Minimalist, we’ll show you how TypeSift can help.

TypeSift is a Data Engineering & Design Minimalism Firm. Our expertise is decluttering information and solving problems in your data that are holding back your growth. We build software that corrals data and invokes ingenuity with the fewest moving parts.

Download, The Data Journey Map.

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