Achieving Business Impact with Data

Research Summary: “Achieving Business Impact with Data” By Niko Mohr & Holger Hürtgen, Digital McKinsey (2018)

Insights Value Chain

At Issue: Every day, increasingly more data is available, computing power is constantly growing, and mathematical techniques and so-called data science are becoming more advanced. Organizations face a very significant opportunity, and potentially daunting challenge, to utilize data (their own) to achieve meaningful business impact. Many companies may understand the importance of data, but can easily face persistent difficulties in the realms of technology and business in the process of data integration. A company must strengthen every link in its “insights value chain” in order to effectively utilize data at its full potential.

Research Objective(s): The researchers’ primary objective was to develop and support the hypothesis that a company is “only as good as the weakest link in [its] ‘insights value chain’.” In preparing this report, the researchers sought to 1) outline the scope of data’s growing importance and impact potential; 2) describe the fundamentals of the insights value chain, including both upstream and downstream processes; and 3) introduce key practice perspectives on creating insights-based value and achieving meaningful business impact.

Scope: This study defines and examines the “insights value chain”, which the researchers describe as consisting of both technical and business components. The technical components include data, analytics (algorithms and technical talent), and information technology. The business components consist of people (non-technical talent) and business processes.

Approach: The researchers are subject-matter experts who leveraged their direct experience working with client companies to develop and support their positions on the impact that data can have when businesses utilize it effectively.

Findings: The three primary structural challenges that prevent organizations from achieving maximum business impact with data are:

  1. The separation of data and business: data science and business execution are totally separate in many companies;
  2. The gap between insight and impact: many organizations struggle with the crucial step of implementation – the act of “moving from insight to insight-based value creation”; and
  3. Lack of organizational commitment: organizations often lack top-level executives who are strongly committed to data analytics, and fail to “embed” data analytics deeply into the corporate culture.

Five guiding principles for implementing and scaling data analytics:

  1. Analytics is not a tool, but rather a new language – a new way of approaching business problems;
  2. “Translators” are crucial – more versatile personnel who can help technical and business staff to communicate;
  3. Change management is crucial – to establish trust in data analytics and enable staff to act on data’s findings;
  4. Corporate IT departments must be involved – to implement successful solutions at scale; and
  5. Agility must be maintained – in order for teams to “fail fast” and recover quickly.

Five strategic actions recommended for the medium- to long-term horizon:

  1. Work “business backwards” not “data forward”: first identify business use cases that are relevant for the organization, then develop the data analytics to support them;
  2. Prioritize and focus the team’s efforts: choose the top-three business use cases that are the easiest or fastest to implement, or are likely to have the greatest business impact, and accomplish those first;
  3. Build IT systems with agility: develop data-driven solutions and supporting IT systems in a simultaneous manner;
  4. Hire appropriately trained staff: fully integrate data science and business team personnel to quickly test and prove viable concepts; and
  5. Organize for scale: establish a centralized data analytics unit and create an internal analytics academy to raise the “AQ” of the organization overall.

Notes: The full text of this study can be accessed here.

Keywords: business impact, data analytics, insights value chain

Researcher Profile: Allie Grace Garnett is a professional researcher and freelance writer with a background in finance and entrepreneurship. A serial entrepreneur who has established numerous businesses, Ms. Garnett previously was a founding Principal of Nexos Resource Partners (NRP), an energy project finance firm in New York. Prior to co-founding NRP, Ms. Garnett provided financial advisory and fund raising services to institutional-scale energy funds with Sustainable Development Capital. Ms. Garnett served as the Vice President of Marketing and Strategic Partnerships for the start-up Rentricity, and additionally founded a nonprofit organization (YAVA) that encourages volunteerism among college students. Ms. Garnett holds a Master of Business Administration degree from Harvard Business School and a Bachelor of Science in Civil Engineering degree from Northeastern University.