According to the International Data Corporation, global spending for big data and business analytics solutions is forecast to reach $215.7 billion in 2021, representing a 10% growth over 2020.
However, a quick internet search for “how many companies are data-driven?” renders conflicting, if not downright perplexing, search results.
Topping the page is a link to a recent Harvard Business Review Survey showing:
- 72% of survey participants report that they have yet to forge a data culture
- 69% report that they have not created a data-driven organization
- 53% state that they are not yet treating data as a business asset
- 52% admit that they are not competing on data and analytics
Scrolling a bit further down in the results, a key finding from Forrester jumps out: “Organizations adopting Data Intelligence were also 58% more likely to exceed their revenue goals than non-data intelligent organizations”.
How can it be that so many organizations are investing exorbitant amounts of money, but so few have yet to realize a return on investment?
Harvard Business Review offers some insight into this dichotomy by writing: “Only 7.5% of these executives cite technology as the challenge. Rather, 93% of respondents identify people and process issues as the obstacle”.
Companies now have a plethora of tools available like Microsoft’s Power BI to aggregate, interpret, and visualize unlimited amounts of data. There are also marketing automation platforms to harness this intelligence and build out personalized customer journeys at scale and with precision.
The truth is, most companies are not yet ready to successfully adopt data-driven business practices. More specifically, their data is not there yet. Organizations attempting to implement data-driven methods where processes and procedures do not support such an effort may be doing more harm towards reaching that goal.
The good news for executives and stakeholders who are looking to transform and chart out their own paths is that by articulating the value and evangelizing for best practices, change does happen. Albeit more slowly and incrementally than we would hope.
With this in mind, here are a few points to consider and hopefully help navigate, what can be a long and winding road:
It’s the journey, not the Destination.
- A company’s culture and processes cannot be reversed overnight. Any organization that has minimized the value of procuring, archiving and maintaining its own data is susceptible to incomplete, duplicate and/or obsolete business intelligence. This presents major challenges, if not completely derailing any efforts for near term, effective data-driven decision making.
- Unfortunately, there are no quick fixes or shortcuts. Data sanitization to ensure validity takes time. It also requires a strict adherence to uniform and comprehensive data collection procedures for the entire organization to follow. (As an example, when sales loses a deal, are they utilizing the “competitor” sections in CRM to capture competitive intelligence? The very type of information that can be leveraged for training, product development, sales collateral?)
- Compounding the problem, messy and incomplete data does not magically disappear. A fact that culminates with many companies purging existing data and simply starting over.
- Other organizations may take a more moderate approach in making efforts to piecemeal data, close gaps and provide missing context. Sales reps retroactively filling in empty CRM fields from memory can be a common technique deployed in this situation.
At this point, it may be appropriate to take a step back to define and prioritize what data points are most important to your organization. Plan for all possible scenarios, asking yourself:
- Does the data exist?
- Is it accessible?
- How can it be acquired?
- What data is important and what is noise?
- Can I make an informed decision with less than complete data?
- How should I weigh this input in my decision making?
After those considerations, you may also want to assess: What systems and employee skillsets will be required to be fully data-driven? Is this process sustainable? Repeatable? Flexible enough to adapt with change and disruption?
We would love to get your feedback—what has been your experience in making your sales and marketing team a data driven organization? Reach out to us at email@example.com!