ALIGNING YOUR BI OPERATIONS WITH YOUR CUSTOMERS' UNSPOKEN NEEDS -Learn how to connect BI and product management to solve business problems -Discover how to lead clients to ask the right questions to get the data and insight they really want -Get pointers on saving your time and your company's resources by understanding what your customers need, not what they ask for

1. Aligning Your BI Operations With
Your Customers’ Unspoken
Needs
BY
Eyal Steiner, Senior BI Engineer @ Alexa Shopping, Amazon

2. About Me
• Teaching Assistant @ Ben Gurion University (Financial Accounting 101
and Advanced Financial Accounting – yes, no one is perfect)
• CEO and co-founder of DNA-7 (startup in the organizational network
analysis field)
• Business Analyst @ SimilarWeb (focus on Product Analysis)
• Data Scientist @ SimilarWeb (professional services)
• Senior BI Engineer @ Alexa Shopping, Amazon (voice search)

3. About Alexa Shopping
• Alexa Voice Shopping is a service from
Amazon that allows you to place orders
through voice commands
• All you have to do is tell Alexa what you
want to buy, and Alexa’s search engine will
find you the most suitable product
• But this is not a PR talk for Alexa Shopping;
if you want to learn more, seek me after
the presentation, or visit amazon.jobs to
find out more about job openings

4. What’s in store today?
• Managing a backlog in an ever-changing business environment
• Engaging with your customers to improve BI outputs
• Going the extra mile to deliver outputs that your customers didn’t
even know they could ask for

5. Backlog Management

6. What is Backlog Management?
• Backlog management is the process by which the product owner
(often in collaboration with others) adds, adjusts, grooms,
and prioritizes backlog items within the backlog to make sure the
most valuable product is shipped to customers1
• The backlog has a tendency to grow exponentially when the BI team
is delivering quality outputs
1. Definition taken from: https://www.perforce.com/blog/hns/backlog-management-6-tips-make-your-backlog-lean

7. The Upper Management Conundrum
• There’s nothing unique about BI backlog, except that…
• Management often requests more information, drill-downs, and
clarifications on your outputs
• It is always urgent
• While you should always “plan” for these requests, it is also a good
practice to present the cost of these requests to your managers
• In some situations, it may also be beneficial to remove an item from
the backlog when unplanned requests come in

8. Cost Discussions
• Think about two kinds of costs when discussing
this with your managers:
• Immediate cost – how many BI hours this task will
take (or already took)
• Alternative cost – what is the cost of pushing down
backlog tasks in favor of these requests - the cost
should be quantified in money and/or productivity
• If you can’t explain the alternative cost - check
again if the task in the backlog is actually
necessary and whether you understand why
it’s there

9. Cost Discussions Pt. 2
Add 5 new metrics to WBR
Cost: 2 days of work
Savings: provide better visibility for
management on critical business KPIs
Dashboard for Sales Managers
Cost: 2 days of work
Savings: improve SM’s visibility into
pipeline issues, helps prioritizing
customer interactions
Actual cost of reprioritization = cost of new task – savings from new task + time delta of cost/savings of Backlog tasks

10. Ask the Hard Questions
• It’s also important to ask management the hard questions, but we’ll
get to that in the next chapter

11. Engaging With Your Customers

12. Constantly Talk With Your Stakeholders
• If your team has a product manager – great!
• If not (and even if you do have one), it is your responsibility to
constantly inquire and understand what data and tools are missing
from their stack and how their existence can be beneficial

13. Have a “Can-Do” Attitude, but Don’t
Automatically say Yes
• Okay, this is a little new-agey, but it’s an important point to make
• Don’t decide for your customers what is important and what is not
important
• Treat them like adults - be transparent about the effort and cost
associated with their requests, and let them help you prioritize the
tasks

14. Don’t be Shy, Ask and Then Ask More
• It makes you a significantly better BI professional when you
understand the business problems your stakeholders are trying to
solve - raising you from executioner to partner
• Questions you should always ask:
• What actions will you take from the data?
• In a perfect world, what would you like to know that you don’t know now?
• What data is missing that could potentially make your life easier?
• Where is the best place for you to consume the data?

15. Meet the Customer Halfway
• If you want your tools to be adopted, they have
to be integrated with your customers’ “jobs to
be done”
• BI tools like Tableau are great, but don’t force
your customers to use them; they are a means
to an end, not an end in themselves
• Best example is for Sales – it makes no sense
for them to consume data outside of the CRM;
it is time consuming and confusing; you’ll end
up creating amazing tools no one uses

16. Splitting Resources Between Ad-Hoc Analysis,
Customer Tools, and Long Term Improvements
• There is always a tension between the three and there is no definitive
answer as to how exactly you should split your efforts
• In general, the following guidelines have been working pretty well for me:
• Ad hoc – a complex business problem that a non-data person can’t produce; if the
business problem is not complex but important, ask yourself whether other people
are trying to solve that problem as well
• Tools – don’t build tools that try to solve complex business problems - those usually
don’t work; however, always build tools for for repetitive/deterministic tasks (not
only for you…)
• Long Term Improvements, such as new data sources and tech debt, should be given a
constant workload because they will only rarely be prioritized by customers, and
when they do, it’s too late

17. A Little More on Self-Service
• Self service is a noble idea, but often fails (both
from the client side and from the data side)
• Usually both sides are interested in self-serve: the
BI because it reduces the amount of repeating
requests and the customer because they don’t
have to wait for you the deliver on the request
• That being said, don’t expect other people (even
if they are data engineers or business managers)
to understand the limitations of the data as well
as you do

18. Own and Lead the Conversation
• You should be the expert in everything and anything data – you are
expected to have a strong opinion about data requests
• What may seem like a very simple request may in fact be very
complicated and expensive – only you know that
• If you think the request does not answer the business problem it is
trying to solve or is too expensive, challenge the request and offer an
alternative

19. Unspoken Needs

20. Most Challenging Aspect of Any Product
• There is no easy solution to this because it requires a very deep
understanding of the business problem and the entire business
universe
• You want to try and do this without reinventing the wheel, as the cost
will become very high
• Use your BI network and other international resources available to
understand how other companies are solving that business problem
(or a similar one)

21. Prerequisites
• Understanding the data and being a technical expert is a necessary,
albeit an insufficient condition
• You must understand the business problem your customers have at
least as well as they do, preferably even better
• You may want to try and forecast business problems before they are
actually expressed by your customers (is there a plan to change the
structure of the sales org?)

22. Don’t Invest too much in the Unknown
• Other people have likely tried to solve that problem
before – try to find them, interview them, and learn
from their experience on what worked and what
didn’t
• Execute small tasks at a time and test their results –
A/B testing is taken for granted in any development
environment, make sure you’re not exempt from it
• Execute with frugality in mind – if the solution turns
out to be successful, plan on a scalable solution;
scale is not important if you don’t have customers

23. How Does it All Come Together?
• Prioritizing these kind of tasks is hard – your backlog includes dozens
of other super important tasks; be certain the task is more valuable
• Own the conversation and explain to your customers why this
investment is important
• “Be right, a lot” - the more often you are right, the easier it is for
your customers to trust your judgment and execution

24. Thank you for listening!
Any questions?