Automating your decision support system to change the reporting game.

Updated: Aug 23, 2021

Data analysis used to make vital decisions for success is called a decision support system (DSS) - often presented in the form of reports and dashboards. In today’s competitive business landscape, having the right data and the ability to quickly interpret it can be the difference between those who innovate and those who struggle to meet their customer’s expectations. With this in mind, the real question comes into play: if reporting is so important, why is the process to regularly develop it so difficult?

Building and designing a useful DSS is no walk in the park. Oftentimes, employees will need to develop a back-end data pipeline, create an automated ETL (extract, transform, load) process, and finally read them into a dashboard. While there are so many solutions available to us, it can be daunting to try and pick the best ones and know how to put them all together.

But before we dive in further, we must understand how exactly a DSS is built and what kind of conclusions can be drawn from it.

So, what exactly is a DSS?

A DSS is anything that can relay important information used to make decisions. It can be as simple as your project budget on an Excel spreadsheet, to something more complicated like a recommender system built in conjunction with a Neural Network. Some common DSS examples include:

  • Balanced Scorecards (most commonly seen in Ontario hospitals)

  • Project Status and Budget Reporting (most common in project management offices)

  • Surgical Scheduling System (used by hospital administration)

  • COVID-19 Hotspot Dashboards (used by public health agencies)

  • Operational KPI Metric Reports (used by operational teams in most businesses)

  • and a whole lot more...

(Leave us a comment below with your own examples!)

The fact of the matter is, a DSS that conveys data in an easy-to-understand way is critical to the success of any business. Unfortunately, this is where a lot of organizations are really struggling.

Most organizations are so focused on their products & services that there may not be enough time, resources, or capacity available in building effective reports which deliver immediate insights and support in decision making. Rather, when insights are needed, employees who are already stretched thin with their day-to-day responsibilities have no choice but to manually stitch reports together for their higher-ups.

From an executive’s point of view, a bunch of charts, tables, and histograms are visible in their inbox on a daily basis - how hard can that be to quickly whip together?

As it turns out, very.

We would like to take this opportunity to briefly walk through the blueprints of common decision support systems.

High-Level Architecture

This high-level architecture can be used as a blueprint to create a decision support system for your business (or even for a project). The objective of this diagram is to showcase "the art of the possible", rather than go through and teach you all the functionality of the tools within.

Once set up in an automated way, it can significantly free up your team's time, allowing them to increase productivity and focus on innovating and delighting your customers.

Note: We’ve listed the names and descriptions of each sample software in the appendix below. Pssst, we’ve also included some fairly popular examples in each step. You’re welcome ;)

Each of the steps noted in this diagram can be set up in an automated (or semi-automated) fashion, allowing your team to query your data and visualize it in a dashboard, share it with people in your organization (executives, team members, other departments, etc), or even with your customers.

Of course, the architecture above isn’t going to be reflective of your exact situation. Every business is unique and your data may actually not reside in some application at all (such as Salesforce) or even in a Database. If you are like 85% of the businesses we have worked with, your data is actually in a bunch of different Excel files which you either get sent to you via email or located somewhere on your company's shared drive.

Just take a look at this survey we conducted on LinkedIn. Based on this survey, only 15% of workplaces have set up systems other than Excel to house their data.

In this case, the first step may be to house the data into a Data Lake or a central repository of some sort, such as a relational database (stay tuned for our article on these topics!).

With this blueprint in hand, the journey to setting up a decision support system for your business can go two ways:

  • Option 1: Learn how each of these different tools can be used to communicate with each other, and then automated (there are several free videos on YouTube to help you with learning)

  • Option 2: Consult with an expert who can give you an accelerated head start on setting up your decision support system

Selecting option 1 will definitely pay dividends in the long run, you'll develop your own skills, your teams' skills, and in the end impress your boss(es) - well on your way for promotion! The road to learning how to automate your data pipelines and creating your own DSS is a long and treacherous one, but boy howdy will you be glad you took it!

However, if you're in a pinch, your whole team is already stretched thin and you need insights on your data yesterday - you can skip right to the insights and using your very own DSS at the click of a button!

It's noble to ask for help in things that may be too complex or time-consuming for you to deal with along with the 99 million other things you're dealing with. Don't wait. Contact us today for a free consultation on how best to set up your decision support system.



Extract/ Export

  • Salesforce - CRM

  • Odoo - ERP

  • HubSpot - CRM


  • Python - High level programming language

  • SQL - Querying language

  • R - Statistical programming language


  • Oracle - Database

  • PostgreSQL - Database management system

  • Amazon Web Services S3 - Object storage software


  • Power BI - Visualization/ dashboard tool

  • Tableau - Visualization/ dashboard too


  • Excel - Spreadsheet/ analysis tool

  • Google Sheets - Spreadsheet/ analysis tool

#data #datascience #etl #dss #decision support

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