Thoughts on business intelligence and customer relationship management as customer analytics need process based support for meaningful analysis.
dinsdag 7 juli 2015
The Eternal Business Intelligence Conundrum
an Optimum between a Manageable BI Architecture and Business Agility
This is the
second post in a series of three about programme management in Business
Intelligence (BI). In the previous post we positioned project- and programme
management in BI and the latter’s relationship with BI architecture.
post, we discuss the universal and eternal problem, conflict, dialectics,… (call
it what you want) between the business who wants a decision support solution
here and now, no matter what the consequences for the IT department are and the
IT guys who want to steer the team and the infrastructure into calm waters.
“Calm waters” meaning a strict architectural, TOGAF based approach to managing
the BI assets.
Head for the Cloud!
describe the situations where the IT guys –according to the business- waste
time with the introduction of new tools and the business strike a direct deal
with a vendor, using the tool completely outside the managed environment.
Figure 2 The data mining tool Data Maestro is an example of a powerful cloud based tool
say that many cloud based solutions offer a solution with a small IT footprint:
all the business needs is a browser. Well, that’s what the business thinks.
Issues like data quality, data governance and data security are not always
handled according to corporate standards and legislation on data privacy and
data security is becoming stricter and more repressive every so many years.
What Business Stakeholders
pointed out in the section “Managing Strategy” (Business Analysis for Business
Intelligence p. 66 – 71) business stakeholders need decision support for their
intended strategy as well as emergent strategies (note the plural in the
latter). To support analysis and monitoring of intended strategies (i.e. the
overall business plan or a functional strategy as described in a marketing-,
HR- or finance plan for example) a balanced scorecard (BSC) does the job. If
well done, a BSC aligns all parties concerned around a well-designed causal
model breaking down strategic priorities into critical success factors and key
performance indicators as well as a project plan, a data model and an impact
study on the existing analytics architecture. But to capture, evaluate, monitor
and measure the impact of emergent strategies is a different ball game. The business
intelligence infrastructure needs an agile approach to produce insights on the
fly. Some vendors will suggest that all can be solved with in-memory analytics.
Others suggest the silver bullet is called “Self Service BI” (SSBI) Yet even
the most powerful hard- and software is a blunt and ineffective weapon if the
data architecture and the data quality are in shambles.
new tools emerge, producing solutions for niches in finance, marketing or
production management which cause the business to urge IT for adopting these
tools. This ends with either a mega vendor acquiring the niche player or the
niche player broadening its offerings and competing head on with the
established vendors. In any case, if the IT department happens to have
standardised on the “wrong” technology partner, there will be bridges to cross
Other than issues
with new software “interfering” with IT’s priorities, most of the troubles are
found in the data architecture. The reason is simple: if not all BI projects
are backed by an enterprise wide data architecture that is connected with BI
programme management, new information stovepipes will emerge. This is quite
ironic as the initial reason for data warehousing was to avoid the analytic
stovepipes on transaction systems. So here’s my advice to the business:
Whatever business you are in,
make sure you have an enterprise view on the major information objects for your
you are destined to waste money on rework, on incomplete and even false information.
What IT Stakeholders Need
management has many constraints do deal with. Keeping up with business
requirements, while getting the biggest bang for their buck means pooling skills,
facilities and technology components to optimise license cost, education and
training and hard- and software performance. The final objective is to provide
high service levels and keeping their customers happy at a reasonable budget.
But if ”happy customer” means: acquiring new, exotic software, training new
skills and insourcing expensive tech consultants from the vendor to explore new
terrain without experience or knowledge of best practices, then IT management
may be at the short end of the stick.
example of data visualisation ten years back. Business had a point that the
existing vendors weren’t paying too much attention to good visualisation to
produce better insights in data. Even the most common tools had problems creating
a histogram, let alone sophisticated heat maps or network diagrams. Then came
along vendors like Tableau Software selling end user desktop licenses at affordable
rates, educating the business to enjoy the benefits of visual exploration of
data. The next step in this “camel’s nose” or “puppy dog approach” is getting
the organisation to acquire the server for better management, performance and
enterprise wide benefits of the technology.
my advice for IT Management:
If a new technology becomes
available, it will be used. Make sure it is used in a managed and governed way instead
of contributing to information chaos.
business intelligence trends that have a pertinent business case, fight BI
A Governance Decision
Model for Conflicting Interests
I don’t like
dogmatic thinking in management but when it comes to governance in BI, I will
defend this dogma till the bitter end: only duopolistic governance will produce
the best results in analytics.
business monopoly won’t work was clear after a consulting mission where I found
a data warehouse with no less than six (6!) time dimensions. This extreme
situation can only be explained by what I call “the waiter business analysis
model”. Without any discussion, counterarguments nor suggestions, the
analyst-waiter brings the ordered tables, cubes and reports to please the
business. If the business funds the projects solely, then accidents will
Figure 3 The BI Waiter Model: don't argue with the customer, bring him what he wants, no matter what...
monopolies also are a recipe for failure in BI. At another client’s site, the
IT department repeats over and over “x unless…” (x is a well-known BI tool
provider). As it happens, this tool provider is lagging seriously in data mining
and visualisation functionality so the business is wasting money on external
service providers who do the analytics off line. Another source of waste are business managers
installing software on their private PC to explore new ways of analytics at
duopolistic governance model, decision makers from both sides have to consider
five key governance decisions. This will result in a better mutual
understanding of each other’s concerns and priorities as well as provide a
roadmap towards a managed analytical environment.
The Five Key BI Governance
book Business Analysis for Business Intelligence, page 300 -301)
a.In what measure do we value data quality in the
b.If we have a trade off between security issues
and potential gains from better distribution of information, which direction do
c.Do we choose a proactive or a reactive attitude
towards our BI users, i.e. do we deliver only the required information or do we
make suggestions for enhancements?
a.Do we follow the general architecture policies
or is there a compelling reason to choose an alternative route?
b.If we need alternatives, where will they be of
importance: in databases, ETL tools, BI server(s), client software,…?
a.What are the shared IT services the data
warehouse will use?
b.What part of the infrastructure will be
organised per department or business unit?
c. What are the access methods for the information
consumers: local client PC, PDA, web based, VPN,…?
a.Specify the business need
b.Specify the urgency
c.Present alternative solutions
of investments in BI
a.How will we evaluate the priorities?
b.Who will handle conflicting interests?
c.Which user profiles will be served first?
d.Which subject areas will be tackled first?
Figure 4 More on BI Governance in this book, available in all major bookstores
In the next
post I will have a look into the next generation of information design and architecture.
Comments are welcome!