Do you feel comfortable making critical business decisions?
Can you act with confidence of the outcomes based on past performance?
Companies that use a data-driven approach can make more informed decisions, rather than depending on gut feelings and broad trends. Data can help leaders create strategies and make decisions that are rooted in evidence.
Companies that use information to drive decisions are data-driven organizations.
A financial services firm was experiencing success in customer acquisition and has been adding new clients consistently over the years.
Client breakdown identifies the most profitable clients between the revenue earned from and the costs associated with the customer relationship.
The focus on customer satisfaction resulted in the team being far over capacity and struggling to find good methods to address the scaling bottlenecks. The lack of visibility into the client breakdown was a result of data being spread across multiple systems, missing, incomplete, or inaccurate data, and difficulty in getting the information together.
The leadership team identified the need for a new way to view customer details that would allow actionable steps and results.
Consolidation of client data such as invoices and timesheets, provided leadership perspective on information that was previously difficult to understand. This allowed the organization to address the main causes of non-profitable customers and support the company on capacity issues.
The actionable insights resulted in immediate savings of 20x return per year, the identification of ideal customers, and the visibility to scale as needed. In addition, some simple systems integration streamlined operations and employees got their weekends back. All-in-all, the team can make critical decisions faster and keep up with the pace of business.
Business intelligence and data analytics are the opposite of instinct and intuition
Data-driven decision making uses data that is collected and analyzed to make strategic decisions based on the insights derived from the collected information. It uses past information to predict what is going to happen in the future.
Without objective data, there is a risk of acting on false assumptions and being swayed by biases.
Every data-driven decision-making process requires setting up Key Performance Indicators (KPIs) and other benchmarks that will follow the KPIs. KPIs are quantifiable measures of performance that help businesses to track their progress and see how close they are to achieving business goals. There are dozens of KPIs and value metrics of whose purpose is to measure the performance of systems and their business impact.
If you are using data to make decisions, then you are a data-driven organization and you will benefit from the practice.
Data-driven organizations will enjoy the following results:
Know how your company is performing
The amount of understanding by simply pulling data from your systems and making it visible is staggering. When executives have easy access to financial, customer relationship, and resource planning data they will have objective understanding to the health of the organization rather than just a gut feeling.
It’s one thing to access your business information, it’s another thing when that data is accurate, accessible and includes historical context. With that in hand, users can make better, more solid decisions and diagnose root causes faster. That in turn leads to more sales, more targeted products, faster response times, and a tangible advantage over your competitors.
A data-focused mindset
Organizations that transition to a data-centric mentality, tend to become much more objective in identifying root causes or opportunities to pivot. By focusing on the data, emotional responses, political agendas, and finger-pointing become relics of the past.
Accessible and accelerated business exploration and decision making
By running what-if scenarios without disrupting your business, you will have a high probability of accurate results.
Forecast with confidence by knowing how to measure outcomes, recognize the trends, and understand their causes.
Bob is the CEO. He has company data spread out through his CRM, Accounting, ERP, and HR systems. Bob’s team are experts in their respective areas, but the data is siloed and while each department has their own KPIs, it is hard to know how the company is doing overall. In addition, while the company has been doing well financially for years, Bob has a sense that there might be more efficient ways of doing things.
Bob begins the journey by identifying mission-critical metrics and KPIs. He works with each of his department leads to come up with 2 or 3 measures and they agree on the definition of each, where and how they can get the information and how often it makes sense to measure (weekly, monthly, quarterly).
Finally they agree on a process and a cadence to review the data. Bob’s company has taken the first steps to use their data to get insights and make decisions. In preparation for next steps, the decide on a shared platform for storing and visualizing their data across the organization.
Now that Bob has a process in place, he decides that understanding the Sales pipeline and effectiveness are a good place to start. Since the team already knows how to source the key metrics, they start off by identifying some leading and lagging indicators.
As they capture and report on the data, the team now has an understanding of their current Sales health. As historical data flows in, trends start to emerge and they start to see the impacts of changes in the business over time.
Bob is amazed at how much he has learned about his business in just a short amount of time. He tasks the Sales team with creating a plan for doing deeper analysis and identifying another set of metrics.
The following months
With the success of the Sales team’s metrics, Bob tasks his other departments to start doing similar analysis. The teams, learning from the Sales department trials and errors, identify key indicators and measures, and capture from their systems so the data can be made visible.
The team now has a number of dashboards, and they are referenced in meetings and emails. Bob notices the meetings are shorter, more productive, and there is a lot less finger-pointing.
Making informed decisions is an outcome of drawing conclusions from the insights gathered from the company’s data. Armed with information, Bob decides to pull the trigger on an opportunity that has been in the backlog for a while and is now supported by past performance.
The following years
They are reaching their target audience, investing in the right areas and headcount is increasing but productivity is through the roof. People are focusing on handling edge cases and exceptions, not the day-to-day report creation, data wrangling, or manual processing. Company morale is high, because people are doing high-value work and not fighting with each other.
Bob is considering going all in and looking into Artificial Intelligence (AI) to help further analyze historical trends to optimize the decision process and make better predictions.
Commit from the executive level to transform your business into a data-driven organization.
Capture, process, and review company data from across the organization (external data as well).
Create an execution plan that considers building, measuring, and learning using small iterations and change management.
Pivot quickly and learn from incorrect assumptions. Identify and document good decisions as organizational best practices.
Find the right partner to help execute walk through the process.
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