Overview of the BI Maturity Model in 2020

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Opening thoughts

There are a few BI & Analytics hypes going on in the recent years driven by the immense quantity of data that has become available thanks to the IoT era. It naturally generated novel ideas and techniques to obtain insights and find business value.

Alignment between business and data analytics has been missing for a while: lack of understanding the nature and benefit of AI techniques, contextualized automation or insights from unstructured data is still the greatest obstacle for Companies to internalize and operationalize these Technologies. The challenge for the upcoming years is to bring clarity for data scientists in AI and overall advanced analytics field and transparent communication towards the management. Data scientists have to learn telling complex stories clear and simple, that requires comprehensive understanding of recent techniques and their limitations.

It takes all the running you can do, to keep in the same place. If you want to get somewhere else, you must run at least twice as fast as that!” – according to Lewis Carroll’s Red Queen.

Keeping up with the ever changing technological and business environment imposes a great pressure on every Company, and managers prone to hurry innovation that can put the entire Organization on a track of deterministic failure. It is a certainty, that current state of Company BI is reflecting the needs of the past (question is: how distant past it is?).

BI maturity model 2020

In case of a mature company there is a natural evolution of business needs in relation of how data (and underlying backend solutions) and analytics being used to answer certain questions, and how organizational structure and company culture is reflecting to all above circumstances. So how does this evolution look like?

BI Maturity Model 2020: The evolution of the BI

1. The beginning

In the beginning an IT guy created a very basic reporting (spreadsheets most probably). And the data was without form, and void; and darkness was upon the face of the Company. It is a completely unaware state of operation, where you just try to get access to data.

2. Enlightment

And the Spirit of BI moved upon the face of the reports. And God said, Let there be light: and there was light. Key performance indicators have been created, to help discovering the data, to measure success and to answer “What happened?” type questions. Relational databases appear, but all of this is still in an opportunistic stage in the more or less capable hands of an IT department, called John or Bob.

3. From data to information

Then the question comes: “Why did this happen?” And to answer it, we need to dig deeper and understand the correlations between our variables. Models are emerging to describe data interconnections and to identify business drivers. You have just turned data to information. You are getting focused. At this point you may have multidimensional data models and a handful of Business Analysts spread across the departments to answer ad-hoc business questions.

4. What’s next?

Now you know the “Why?” but you are getting more anxious about the future. So, what may happen to your Company? By this time, you think in strategy, and you have most likely taken a deep breath to build an Enterprise Data Warehouse, and you have scaled applications to extrapolate past information to future information. Predictive stage may also shake the structure your growing organization, that follows the changes of other dimensions. BI competency center is one of the key enablers of this stage, to have a standardized and centralized team of professionals to leverage all relevant competencies and support the needs of a data-driven organization.

5. From information to knowledge

At the Prescriptive stage, you would answer the question “Why is this going to happen?” – by transforming information to knowledge. Your Enterprise is most probably so large by now, that it is starting to look like an independent organization awakened own consciousness, and forming its own structure according to business needs. Data scientists are widespread across the company, providing deep predictive insights into your data and targeted, relevant predictive analytics and recommendations to business users. They are making complex Analytical solutions available for daily users by designing flexible and easy-to-use models. As the quantity of gathered data increases dramatically, big data and unstructured data solutions appear in the IT infrastructure. This is the stage of scaling up.

6. BI as Air

The last stage of maturity focuses on optimizing your digital transformation in terms of organizational structure, how you are utilizing data and what type of analytics methods you are applying to transform knowledge to decision. Now you are fully equipped with an analytics ecosystem to answer questions like “How to decide?” and “How to prevent?” and to recommend the best course of action entirely based on data. By this time data is as essential to your decisions as air to human beings. This is what we call “BI as air”.

BI Maturity Model in 2020: Further insights

How to eat an elephant?

One bite at a time. Do not hurry or advance BI evolution because it will disrupt your business and sets back progress. A carefully designed BI roadmap may be slower, but ensures staying on the right track.

Never leave people alone

Let the early adopters evangelize, but do not let the tech-resistant colleagues lag far behind the company. We are prone to resist changes. “We have always done it this way.” – they tend to say. Key prerequisite for successful transformation is to drive change of organizational culture by empowering them with trainings and e-learning platform to become next generation BI power users.

The 4th dimension: Organization

These dimensions are continuously interacting with each other and therefore, must be handled together.

Be ready to internalize

Deep learning and Machine learning are becoming reality for many Companies far beyond fortune 500, while B2C mobile applications also bring IoT based recommender systems, hyper-personalization and real-time learning machines part of our everyday life. More robust and cost-effective big data platforms will foster uncovering deeper and more comprehensive insights to unstructured and dark data, that may result in bringing the pledge of Industry 4.0 benefits closer to medium-sized companies.

How Onespire Data Science and Innovation experts can help you?

We asses with you, which stage of the Maturity your Company is at from Data, Analytics, Business and Organizational perspective, and define an actionable Strategic Plan how to become from Good to the Best in your Industry without disrupting Business continuity. By progressing with the maturity stages your Business will get closer to leverage all Data as a Strategic asset to drive Customer satisfaction and Business performance and constantly exceeding the expectations.

Apáthy Sándor

Overview of the BI Maturity Model in 2020

Author: Sándor Apáthy

Data Science and Innovation Competence Center

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