Operating a successful business in today’s fast-paced retail environment is far more challenging than it might seem at first sight. Retailers now have more data from more sources than ever before, but that doesn’t necessarily mean that they have a clearer picture of their businesses or their customers than they did twenty years ago. Retailers need to better equip themselves to make the most of omni-channel data and gain the deep insights that they need to give them an edge on their competitors. While this might seem fairly simple in theory, making the most effective use of data requires knowledge, ingenuity, reactiveness, and perseverance. Yet, far too often, data is misused and misunderstood, costing retail organizations millions of dollars every year. The potential rewards for those who invest in the right tools, however, are enormous. According to Forrester, insight-driven companies are on track to earn $1.8 trillion annually by 2021. This article covers the most common myths and misconceptions about analytics.
Myth #1: Our company already has business reporting. We cannot afford to increase our IT budget simply to follow trends in technology.
Reality: Analytics is a value-driver rather than a cost center, and most retailers lack the right tools to turn data into actionable insights.
Forbes found that an astonishing 59 percent of companies are not using any predictive models or advanced analytics. This is especially true for small- to medium-sized companies that often believe they can’t justify the investment when in reality, they’re losing potential revenues and racking up needless costs because of a failure to effectively use the data they collect. No matter the size of a business, advanced analytics have become essential to modern retail success. Retailers should thus consider investing in analytics systems that go far beyond focusing on inventory and sales data and that provide access to enterprise-wide data at the most granular levels and support data aggregation and clustering, regardless of where the data originated, without historical or departmental constraints, and without negative impact on system performance.
Myth #2: The more data, the merrier.
Reality: More data does not equal better data.
Big data seems to be on everyone’s minds these days, which has contributed to the confusion surrounding the amount of data needed to make better business decisions. While collecting massive amounts of data is important, managing and analyzing it in meaningful ways is what can significantly improve a retailer’s business. For example, what makes Amazon so successful is not so much the mountain of data they possess, but how effectively they’re able to act on it.
Prescriptive analytics do what the human mind alone can’t (HBR): it allows retailers to adapt quickly to market trends by processing huge volumes of data, in turn guiding proactive business decisions that will enable sustainable, long-term growth.
Want to learn more? Download our white paper on prescriptive analytics to discover other common analytics myths, and benchmark yourself with our maturity model questionnaire included in the document.
