5 Myths About Data Analytics Adoption

I’m revisiting a subject. I wrote about it in 2016, and seven years later, the topic is still actual. I decided to write about it to let you know how the correct strategy can help you to have a data-driven business.

The context

Years ago, owning an ERP for business management and computers ceased to be a competitive advantage, regardless of the business size.

Today the challenge is different: transforming data into knowledge and, from there, optimizing processes, making data-driven decisions, and achieving better results.

Unfortunately, for many companies, it is still treated as something out of reach, intended for a few, just for big companies.

Is it true?

The Internet and its new business models, the use of on-demand computing, and the high availability of knowledge for those willing to learn have brought fresh air to this universe, reducing costs and put it available for those who desire.

But certain myths are still alive. What do you think about talking about them in five popular topics?

1. It's expensive

Indeed, a BI project in the 1990s and 2000s could require a significant technological investment (software and hardware). Talking about hundred of thousands was very simple.

But the advent of a more direct approach and tools with zero initial cost brought an entirely new perspective to this market.

In software, today we have Open Source databases, like MySQL, PostgreSQL, MariaDB, and MongoDB, among others, and Microsoft's PowerBI, which can be downloaded for free from the site, or Google Data Studio, an online tool from Google.

On the hardware side, using scalable cloud servers allows projects to be started instantly, without machine acquisition and with very low initial costs. We have cases that started at $200 per month using AWS infrastructure.

Access the Power BI Pro Services has a $9,90 per-user license fee. It is enough for a significant number of projects.

2. The company is not ready

Considering that all companies have data, I always ask myself: what is a company ready for data analysis?

The day-to-day has many operational routines such as orders, invoicing, accounts payable and receivable, accounting, sales, etc. ERPs support all these routines, which provide specific reports for each module.

But what about strategic information? Where are cash forecasting, stock provisioning, sales performance indicators, analysis of costs, and profitability of the business done?

These are usually the responsibility of our friend Excel. A lot of Excel, by the way

Companies spend a huge amount of hours gathering and organizing data extracted from various ERP reports in "simple" spreadsheets. Besides being laborious, this has a high embedded cost and usually provides outdated information.

So, why don't you use an appropriate tool that will demand some time in development but will update the data automatically after this?

One of the most common tasks we receive is precisely changing this scenario.

We do it by creating a direct connection with the data source and eliminating manual data extraction by developing a programmatic interface. The result is stored in a database; after that, we develop dashboards and reports.

The next step will be to establish an automatic update routine.

And it doesn’t matter if we are talking about a thousand of a million records; the most important here is to turn strategic information available uptime.

3. It takes time to deliver results

Creating reports and dashboards today has become more straightforward than 20 years ago.

We still need to have knowledge about the technical stuff, but with the right approach, we are no longer talking about months and months of development by a large team of developers.

I usually work to define an MVP – Minimum Viable Product – that typically includes the development of the data source connection, database configuration and implementation, data upload, and first dashboard or report development. After the MVP delivery, we start a continuous evolution process.

It means the client usually has the first results in 60 days. Nothing bad, no?

4. It's complicated

It is not complicated if you have the right team with the right technological solution working with clear goals and experience in business solutions.

A well-implemented BI system dramatically simplifies the data collection and updating process through automation, freeing up time for information analysis. It is a totally different scenario compared to manual extraction from systems and the use of sophisticated Excel worksheets, always with the risk that something goes wrong.

5. It's always outdated

While data updates on Excel used to happen when is possible, the automatic routines can occur multiple times a day, allowing real-time monitoring of critical indicators.

We can do it by creating program routines or using services like Power BI Services.

6. Extra topic: We don't have too much data

Accurate information to manage the business is essential, not the volume of data.

Your company could have single or multiple locations, thousands or millions of data records. It doesn’t matter; you need to know what is happening and have numbers to make decisions, and we are talking about it.

By the way, usually, we have much more data than we imagine.

Conclusion

Once a BI tool is implemented, dealing with its day-to-day operations is much simpler than dealing with thousands of Excel spreadsheets. However, I'll leave that for my next article, where I intend to discuss the advantages of using this tool.

Having a result-oriented team working on the project is crucial to reduce costs and time to start having results.