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How to make change management happen in the most effective way

Many things can put your business at risk, including changes to your organisation, people or technology. The current pandemic has put many businesses under unprecedented pressure, and some even teetering on the brink of survival. Crises like this quickly turn change...

Future-ready part 2: Diversity – an essential ingredient for a future-ready organisation

In his seminal 1937 essay, “The nature of the firm,” the economist and eventual Nobel laureate Ronald Coase argued that corporations exist to avoid the transaction costs of the free market. Yet with transaction costs plummeting (spurred by rising connectivity)...

Future-ready part 1: What does a future-ready business look like in the new normal?

The pressure to change had been building for years. Well before the COVID-19 pandemic, senior executives routinely worried that their organisations were too slow, too siloed, too bogged down in complicated matrix structures, too bureaucratic. What many leaders feared,...

Organisation Design: Restructuring or Reshuffling to enable Strategy

Customer expectations are not just changing; they are exceeding the ability of a business to deliver on time. They are looking for alternatives, with more emphasis on experience and convenience. To keep up, companies are evolving their offering to meet the...

How to fill the gap between Strategy and Execution

Organisations are great at setting their strategy and identifying their goals, but they fall short when it comes to their operating model review and redesign, the key component that enables the strategy and drives the achievement of goals. Operating models consist of...

Culture PART 2: The role of leaders in a culture shift

In the previous article in this series we examined the effect of COVID-19 on an organisation’s culture. Now, we turn the focus onto the role of leadership and technology in leveraging culture. When an organisation decides to change its culture – be it planned or...

Culture PART 1: Did COVID-19 signal the end for hierarchical organisations?

According to the Organisation for Economic Co-operation and Development, human capital is defined as: “the knowledge, skills, competencies and other attributes embodied in individuals or groups of individuals acquired during their life and used to produce goods,...

Meet MAC’s Executives: Karina Jardim, Senior Executive

“Exceptionally talented consultant” “An absolute pleasure to work with” “Driven by a desire to see people grow” If you know Karina Jardim, you know that these phrases used to describe Karina ring undoubtedly true. She is a name that is valued to every MACer, whether...

Thriving in the Age of Digital Adoption: Embracing the Workforce Ecosystem (part 2)

In the first part of this series, we looked at how the fears of technological innovation are resulting in an unproductive resistance toward modernisation, even as it gains extraordinary pace in 2021. We also delved into the importance of a growth mindset in allowing...

Thriving in the Age of Digital Adoption: Overcoming the Fear of AI (part 1)

“What if artificial intelligence takes over my job? What if I become redundant?” Every one of us has experienced technology encroaching on our lives, more and more so with each year that passes. It appears that technological innovation is a certainty that is only...



Mac Consulting

The ‘Sit. Crawl. Walk. Run.’ Principle that drives data and analytical maturity

The ‘Sit. Crawl. Walk. Run.’ Principle that drives data and analytical maturity

Biological and intellectual advancement in human beings follows a set pattern, as does implementing data analytics into a business.

Unfortunately, many organisations want to rapidly ascend from having no analytics to having mature predictive analytics. Often, this revolution-based approach fails to realise the importance of data and analytical maturity. Instead, an evolutionary-based approach following the ‘Sit. Crawl. Walk. Run.’ principle will yield better adoption and results.

Organisations are investing heavily in data teams and solutions, but often fail to realise the importance of building a solid data foundation, first and foremost. Heavily investing in data and analytical capabilities will only yield fruitful (and tangible) results if the teams driving the adoption thereof acknowledge the value of incrementally showing the business value.

Incremental value delivery is very important.

Understanding the Analytics Continuum, and how it provides a guideline for incremental value delivery can help guide your organisation to correctly apply the ‘Sit. Crawl. Walk. Run.’ Principle. Ultimately, the main goal is to build the foundation first, before adding your walls, windows and roof.

Step 1: Descriptive Analytics – Observing

The ‘what is happening here?’ step.

In an immature environment this should be step 1 (Sit). The foundational building block of data and analytical maturity emphasises that the first step towards data evolution is to start measuring what is happening – the ‘Understanding’ phase.

Step 2: Diagnostic Analytics – Analysing

The ‘why is it happening?’ step.

Unpacking an issue or opportunity is extremely important, and the data analysis can deliver tangible data-driven insight in step 2 (Crawl). Leverage your data to tell a story, diagnose a problem, and inform the business on insights that will deliver operational intelligence and assist in effective decision making.

Step 3. Predictive Analytics – Signalling

The ‘if I do X, I can expect Y to happen’ step.

The fancy ‘buzz word’ that everyone wants in their organisation. The step towards maturity places the emphasis on exploring hidden patterns in your data that might be too difficult to spot with the human eye (Walk). This is a playground where predictive solutions can leverage Big Data to deliver data science models that predict customer churn, forecasts stocks, or determines the optimal route for logistics.

There should be some rules on the playground though – it is great that your team wants to deliver predictive solutions, however, solutions should solve real business problems and not just be shiny cool toys that add no business value.

Step 4. Prescriptive Analytics – Acting

The ‘if I want to achieve Y, I must do X’ step.

All those observations and predictions are great, but how do we get concrete actions from this? It does not stop at only predictions. With Prescriptive Analytics you will create concrete advice about what should happen, including directly putting it into practice (Run).

Yet none of the steps can be skipped, and neither should they be rushed if you want to collect meaningful data. Map the steps out, build the foundations and move methodically, as each step informs the next. You will start to sit up straight as you transition through the maturity model, and certain aspects or systems which need to be put in place to help you get to the next step will see you learning to crawl, then walk, and then run.

Learn to sit before you crawl, crawl before you walk, walk before you run.

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