Data to Insights to Value
Over the last few years, we have seen unprecedented growth and innovation in data and analytics (D&A) - the amount of data available, the capacity to store it, and the tools to analyze it. Consequently, companies have invested significantly in data / analytics-related infrastructure, technologies, and human capital to reap the benefits. As with all investments, the question from a business perspective is, "Is there an ROI for these investments?"?
The answer is "Yes" - research highlights increases in top / bottom-line results and competitive differentiation for companies that have made investments versus ones that have not. However, challenges continue to prevent companies from gaining the full benefits of these investments. Having been part of multiple transformation journeys across companies, we believe that?
will be the path forward to achieving greater returns from these investments.
Challenges today
Multiple challenges prevent organizations from achieving the full benefits of data and analytics investments.
Data rich, insights poor - with the proliferation of cheap storage, and massive volumes of data, data inventories have exploded. In the past, companies collected data but could not access and utilize it easily. However, there are many barriers to extracting insights from data. First, while massive amounts of data exist, it is often of poor and inconsistent quality. Second, there is a limited understanding of the data needed to address a particular use case, whether it exists within the organization or is available from external sources. In our experience, this is a symptom of weak problem definition and/or immature data management practices. Lastly, there is a lack of appreciation for what it takes to go from data to actionable insights to business results. Data and analytics are part of the journey but not the only component.
Weak linkages between the business and analytics teams occur at multiple levels. Limited connections between the business strategy and the D&A agenda are the most detrimental. This happens when D&A, IT, and other partners are viewed as inputs to and not enablers of the strategy. In this scenario, Business teams set the strategy and share it with the key priorities and initiatives to achieve it, indicating where partners, including D&A, should provide input. Consequently, D&A teams review the list and record how they will contribute, including the associated cost. This lack of collaboration results in a limited understanding of the business needs, disjointed responses from enabling partners, and arbitrarily high-cost estimates - all resulting in a year-end struggle to justify the value of investments in D&A.?
The absence of a cross-functional approach to strategy and prioritization upfront also impacts delivery/outcomes. In one situation, the D&A team had to shelve its work due to a lack of available capacity for the technology needed to update an operational system - that is all too common.?
Ineffective Communication between teams. More often than not, the analytics and algorithm language of the Data/analytics team does not connect with the language of the BU. Business leaders are more interested in business outcomes, viewing analytics as a tool to achieve them. It becomes even more challenging when the discussions focus on the details of the data, analytics, modeling techniques, and AI.
The gap between insights and action. This occurs when there is a lack of data and analytics integration within business processes. While functions like marketing are generally more mature, having robust integration with analytics that produce demonstrable value, analytics integration is commonly less mature or lacking in shared services and operations.?
Investing since competitors are doing it: Over the last few years, a lot of investments have gone into Data & Analytics talent. In many cases, these investments were made as part of an industry investment wave and FOMO on the potential benefits. We have seen multiple companies build analytics organizations, staffing hundreds of analysts and data professionals without having the enabling capabilities established, operating models in place, and proof points with the business established. This “if you build it, they will come” approach to standing up analytics capabilities leaves business leaders feeling like they are paying a tax to get the help they did not ask for.?
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Future Forward
Given the challenges of the current economic environment, we are entering a phase of active trade-offs. In a constrained environment, winning in D&A will require:
Building the D&A agenda from the business strategy and including “last mile” integration investments in operating plans: Involve the D&A team early in the strategic planning process, ensure initiatives get defined, including where and how analytics will contribute - the more detailed, the better. From the D&A team perspective, understand the top business priorities and proactively pick a few areas to deliver demonstrable impact. If the strategy dictates building analytics capabilities in a less mature part of the business, ensure that there are plans for investments to build out last-mile integration. Last-mile integration is the technical plumbing required to deliver insights to the relevant business systems/areas.?
To benefit from analytics investments, the organization should plan for the end-to-end implementation of analytics into the business, including systems integrations, test and learn capabilities, and measurement plans required to realize value. Once the integration is in place, businesses can source analytics from external service providers and lower the cost of managing analytics in some cases. Finally, ensure that measurement plans are defined and agreed upon across all stakeholders. The measurements and incremental improvements should be visible across the organization through scorecards.??
Focus on "incremental" wins and quick payoffs:? D&A teams tend to use sophisticated tools to come to an answer. Err on the side of building simple, understandable solutions, and aim to take the initial analysis far enough to begin testing using the most straightforward analytical tools for the job. The goal is to put the insights into action and start learning.?
Take simple structured approaches to facilitate rapid learning through testing. For example, adjusting call center scripts to optimize call duration and resolution can be done without advanced analytics but requires the systems and tools used by call center staff to support the experimental design, test execution, and data collection. Advanced analytics can be incorporated once the business gains confidence by seeing actual results, i.e., shorter calls, high customer satisfaction, and lower volumes of repeat calls - outcomes that can be measured and translated into hard benefits.
Lastly, the financial contribution from analytics efforts needs to be done objectively and in partnership with a scorekeeper, i.e., Finance. Remember that most of the contributions will be from incremental improvements to revenue or cost-related metrics. Having operational definitions for the metrics is essential, including calculations for valuing the incremental improvements attributed to analytics.
Strengthen the collaboration with Business and IT: We have covered the strategic benefits of aligning with the business, business strategy, and outcomes above. Finally, we will address the communication challenge. A few simple approaches to achieve this are: Jointly define the business problem statement along with cross-functional partners (e.g., tech, operations), including expected outcomes before going into solution mode. Take an iterative approach that includes regular progress check-ins vs. waiting for final results.?
Education and training are other big opportunities to tighten alignment. Continually show the value of the partnership between D&A, Technology, and the business by celebrating the small wins.? Publish post-mortems for successes and failures with the business teams and ensure the D&A community gets trained on “How the business operates and makes money.” Get all the teams pulling in the same direction focusing on the business outcomes, and trust the partner teams, including D&A, to play their roles. The language that unites the team is the business.?
Another equally important element is the partnership between D&A teams and Technology. Technology is integral in managing, maintaining, securing, and operating the organization's technology assets. As mentioned, last-mile integration of insights requires tight alignment with IT to integrate the analytics into the technology and platforms used to operate the business, including external websites, operational systems, vendor solutions, etc. Ideally, this happens early when the organization's data and analytics capabilities are put in place, but it can also be planned for when projects are prioritized. Prioritize jointly to remove any capacity bottlenecks and deliver value to the business. Organizations that incorporate these steps into their planning processes will be able to achieve the benefits of analytics in a scalable, repeatable way.
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D&A will continue to be a competitive differentiator for driving growth and efficiencies. The full value of this lever comes through when the D&A agenda is aligned with strategy / strategic priorities. Continuously demonstrate the value of D&A by delivering business improvements with early pay-offs, and ensure the last-mile integration is done effectively in tight collaboration with technology.??????