3 Challenges of Big Data in Business Development 2 years ago

The business development landscape has changed. Information spreads faster than the common cold. Automation and artificial intelligence have raised the bar on getting a foot in the door, leaving business development teams scrambling to keep up. As with any problem, the first step in solving it is recognizing you have one. Truly realizing one of the larger stumbling blocks to modern business development calls for an examination of its smaller parts. In other words, if we want to understand the whole problem, we need to understand the individual challenges. Let’s take a closer look at the three prevailing hurdles to business development in the information age.

Key Findings

“Big data” is not useful data unless you know how to extract actionable intel.

Raw data is meaningless until it is analyzed and interpreted, allowing for the articulation of actionable insights.

Insights must be acted upon in ways that exceed the high expectations of prospects in the wake of recent advancements in personalized marketing.

Business development teams who cannot efficiently synthesize big data into actionable insights are struggling to compete with those who can. Limitations in analytical capacity are often due to a lack of resources; human or technological.

1. The Illusion of Big Data

Big data does not equal useful data. For as much data as there is, floating around the internet in 2019, none of it matters to sales teams unless it can be acted upon. Actionable intelligence demands the alignment of three integral factors.

First, the content. Information and metrics are the building blocks of actionable insights. You can’t build a first-rate house with second-rate bricks; likewise, you cannot act effectively on low-quality data.

Second, the context. If content constitutes the “blocks” from which actionable insights are built, context is the blueprint. Context provides structure, narrowing the scope of information to fit both individual goals and the circumstances in which they’re met.

These circumstances may be external—regulatory rollbacks, revisions, or expansions; a shift in the competitive landscape or economic climate; and other such market conditions which favor specific segments and verticals.

However, they can just as well be internal—quarterly revenue goals; pressure to upsell, add value, or increase billable hours; or a shift in products, services, or market conditions which favor specific segments and verticals.

Third, the people. People—operating within the circumstances of their respective markets—drive individual goals, dictating the context which enforces a structure on the content.

This relationship traces the connective thread between action and intelligence, begging the question: “what role does big data play in this nexus?”

Big data is content. Content, whether it be of poor quality or poorly-suited to the context of the business development landscape, can render BD teams—the “people”—less able to take effective action. Like we said, “big data does not equal useful data”. It’s only useful data to those who know how to use it, and therein lies the problem.

2. The Reality of Raw Data

Raw data is only the beginning. After content has been contextualized for relevance and curated for quality, a sizable amount of analysis remains before can be considered “actionable”. This analysis involves the identification of patterns and, from those patterns, the articulation of insights; both of which requiring more statistical acumen than a few business development teams have at their disposal. Raw data is meaningless without the ability to synthesize it into something capable of guiding impactful decisions. Absent the human or technological capital to get from Point A to Point B, business development teams are fated to find themselves stranded at square one. In this way, companies with the resources to invest in research personnel or intelligence software have a significant advantage over those with limited analytical capacity.

3. The Rising Expectations

Despite the drawbacks posed by poor-quality data and the constraints of inadequate analytics, prospects’ expectations continue to rise. The creeping expansion of new technologies has made it easy to create the illusion of a meaningful connection. Improvements in automation and artificial intelligence have raised the bar on personalization; prospect expectations growing ever harder to exceed. AI-guided ad targeting, automated nurture campaigns, chatbots that address you by name; these new toys are shiny, yes, but their prevalence has made them easy to spot. To go above and beyond, in this context, is to find a unique means of understanding prospects’ needs. Rather, it means creating the appearance of unique understanding; demonstrating an awareness of objectives, obstacles, and opportunities prospects perceive as having been gathered through earnest research. This perception plays a pivotal role in distinguishing companies who care for clients’ needs from those interested only in streamlining business development workflows. At the same time, it puts sales teams in a catch-22:

  • Putting in the time to gain a comprehensive insight into prospects’ needs steals focus from other activities necessary to secure new leads.
  • Advancing prospect relationships without this research makes it difficult to stand out from the crowd and turn leads into clients.

Efficiently leveraging competitive and market intelligence can streamline the development of deeper understandings. However, cultivating the knowledge to advance a business development conversation requires less research than knowing how to start one. Identifying the common priorities and pain points of a given vertical requires little more than a basic understanding of the industry. Emotional intelligence and quick thinking are all that’s needed to anticipate those needs while in discussion with a prospect. This won’t hurt the chances of converting a prospect, but it’s not impressing anyone either; even when that knowledge is backed by great intel.

Successful business development teams set themselves apart by contextualizing common needs and concerns with the latest news, data, and industry developments. The resulting insights are used to shed light on potential risks and rewards before they’re on a prospect’s radar. This tees up the business development team to position products as being vital to the pursuit of these issues; evading the risks and capitalizing on the rewards. At the same time, it demonstrates a meaningful understanding of prospects’ needs and concerns; extending beyond the formulaic personalization features of a sophisticated marketing tool.

Together, these challenges form the basis of a fundamental obstacle to modern business development. The increasing availability of information has split competition between firms, dividing companies by the efficiency and effectiveness with which they leverage big data in support of their goals. There are those with the resources to analyze, synthesize, and act upon big data and those who are struggling to keep up.

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