Day to day operational decisions managed by retail executives have not changed over the years. They continue to ask and answer the same questions on a regular basis.
- What brands should we invest in?
- Which vendors should we partner with?
- What products should we buy or develop?
- How much should we buy?
- How should we allocate the merchandise?
What has changed, however, is the way in which these decisions are approached. Fact-based, informed, timely decision making is a requirement when considering today’s heightened competition and demanding customers. Retailers need to find new ways to manage “big data” and use it to drive results – not just by answering these questions, but by using it to achieve strategic business objectives.
For example, determining order quantities has traditionally been done using rough estimations for sales based on recent performance of the same or similar items. Today, retailers can build statistical forecasts based on product attributes, seasonality, and the designated store location or channel through which the product will be sold. To make these decisions, retailers need timely, high quality, integrated data. Without it, achieving basic retail business objectives such as optimizing local product assortments, improving marketing effectiveness, and delivering a seamless brand experience to ultimately drive sales and profits, will be nearly impossible. And more importantly, failure to leverage data for these critical decisions will put retailers at a competitive disadvantage.
Why is This So Hard?
Unfortunately, existing retail processes and systems actually create poor quality data. Product Development, Merchandising, Marketing, eCom, and the other functional groups all have their own systems and processes and often work in silos. As a result, data is usually duplicated, stored in multiple formats, in multiple locations, and at varying levels of quality. Worst of all, the use of inconsistent data definitions can lead to groups working from “multiple versions of the truth” which makes it very difficult to drive companywide alignment around the achievement of common goals.
Industry trends are making data management even more challenging, and the already tough situation is getting worse. Data volumes are expected to continue to grow at an increasing velocity, while managing data variety – structured, unstructured, and semi-structured – requires building new capabilities. On top of that, most retailers have minimal data governance processes and operate legacy systems which require manual data input and integration. This further erodes the data quality.
A Holistic Approach to Information Management
Successfully addressing these challenges requires a holistic Information Management (IM) approach. IM is based on the principle of managing data as a strategic asset rather than an operational necessity. It starts with understanding what decisions need to be made to support the strategic objectives of the company, and then determining what metrics are needed to support those decisions and measure results. As an example, if driving increased loyalty is a business objective, then measuring repeat purchase rates, conversion, and customer profitability are the required metrics.
Once the metrics have been identified and defined, determining what data is needed and where it resides is the next step. This is when retailers run into roadblocks that have been created by discrete systems and processes; the data required to move forward is incomplete, poor quality, at varying levels of detail, or just not usable. Disciplined Information Management calls for root cause analysis, combined with remediation efforts, to address the organizational, process, or technology issues. Solutions to close the gap are then designed and prioritized on a roadmap for implementation. Ultimately, this helps drive standardization and consolidation, and to improve the overall quality of the data, effectively turning it into real information that can be used to drive value. Governance also plays an important role in IM. Retail executives must ensure that all key stakeholders are aligned around the key metrics and how they are defined, and they must clarify who owns and edits the data.
The Benefits of Information Management
Truly effective IM requires an investment, but the potential benefits are hard to ignore. Retailers that enable fact-based decision making by providing visibility to supporting information will streamline operations and increase efficiency and productivity. Quantitative benefits include top line revenue growth, improved inventory turnover rates, and reduction in time to market. Qualitative benefits include improved customer experience and brand perception. Data transparency drives cross functional alignment and collaboration. Associates will spend less time on low value added tasks, like data entry or manual reconciliation of reports, and more time on strategic work that adds value for the business. With a holistic investment in IM, both internal resources and external customers will benefit.
Retailers must fundamentally change the way they manage data today. While poor decision making has always impacted profits, today’s customers have more options and more information at their fingertips. Picking the wrong product or running short on inventory has a much greater impact on sales and margin, and even on the brand. Disappointed customers don’t have the time or patience for second chances. Data is no longer just an operational necessity used to support day to day business processes. It is a valuable asset that should be leveraged to drive sales growth and optimize profitability.