Businesses are accumulating data in record quantities from sensors, web analytics, cookies, and apps, but a considerable number of companies do not have the experience to distill that data into valuable insights. It is widely accepted that we’re in the age of data, but skills and expertise regarding data interpretation still lag behind. This discrepancy created one of the most exciting trends in business: Insights as a Service (IaaS). While the market is still in its early stages, researchers estimate a 24.2% compound annual growth rate (CAGR) between now and 2024.
Established businesses and entrepreneurs are seizing this opportunity to transform expertise into a product. Companies strive for data-backed decisions and strategies, and third-party IaaS partners make that possible. Before launching an IaaS business, or branching into the field, first consider the best practices that differentiate top performers from the rest in this emerging industry.
1. Narrow the objective
For any analytic endeavor to achieve meaningful results, it is imperative to focus on a clear business problem. An example could be customer churn on an eCommerce site or a specific section of the sales pipeline within a CRM. While it’s possible to address multiple challenges, if the parameters are vague, then the insights won’t produce the desired effects. Invest time upfront developing narrow objectives.
2. Manage expectations
Companies are already investing 15% of their IT budget on IaaS and that number is expected to double in the coming years. While it’s important that clients can afford IaaS services, it’s equally important to prepare clients for the possibility that insights might reveal an expensive opportunity. Ideally, minor tweaks would create big results; however, it’s not unusual for data to reveal the need for changes to core infrastructure and tired business models. Some businesses may jump at the impetus for change, but others may find the challenge uncomfortable. Becoming a data-driven company certainly has its benefits, but it also requires stakeholders to take measured risks.
3. Source strong data
Reliable information science requires strong data. While many companies sit on a wealth of data, it’s still best practice to gather third-party data from industry resources and competitors. A study by IDC found that over 70% of companies already used third-party data and predicted that number to approach 100% in the near future.
Gaining a 360-degree global view of a circumstance creates the prowess necessary to confidently pursue a new trajectory. People famously say that hindsight is 20-20, but with proper data preparation foresight becomes competitively clear. Do not skimp on the data collection; rather, focus efforts to compile the most robust sets possible.
4. Break the silos
It’s common for businesses to analyze data from within particular segments—marketing observes customer data while operations focuses on process data—but this can lead to predictable low-value results. Businesses are increasingly discovering relationships between data typically separated into distinct silos. For instance, customer service data may provide insights relevant to sales while supply chain data may inform marketing. These transcendent relationships release fresh strategies invaluable to enterprises and are the exact type of outside-the-box perspectives sought from third-party vendors.
5. Make a sound case
After processing and analyzing data do not rush to clients with half-baked results. Companies ready to enact drastic shifts still expect a thoroughly-considered deliverable; no company would back a strategic shift without firmly comprehending the underlying reasoning. Spend proper time and effort translating insights into digestible graphics that present concise conclusions. Prepare to answer direct questions relating to the methods and algorithms behind a given insight and include expert team-members in the conversation who can explain their findings. A thorough delivery creates trust among partnering companies and paves the way for a mutually successful relationship.
6. Use revolutionary thinking
With data science, big data, artificial intelligence, machine learning, and the IoT being all relatively new for many industries, old business models are quickly being upended and replaced. When leaders invest in IaaS they’re fighting to become part of the revolution and not to be left behind.
Don’t settle for menial results; discover unconventional realities to drastically change the game. Revealing minor operational tweaks is valuable, but discovering entirely new ways to do business is invaluable. Not every project will yield groundbreaking results, but business leaders should continue to seek revolutionary breakthroughs and soon enough they will emerge.
Breaking into an emerging industry
As IaaS continues to expand and evolve, expectations and products will become more defined. Like any gold rush in history, by the time the saloons are built the gold is already spoken for. Whether branching into the IaaS market or launching a startup, now is a perfect time to take bold steps and create solutions that stand apart from the rest. This new market will not be defined by flashy websites or catchy phrases (although those are both helpful), it will be the industry-shifting ideas and newly discovered opportunities that win the day. Millions of businesses are in need of quality insights, large and small, and partners providing the in-demand expertise are a welcome boon in this adapting economy.