An increasing number of businesses are turning to data and analytics to enable information-based decision making. Yet, ironically, many of these same companies struggle to quantify the impact of their own data and analytics programs.
Recent reporting indicates that only 15% of data and analytics strategies specify concrete metrics of success. The other 85% make no mention of metrics or even intangible goals.1 Worryingly, if those statistics hold true, then businesses are choosing whether or not to invest in data and analytics based on gut feel, rather than on hard data.
This lack of benefits tracking can have significant impacts – if data and analytics is viewed as nebulous it is far more likely to be side-lined, ignored, or dismantled altogether. In order for a business to justify building and maintaining a centralised data and analytics team, thought has to be put into how the value of that team is tracked.
There two main challenges around achieving this:
- IT professionals find it hard to connect analytics to business outcomes
- It is often hard to take the time to complete baseline measurements during the rough and tumble of everyday operations
Ultimately, everything comes down to providing clear links between the data and analytics strategy and associated initiatives that support corporate objectives. However, for data and analytics leaders trying to quantify the benefits of their team, there are three areas of value that should be articulated.
1. The productivity of the data & analytics team
Optimising your data and analytics processes of the data and analytics team itself is a key place to demonstrate value. One way to approach this is by structuring and measuring your work around the principles of economic minimum, and economic maximum.
For example, tracking the number of projects delivered on schedule, the cost per dashboard, or the percentage of data quality improvements over a given time period, allows you to demonstrate your team’s ability to achieve a pre-determined result using as little resource as possible (i.e., the economic minimum).
Conversely, measuring areas such as the satisfaction score of internal customers or the number of dashboards created per workday showcase your data and analytics team’s productivity (i.e., economic maximum).
2. The impact of data & analytics on the business
While there are various use cases, the most common place to demonstrate business value is through descriptive and diagnostic analytics. Optimising internal processes can help management teams to improve the running of day-to-day functions in a way that is seen and felt across the organisation.
When reporting on these changes it’s important to consider what level of detail you are supplying. Board members, directors and managers will all require different levels of granularity to gain insight into how data and analytics is impacting their area of focus.
For example, at a board member or director level it may be best to provide descriptive analytics – e.g., what percentage of deliveries arrives on schedule last month. Whereas at the manager level, it’s far more likely that they will need diagnostic analytics that provide granular insights – e.g., of the 15% of deliveries that arrived late, what was happening at each stage of the delivery process? How can this be improved?
For each data and analytics function, it is essential to identify which key performance indicators (KPIs) should be tracked against baseline measurements. Whenever possible, changes in KPIs should then be linked to corporate objectives and direct impacts on shareholder value – e.g., profit increases, working capital improvements, or risk mitigation.
3. The role of data & analytics in shaping an open and collaborative culture
There is an increasing expectation for information to be shared across networks to both internal and external stakeholders. This can mean customers, suppliers, partners, investors, employees and more.
Data and analytics plays an essential role facilitating the availability and enabling a collaborative approach which all stakeholders into account and to promotes a transparent and inclusive business culture.
A key benefit of this approach is closer and longer-term stakeholder relationships built on trust. This can be seen in reductions of customer churn, along with fewer, and lower cost, customer complaints. It can also reduce friction in the supply chain by helping stakeholders to be open about that they expect, want, and can commit to.
While these benefits are undeniably harder to quantify, they are an essential aspect of what data and analytics brings to modern businesses and it is important to draw attention to this value wherever possible.
This article is part of our Data-Driven SMB series. For more information, advice and resources on how to accelerate your organisation’s data and analytics maturity, click here or contact us today.
Bill is a Business Development Director at TrueCue and is responsible for helping existing and future clients gain value from their data and analytics investments.
With over 20 years of experience in Management Consulting (AT Kearney), Industry (BOC Gases; Eli Lilly) and Private Equity (LDC; Easynet) Bill has worked in, and successfully led, teams across several operational functions including marketing, sales, delivery, project management, client success, and support.