Truth, in our times, is one of the most expensive pleasures.
Because without truth, it's impossible to achieve Significant, Manageable, and Effective Business Growth.
Knowing the truth and accepting it allows you to confidently take off: set goals (that won't change in a month) → choose priorities → see your resources and opportunities → formulate available options → start moving.
So, let's talk about Significant, Manageable, and Effective Growth.
Significant reflects the scale of your growth compared to the other players and the market itself. Once you have data about the market, the current size of the business, growth prospects, and competitors, you can formulate what significant growth is and what insignificant growth is.
It's important to understand that the significance of growth is not about how much you grew last year. It’s about you being ahead of or behind the market dynamic, how others are growing, etc.
Managed growth means sustainable growth. It supposes you understand the metrics that create growth, and the resources that can influence these metrics.
Effective shows the cost at which this growth comes to you. The cost can be both financial and personal, e.g. how much stress and emotion was spent on achieving the goal. You wouldn’t want to achieve a goal if it implied you being sick of working and having to spend a year on recovery, and the team burning out. Long-term growth in stress is impossible.
Knowing the truth allows you to achieve all three:
You’re very likely to spend 90% of your time collecting data, verifying and understanding it, and only 10% of your and your team's resources improving it and brainstorming.
It normally takes a lot to change this situation. However, once you succeed – and make the data collection process automated – you transform your company into a self-driven business.
This can be achieved only with a clear understanding of the metrics that influence your outcomes, the ways you can amend them, and up-to-date, precise data.
Self-driven business is like a self-driving car: you only have to control the destination (business goals) and the level of comfort (risks). The rest happens without your participation, as the car (your business) has a comprehensible set of tools to arrive to the destination (achieve said goals).
These same stages are the Data Maturity levels of the organization.
The stage of using Excel spreadsheets and basic free visualization. Usually, the data is collected and updated manually. Information from different data sources is not connected. The question of automating data collection arises, as well as the need to analyze different data sources.
You have multiple dashboards, which do not match each other and the company is dying in the search for truth. There are many truth centers and many truth definitions. Different departments calculate metrics differently. The cost of searching for the truth becomes very high.
The tools for standardizing metrics and dashboards are introduced, moving to a single seamless data stack. A basic data catalog is implemented. The stage of proper monitoring of metrics is tidied up and completed.
The monitoring of main metrics is established and the question of forecasts arises. The leaders want to manage not the actual values of today but the calculated forecasts, want to understand trends, and want to look ahead to understand in advance how the current difficulties they have today affect their short-term and long-term goals.
At this stage, great attention is paid to the tight connection and description of the business model with data models. The final stitching of the business model and data models that the business has, and absolutely all indicators of departments: marketing, sales, product, support, finances, operations, HR, IT, and even legal departments are stitched together.
Here, the manager receives not just a set of suggestions from subordinates but a set of modeled solutions with different effects, terms, budgets, and speed of effect and most importantly with a calculated final effect. The main problem is
The priority is the speed and efficiency of decision-making. It's important to generate ideas based on forecasts and existing information. Everybody searches for unconventional, interesting solutions for very well-formulated goals and a set of data.
The beginning of the collection and registration of all adopted decisions for subsequent assessment of their effect.
A business where the set of decisions and models are generated by AI, not humans.
The main challenge is the quality of the proposed AI models, meaning the collection and training based on the decision options of current systems, as well as the integration of the maximum amount of additional external data for decision-making. Also, the creation of digital Advisory Boards, which consist of dozens of deep experts in their fields and industries who help train decision-making models in companies. It's important to have a history of decision-making with assessments from the previous stage.
To sum up: everybody wants to grow, and significant, manageable, and effective growth is impossible without a data backup. The main tool to provide comprehensible and actionable data insights is a dashboard. It allows you, as a business leader, to understand what the company is going through at the moment and where it’s headed in the future. So basically, that’s what we do.
Feel free to visit us and get a complimentary 30-minute data consultation + your first data task for free: data-never-lies.com.
