When identifying opportunities to innovate in today’s world of evolving technological and societal change, following the traditional development path can lead to costly setbacks.
“We know what to build– we’ve built products like this before – so let’s just go build it.”
Throughout our nearly two decades of helping businesses design and build innovative products, we’ve heard statements like this from time to time. Relying on past experiences for developing new solutions is understandable, but can be also misguided.
On one hand this type of statement reveals a level of excitement and a desire to innovate, or at least to attempt not falling behind their competitors. But usually there’s something else at play.
That something is an assumption that what we’re about to build together already has a clear blueprint and we should follow it. Worse, there’s a hint of arrogance to suggest the investment and hard work someone else put in to develop their solution isn’t necessary for us in order to compete against them. The irony is that every company knows they don’t simply want to match their competition – they want to win and emerge as a market leader.
So, how do you win and emerge as a market leader? By providing valuable business offerings that meet, or better yet exceed, customer expectations. And data is the key to unlocking that value.
In fact, Forester’s 2018 report indicates that data-driven companies that harness insights across their organization and implement them to create a competitive advantage are growing at an average of more than 30% annually and are on track to earn $1.8 trillion by 2021.
BARRIERS TO DEVELOPING A CUSTOM DATA STRATEGY
Most business leaders will agree that data is critical, and that data from their customers and their specific applications is the holy grail for generating new business insights. So why would companies even consider foregoing collecting customized data as they attempt to chart new ground with an unproven product?
We see four common barriers that cause companies to be hesitant to invest in data collection up front. We know these barriers are real and don’t take them lightly:
- Time – it can feel like the project timeline is being delayed by this up front step but, it pays rich dividends in the end
- Cost – capital investment in manpower and data collection tools can be significant
- Tools – often the tools needed are not “off the shelf” so new tools must be designed and built often by outside experts
- Discipline – working with data is different than traditional product development and demands a commitment to a tedious and detailed process
While every project is different, we make a point to show how data-driven development has led to end product success within budget parameters. But we also point to those few times where we’ve been wooed against our better judgment to run ahead with strong assumptions or unproven data until the inevitable problem rears its head. These are learnings that don’t need to be repeated.
By delaying the investment in curating reliable and a specific set of data the key insights that drive innovation are often missed. And so a rather obvious choice presents itself: proactively invest in custom data gathering or reactively invest even more dollars and time to rectify the poor design choices that occur based on bad assumptions.
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DATA – IT’S ALWAYS AT THE CORE
To offset these challenges two ingredients for success are needed. First a solid belief that the data holds value. And second, a development process that puts data at the center of your efforts.
It starts with a hypothesis that a data set holds new business value (prediction, decision making or insights). The process is a series logical steps where the data is used to both direct the algorithm development and to objectively evaluate the system performance, proving or denying the hypothesis.
Data driven development is a rigorous process for effectively managing the complexities of statistical decision-making (AI) systems:
Starting with a small data set and rapidly repeating the process with feedback from previous runs builds confidence in the hypothesis, directs clear course corrections or proves the hypothesis wrong altogether. In any of these scenarios the key value gained by the data driven process is the decision-making confidence produced.
BENEFITS OF CURATING YOUR OWN DATA
Beyond just confidently finding the right path or avoiding the wrong path, your data development strategy is about securing your digital future. When you embrace a data development strategy, you want to know that doing so will get you to your end goals. Three benefits make the data strategy decision an easy one.
- Higher success rate boosts brand. Data that accurately reflects your target environment dramatically improves the success rate of your offering. It boost confidence that your offering is working as intended. When hypotheses fall apart after deployment because bad assumptions the brand value of your offering is undermined at a significant cost in time and money.
- Adaptability to new offerings. Embracing the data development strategy also affords a team to adapt the offering to changes and advancements and on the fly. As new data comes in from the field , surprises and unforeseen variables in the data will no doubt arise. Because the process is iterative, the offering can be confidently flexed to accommodate ever improved and optimized solutions.
- Success trumps speed. Eighteen years in and we’re still waiting for the first client to say – that sure went fast. Truth is innovating with data is hard. The path to innovation isn’t a straight one, it’s a winding journey through challenging twists and turns. Basing development on the traditional way may doom your innovation to an endless do loop. But by committing to a data driven development strategy up front will deliver the payoff will be innovation realty. When dealing with data, It simply needs to be viewed through a long-term commitment rather than a quick fix.
We all want our assumptions to be true. But we also want our businesses to thrive, and thriving businesses don’t credit their success to assumptions and intuition alone. They test those assumptions. Jerry Belson, a Hollywood writer and director popularized a tongue-in-cheek definition of what it means to “assume” in the early 1970s with this clip from The Odd Couple. It’s a perfect explanation of why assumptions about data, or any other aspect of business, isn’t a winning strategy.
And if you’re ready to take the first step in building a data-driven development strategy, we invite you to reach out and hear about our process and how we can help you unlock new value for your company and your customers.