Strategies for Data-driven Organizations

Published: 26 Feb 2020

Time and again, it has been said that, to survive in today’s business environment companies should target their efforts in becoming data driven. A vast majority or organizations have actually taken cognizance of this and are striving to become conscious data-driven enterprise. Although many organizations think of themselves as data-driven, many lack the level of integration and change in organizational culture that is a requisite in organizations. This is the primary reason why companies are nowadays struggling with data overload & inefficiency in using the data accessible to them.

You have data, now what?

The trend of investment in big data and analytics has been swelling up with private equity and venture capitalists flooding the money in. But, just accessibility to data is not enough, the data acquired has to be put to use by constructive decision-making. Thus, there has to be effective strategy making at the other end of the spectrum for all the data driven organizations to exploit the potential that the data actually holds. While creative channels for acquiring data are in abundance now there is a need for quality sorting and getting crunched insights even when the data is from disparate sources.

Consider this as a long-term organizational goal to be 100% data intensive but in order to achieve that goal you need to ensure that you have the following ready,

You have connected all your complex data sources
You have the ability to share data swiftly via various dashboards, storyboards, applications etc.
You have data warehousing abilities (this is critical as the mass of data you will have to store in near future is only going to increase).
Analytical tools are in alignment with your managerial strength.
Capacity to crunch data and provide business intelligence at ease.
If you do haven’t ticked these boxes then every time you take a step forward to utilize the data for more you will be restricted by one thing or the other. If you have ticked the above boxes then congratulations, you are on the right path on using your data well but in order to do more it’s essential that you do more with data.

Strategizing with data

Effective strategizing with the data can transform the way business is done and speed up the problem finding and problem solving processes for companies. McKinsey & Company tells us that companies that have adopted data-driven strategies enjoy 5 percent higher productivity and 6 percent higher profits than their competitors. This proves that strategy making based on data can give an immense boost to your organizational performance. Now let’s have a look at what all can be done on an enterprise level to capitalize on the data.

1. Smashing the Silos:
After you have sourced the data from various channels, it so happens that there is departmentalization of the data, which leads to creation of data silos. This restricts an organization’s capacity to make the most of this data. To inhibit this from happening it’s essential that we break down these silos. For doing this, it’s essential that all the data sharing platforms are integrated and all teams have access to all types of data at any given time. For example, if the marketing team has access to sales insights, it will assist them in coming up with better marketing content to push the product portfolio. Similarly if the operations team has access to marketing & sales insights then it can implement production schedules by understanding which products are in demand more which in turn can help save on the inventory pile up and guarantee the product being at the right place at the right time. All of the raw and unstructured data has tremendous consumer behavioral insights which if considered while creating the business strategy of a company the results obtained would be tremendous.

2. Creating Analytical Models:
With the uncertainty of business outcomes at an all-time high, managers need to work with analytics models that can forecast and optimize these outcomes to the fullest. Once you have identified a business opportunity you need to build a model around it so as to increase the performance levels of that venture. Creating models based on a hypothesis and statistically reviewing it helps managers understand the crux of the data faster and assists in gaining actionable insights, which then enhance their decision-making ability. Clarity of thought acts as a byproduct here but doing any modeling exercise requires extensive investment in terms of time and can put practicality at risk. Thus, executives need to understand which model can serve them the most with the least amount of complexity.

3. Leveraging Capabilities:
Achieving and maintaining a level of balance between your human capital and technical capabilities is paramount. Only when you have achieved this can you then leverage the potential they carry. It is not pragmatic to bring expensive data driving systems onboard when you haven’t got the human resource with the right skill set to drive it. One of the primary goals can thus be working towards building a stable bench of analytics professional within your company, which can be backed with continuous training and development to maintain the efficiency. Creating platforms, which can be easily accessed by the employees to draw and use data, is essential. It calls for an advanced backend infrastructure and improved front-end capabilities like report generation and visualization. Once the above is done and your data strategy is aligned with the business strategy then the opportunities for value creation are endless.

4. Agility + Security + Quality:
Failure in creating a feeling of data drive in your organization and a poor data governance structure can turn out to be catastrophic for any enterprise. To protect your company from this it’s imminent that 1) there is a clear definition of business outcomes known to all and 2) clarity in terms of accountability i.e. there should be no miscommunication in understanding the ownership of work. Integrating business workflows with employees accompanied with a strong compliant data governance structure will only certify higher efficiency for any organization. The right amount of vigilance also keeps quality of work in check and maintains discipline.

Conscious efforts in incorporating good data driven practices in your organizational culture will serve the organization in the long run and increase the adaptability to any changes in the near future.

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