How do you develop domain knowledge in your analysts, so their data use, interpretation, and recommendations make sense? I’ve mentioned in a previous article, about the difficulties of offshoring analytics, how vital domain knowledge can be. Yet, I find most articles or speakers focus on the need to develop new technology skills such as mastering the latest en vogue coding language.
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Akin to the greater importance of softer skills for analysts, my own experience is that domain knowledge makes a greater difference to analyst effectiveness. So, as my contribution to redressing that imbalance, here are some thoughts on domain knowledge, why it matters and how best to help your analysts learn about their domain.
Let’s start with a definition. The Dictionary of Computing usefully defines domain knowledge as:
“That knowledge which is specific to an application, as distinguished from general strategic or control knowledge that is independent of the details of any particular application. For example, data about the flight routes covered by a particular airline is domain knowledge, unlike search algorithms that might be used to locate the cheapest entry.”
Relevant to customer insight, data science, or analytics teams, I would emphasize that this is knowledge about the real-world context or business problem. It’s not just general awareness of principles (from business studies), or the technical knowledge of data, methods, and technologies; it’s an understanding of what this means.
For example, an analyst might be fully familiar with data warehousing and the coding skills required, but when asked to analyze customer behavior when they are using a new channel (like mobile), the analyst may not have the knowledge required. Although he may be able to complete thorough descriptive analytics or other statistical work, without an understanding of customer context and what the business is trying to achieve, he is unlikely to produce useful recommendations.
All too often I have seen apparently robust analysis be totally ignored in wider business because it appears “naive” or “impractical.” A lack of understanding of business strategy, including the goals for products or channels, current commercial performance and issues, and customer needs, as well as a “feeling” for the customer experience, can all lead to inaccurate interpretation of data items or irrelevant recommendations.
I’m sure other customer insight or analytics leaders will concur; such knowledge is key to both understanding the real business problem or need and making sensible recommendations as a result of analysis.
So, if such context is critical, how can analysts gain the knowledge needed? Here are three ways that have proven effective.
Knowing your numbers: A key element of commercial understanding
Many an analyst or analytics manager has been “encouraged,” usually in annual performance reviews, to become more “commercially aware.” One of the problems with such feedback is the vagueness of that phrase. What does an analyst need to know to be commercially aware? From my own experience, I’d suggest there are three key dimensions of commercial knowledge:
1. Strategy: Understanding the business strategy and why current participation (in products/channels/brands/segments) makes sense
2. Competitive market: Understanding who the key competitors are, the threats they pose, and keeping up to date with relative performance and innovations
3. Financial performance: Understanding the key profit drivers amidst commercial numbers, how to read financial reports, and keeping up to date on key performance indicators (KPIs)
Of those three, I find most businesses make an effort to share items one and three but only at a high level (i.e., suitable for staff at all levels). Analysts and analytical teams need a deeper understanding of strategy, assumptions, and rationales for key decisions. Those insight or analytics teams working within marketing will also probably see regular information on competitors and performance against the broader market. This is especially true if they have brought the research team into the same department as analytics teams (and ideally the market and competitor intelligence teams as well).
Working with a variety of clients, I seldom see a focus on really explaining the financial drivers of business to analytics teams. Surprisingly, given analysts’ high numeracy skills, businesses tend to keep that education and information within their finance or strategy teams. This is well worth addressing. Investing in commercial training, sometimes in-house from strategy and finance leaders, can pay huge dividends in the quality of future analysis. If you need to do this on a shoestring, then I’d also recommend Naked Finance (Nicholas Brealey, 2011) by David Meckin as a great book on this topic.
In line with the benefits of collaborating with finance and strategy teams, it can also be worth asking your sales leaders to help. Any effective sales manager is used to keeping her team up to date with the latest sales performance or expecting account managers to know their numbers. A similar requirement, to understand headline financials and be able to quote the latest KPIs that matter (often sales performance), is a great expectation for analytics leaders. I have found it helpful to expect insight business partners or those managers with responsibility for a particular business product, channel, or function, to know their numbers and be able to talk meaningfully with their commercial contacts at any time.
Doing the rounds: Using team meetings to achieve more
When asked about the aspect of their job that they like least, many an analyst (or leader) will cite excessive emails or meetings. Keeping the latter interesting is a challenge for any manager or leader. When meetings work well, they can be an effective way of keeping a whole team up to date on key knowledge they need, and together spotting opportunities for collaboration, challenges, or developing new ideas.
But, in line with the entrenched functional fiefdoms of corporate life, too many team meetings are too insular. They may go an entire year or more without anyone from outside that team or function attending. This is a missed opportunity because encouraging leaders to “do the rounds” (by visiting other team meetings) can be an opportunity for a win-win result.
Relevant to increasing domain knowledge, a simple solution is ensuring that your analysts have the opportunity to hear first-hand from leaders or experts in other business functions. The quickest way to understand sales performance, marketing strategy, customer irritants at service touchpoints, or the potential of IT systems is to hear directly from the function with ownership for that aspect of your business. The goal here is to create a mutual safe space sharing environment, where other functions leaders, or experts feel valued, and your analysts feel unembarrassed to ask basic questions about anything they don’t really understand.
I mentioned a win-win outcome. The other benefit that can come from this approach is to give your team a break from you. I say that because I recommend reciprocal visits. This can help demonstrate how to value other business functions as well as create an opportunity to talk directly to their direct reports about analytics and any key insight you need to champion. It can also aid your team’s development to be exposed to a variety of leaders, or for one of your team to be responsible for running team meetings in your absence.
But with all three of these initiatives, there is also a responsibility for the analysts to engage and learn. Solutions should not be spoon fed too much because everyone is primarily responsible for his own self-development. That emphasis comes to the fore in my last suggestion.
Getting out and about: Domain knowledge and real customers
The final means of encouraging analysts to gain domain knowledge is to expect them to meet customers on a regular basis. Something I’ve seen work effectively is to expect every member of your analytics team to hear from or meet customers at least once a quarter (and include that as a metric in their performance assessment).
Human contact is always a more emotional and immersive experience than reading research reports or knowing the results of behavioral analysis. For that reason, although listening to calls from a call center, or viewing focus groups in a research studio, can help, the best solution is meeting customers in their natural environment.
A few insight teams may have the advantage of occasional ethnographic research. If so, I encourage analysts to get involved if possible. But for most sectors, a more realistic goal is for analysts to visit the key distribution channels and observe or talk with customers. For your business, that may include stores or branches, call centers, advisors or intermediaries (sometimes visiting customer homes), mobile units, or partners that supply services.
At a minimum for sales and service experience, analysts should try using any mobile and web applications themselves. But if it is possible for analysts to engage with typical customers in the normal environment for buying or using your products or services, that can create an opportunity for emotional insights. In a previous series, focused on insight generation for proposition development, I mentioned how this type of knowledge can be useful to converge with internal analytics or research studies.
Beyond learning further domain knowledge, often about the real-world context of data items or customer behavior patterns observed within those data, such visits can also increase motivation. To truly empower your team includes creating opportunities for them to discover their own “why.” Why do they choose to keep working for your business? Why do they do the work they do? Seeing the difference their work can make to customers’ lives is often a key to unlocking such personal motivation, too.
How do you develop domain knowledge in your teams?
I hope the above content has convinced, or reminded you, of the importance of domain knowledge. How do you currently ensure your analysts or researchers gain this knowledge?
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