For any business approaching a new data strategy, success is dependant on a deep consideration of every element in the process.
With all the hype surrounding data as the “gold rush of the digital age”, you’d be forgiven for thinking it was just that: hype.
The truth is, the gold rush analogy is pretty accurate, as those who arm themselves with the right knowledge, skills, and equipment can discover valuable returns, while those who go in unprepared leave empty-handed.
Even so, companies face numerous challenges on the journey to becoming data-driven businesses. These blockers include poor quality data, unmanageable data silos, insufficient technologies, lack of knowledgeable talent, and difficulty building a company culture that values this commodity.
The key to a successful data strategy is overcoming all of these challenges, not just one—if any are left unchecked then expect more problems down the line.
Technology is not the absolute solution
It’s common knowledge that technology is essential to the success of any data strategy, but it’s not automatically a golden ticket to success.
In order to scale, companies require sufficient data storage and processing capabilities, robust communication and analytics tools, and artificial intelligence or cognitive technologies to drive new insights and value. However, business leaders often expect too much from technology alone, viewing it as a “one-size-fits-all” solution to their numerous data challenges.
The reality is that technology—while indispensible—is only a small piece of the puzzle and many additional elements must be considered before a successful strategy can go ahead.
Developing a culture of data
In today’s digital world, proprietary data is frankly one of the most valuable assets owned by a company. The insights locked away in this unique information can be leveraged in so many ways to differentiate a company from its competition.
The challenge is ensuring the whole company understands and believes that, starting with leaders and decision makers.
From the top down, business leaders need to direct the company’s data philosophy by communicating its importance throughout the organization. This requires a paradigm shift in thinking, as leaders must embrace the unfamiliar and prepare the company for significant changes.Ensuring that the value of data is absorbed by everyone will make it part of the company’s DNA, helping to drive better business decisions throughout the organization. Click To Tweet
Trust is a determinant factor in creating this culture, as leaders often struggle to rely on insights from unstructured data. Developing this trust takes time and motivation, along with the talent and skills necessary to improve the quality and reliability of the data.
Bridging the gaps between departments is also essential in reducing the negative impacts of siloed data, such as duplication, lack of transparency, and difficulty sharing information. Department heads must prepare to move towards the same goals, ensuring that their efforts complement those of their peers—the alternative is high associated costs later down the line.
Ensuring that the value of data is absorbed by everyone will make it part of the company’s DNA, helping to drive better business decisions throughout the organization.
Maintain quality, increase value
While culture and technology play their part in the data-driven business strategy, they mean nothing if the data is poor quality.
Without polished, credible data, associated technologies can become pretty much useless. Bad quality data also leads to unhappy customers and makes it virtually impossible to execute an actionable data strategy without expert support.
For modern companies with digital DNA, the cost and effort to improve the quality of data is lessened, as their business models often consider this from day one. However, for more established companies that didn’t start with a digital crystal ball, the issue becomes more expensive and laborious to resolve.
There are often many root causes of bad data quality within an organization, from simple human errors to poorly designed data entry systems and forms. According to the Harvard Business Review, an average of 47% of newly-created data records have at least one critical error. This is a staggering discovery when you consider just how much companies rely on data to operate effectively.
A common misstep to determining the source of bad data or tidying it up is assigning the task to underqualified people. These kinds of issues require experienced data scientists that can analyze the issues, fix the problems, and ensure they don’t arise again. They can also advise on how to gain business advantages through data, resulting in new benefits and increased profits.
Without the right level of support, the long-term costs will far outweigh the relatively small investment, ultimately reducing the data’s value.
Leveraging multiple skills
Sticking with the topic of talent, data scientists are not the only necessary links in the data chain.
As previously mentioned, business leaders must take the reins when it comes to their data-driven strategy, corralling their teams toward the same goal and ensuring that everyone falls in line. Furthermore, there’s a need for people who can extract valuable data from old legacy systems and modernize business processes. This is further supported by experts who can create predictive insights from the data—the equivalent to finding a gold-bearing vein in the Wild West.
Then there’s the security element, often referred to as “defense”. This involves keeping data protected while following relevant laws and regulations, such as GDPR. The act of data defense is by no means profitable, but this level of security and knowledge is required to prevent issues down the line, saving time and money. Ensuring that the right professionals are on board to cover these considerations is vital.
Bringing it all together
A lot of effort is required to make this work: HR must plan how to train the whole organization, managers must prepare for change, IT departments must find and integrate the right technologies, security professionals must create the policies that protect the company, and leaders must tread unfamiliar paths.
The main takeaways here are that becoming a data-driven business is not merely a case of “going digital” or installing the latest plug-in solution; it’s about following a deliberate, pre-planned path that encompasses multiple aspects of the journey.
Whether a company is long-established or just starting out, the secret to a successful data-driven strategy is to look at the big picture. By ensuring that technology, culture, talent, organizational alignment, and data quality are all aligned with a far-reaching understanding of data’s value, they too can avoid finding rocks and start collecting nuggets of pure digital gold.
If your business wants to work with a trusted partner in developing and executing a sound data strategy, reach out to our team at email@example.com or fill out this form to start a conversation.