“Culture eats strategy for breakfast” – Peter Drucker
Institutionalizing the use of any tool or technology in an organization steeped in existing ways of working is often the hardest part of a transformation effort. Adopting new ways of working requires a different mindset. No matter how excited executive sponsors and IT leaders are when a new set of tools are introduced, one cannot assume their automatic adoption by line workers and managers even though the tools may make their jobs easier to do. A business attempting an Industry 4.0 or Analytics transformation will be plagued by the same challenges that come with any other type of transformation.
Now, if you read Peter Drucker’s most famous quote again, it should be apparent that strategy should include a cultural transformation. For the sake of this article, we will focus on data strategy, and the cultural transformation required during execution.
Let’s ponder over the following questions first:
- What does it mean to be data-driven?
- Why should a business care about being data-driven?
- Who benefits from being data-driven?
- What are the key considerations for a business when it wants to be data-driven?
- What cultural changes need to be implemented to achieve transformation goals?
What it means to be data-driven
Simply put, being data-driven means using data to make decisions. A small business may rely on the owner’s or manager’s intuition to make decisions because of their experience. This model does not scale as the business grows to become mid-sized.
A larger organization with more workers, managers and locations requires using a business intelligence solution to make decisions. Detailed customer, supplier, product, raw material, and transactional data along with a handful of key metrics are the typical requirements to make decisions. At the very least, managers need to be able to explore and communicate with the data their departments generate or share with their peers.
Why care about being data-driven, and who benefits from it
The right decisions at the right time benefit customers and the employees of a business. A company could try to motivate its employees by empowering them to meet mutually agreed-upon goals. Data helps a business set the right goals, and determine whether or not each department is on track to meet its goals.
Being data-driven does not mean discarding experience, intuition or the knowledge of market situation. Data does, however, help you explain your decisions up and down the hierarchy and across the organization. It also helps a business determine the efficacy of existing processes, and make continuous improvements over time.
Key considerations to become data-driven
- Less is more: A handful of Key Performance Indicators (KPIs) are better than tens of KPIs per department. KPIs lose their meaning and utility if they proliferate. A typical department does not need more than five KPIs to demonstrate its performance. Here’s what we mean: A business will need measures for each product, but it needs one KPI for a product category. Even if there are a hundred product categories, the KPIs of interest will be top 3 product categories by sales, and similarly, the bottom 3 categories. Here, we draw a distinction between measures (or metrics) and KPIs.
- Implement KPIs across rank-and-file: Employees across rank-and-file should be responsible and accountable for the same set of KPIs to improve transparency in decision-making. The higher the leader is in the organization’s hierarchy, the greater the aggregation of the KPIs. If department leaders and line workers track different sets of KPIs, decisions made by the leaders will be out of sync with business reality.
- Tie measures to overall business health: Measures are used to track the health of business activities, and should indicate a relationship with revenue growth, profitability, customer satisfaction, brand loyalty, or employee engagement. E.g.: Production line throughput and equipment downtime have direct impact on revenue, a KPI. Labor cost affects profitability, another KPI. Online ratings affect customer satisfaction, and long-term brand reputation. Number of sales calls made per day impact orders received and therefore revenue.
- Analytics as a capability: Analytics projects are not a once-and-done deal. 100% adoption of all the defined KPIs across all the departments and their respective hierarchies is an unrealistic expectation. In fact, business and IT leaders should expect their company to go through an iterative process involving ongoing feedback loops to determine the adoption of KPIs by the business, and their utility. Therefore, analytics needs to be treated as a capability or a product, not just a transformation project.
Cultural changes needed to be data-driven
Aside from teaching line managers and business executives how to use analytical tools, they need to feel motivated to continue using KPIs and measures to drive decision-making and provide feedback to improve processes, refine KPIs and measures, or define new ones. At a minimum, the most important KPIs should be part of managers’ annual performance goals.
Line workers or employees at lower levels should be rewarded and recognized for the KPIs their department meets or exceeds. Public recognition at town hall meetings or in monthly newsletters for meeting or exceeding key KPIs is the best way to motivate employees. Employees demonstrating exceptional performance, with KPIs to back them, should be considered for promotion.
In sum, instilling a data culture should be a core part of any transformative data strategy. Without this understanding, your Analytics transformation effort will join the graveyard of failed projects, and your company will not be able to achieve its goal of being data-driven.
Refer to the following resources for further reading:
- Why data leaders struggle to produce strategic results, a CIO Magazine article
- Data literacy explainer by Tableau
- KPIs explainer by Investopedia
