Northwest Data ConsultingAs a consultant, it’s important for me to tailor my services as closely as possible to the unique needs of each corporation each time I engage. No two consulting engagements are exactly alike, but there are some typical cases that might give you an idea of what to expect.
The numbers in these cases are hypothetical, but based on my experience with organizations of various sizes. Estimates of profitability are taken from a study of average profit margins in various industries.
Case 0: some occasional advice
Sometimes you don’t need a lot of help on a specific project, but just a quick review of your analytics setup to address a couple of pain points. Or maybe you want an expert, on an ongoing basis, to answer questions occasionally as your team encounters issues. I’m happy to be on call for a few hours a month of guidance and advice.
Case 1: small company needs a data bootstrap
Let’s take a manufacturing company with a few employees and $1m in yearly revenue at a 15% margin ($150k annual profit) which wants to quickly put in place some useful analytics and reporting. A lot of smaller companies like this understand the importance of putting their data to use, but don’t have the resources to hire a whole data team, or even a dedicated analyst at $75k/year or more. And their data needs might not be big enough to occupy a full-time analyst.
This company doesn’t have a large amount of data by modern big data standards, but it still has what, to its principals, is a good deal of data. They have data on customers (maybe from CRM software), finance, marketing, manufacturing processes, and perhaps other sources. They probably already have some minimal analytics capability (perhaps using spreadsheets and Intuit, for example). But they want to get a broader picture of their data and be able to see reports in one place, rather than using several disconnected tools.
This use case will require some integration to connect multiple data sources. And this company is a good candidate for a business intelligence tool like Microsoft PowerBI, or an open-source alternative like Grafana. Either of these tools (or other similar ones) can connect to multiple data sources and combine it into unified reports and dashboards.
This project might require a week or two of full-time consulting work. I would work with the principals and employees to better understand their needs, select appropriate tools, install and configure them, build a set of initial reports, and give a manager and employees some basic training on how to use the software and build their own reports, so they could be self-sufficient in the future.
For a week of full-time consulting, depending on particulars, I charge $5k. Let’s look at the value proposition in this case. For $5-10k, depending on scope and individual needs, this organization would gain a solid base of analytics capacity on which they could build in the future, and gain the knowledge to use the tools themselves. This company could realistically boost yearly profits by $25k by putting better analytics in place. When you compare that cost to the yearly salary of a dedicated analyst, and the time spent in the hiring process, this company is making a solid choice by investing in a foundational analytics capability.
Case 2: somewhat larger company has some analytics, but needs an overhaul and upgrade.
Let’s take the case of another, slightly larger, company (say fifty people), which has already made some investment in their analytics culture. This company also has multiple sources of data, and in this case the volume and velocity of data is higher. They have paid licenses for PowerBI or Tableau, but their analytics is still not well-integrated. Not all of their data sources are connected…
It is very common for organizations, especially of this size, to have siloed data, meaning that the data exists in multiple disconnected sources. But often the best data insights come from combining data from multiple sources, such as integrating your finance and marketing data. This company probably needs to develop some data transformation processes, like ETL (Extract Transform Load) operations using dbt or a similar tool. Those processes will combine and refine data into a form that is more easy to analyze, and which gives insight across multiple areas of the business.
In this case, a few weeks of work might be required, perhaps continuously, or perhaps spread over a few months as your team learns to develop these processes for themselves. Let’s look again at the value proposition here. A typical 50-person company might have $7.5m/year in revenue. At a profit margin of 10%/year, the company is making $750k in yearly profit. If improvements in their analytics culture can improve profits by 10% (which is on the low end of estimates for improvements from embracing analytics), the total value added would be $75k/year on an ongoing basis. That seems like a pretty good return on investment for six weeks of consulting work ($25-30k).