I've already invested a million $ so far on data science / machine learning. It's been, what, 6 months, 9 months, 12 months - my Data scientist team has been "working" on your intricate and complex enterprise problem - but despite assurances and some encouraging signs - i'm still far away from cracking it.
Things are building up, but it seems the team needs more time. I
may continue to invest another million $ this year.
I sometimes feel, is this the best way forward?
Do I
just keep throwing people and money at the problem?
Maybe it's just time. I understand, even some of the biggest and
best companies in this area took more than 10 years to solve some
of the biggest challenges.
10 years!
Am I prepared to wait (and continue to invest) that long?
Will my market wait for me?
Will my problem remain
the same?
Will my team persist with me during the
whole journey? On-boarding and retaining such incredible talent
sometimes is a headache.
Creating business value out of data is not a simple process. Its
not enough to simply push Data scientists and technologists at the
problem. JetFerry's Answers Journey was designed specifically to
help enterprises get more effective and robust answers - minimizing
the pain of false starts, costly experiments and process
back-fires. We strongly recommend leveraging proven expertise where
available.
Leverage a complete end-2-end tools
based approach rather than an experimental one. Go complete and
comprehensive AIO (all-in-one) - get a complete end-to-end
solution, rather than spending months and months overcoming
integration challenges amongst vendors.
Partner
with experts in providing enterprise answers, rather than
transactional ones.
We did a survey on why companies do not move to proven solutions.
Here are the results.
1. Strategic (31%)
Building
strategic capability in-house for Predictive Analytics was one of
the biggest reasons mentioned in the survey. In these times of lean
organizations and core competence, this seems a little contrarian.
Typically, management/leaders and data scientist views and focus
differ significantly.
2. Control /Trust (27%)
This was
the second most reason cited in the survey at 27%. Either
enterprises did not trust or agree with the vendor approach.
However, there are many ways to ensure your provider is trustworthy
and able to keep data confidential. Also, having a tried-and-tested
methodology such as JetFerry.ai�s 4Cs helps ensure relevance,
weightage and impact of the insights found.
3. Biz Domain Knowledge
In-house
technology and AI teams are generally composed of technology driven
professionals - focused on technology, algorithms, frameworks and
the lastest tech jargon. Their understanding of the business domain
is, generally, specious. They are battling on many fronts at the
same time - AI and business. Both are continuous efforts requiring
sustained investments of time and energy.
AI
solution frameworks have the advantage that they have already
"figured out" one part of the puzzle. They can focus all of their
considerable expertise, knowledge and experience on the biz domain.
In addition, they can leverage their experience of related
offerings to provide higher value solutions.
4. Lack of clarity
Despite the hype
around it, AI and predictive analytics is still a relatively new
area. So, it's quite reasonable that a lot of people do not have
clarity on what to expect. Many still think of it as reports and
graphs coming out of their system. The reality is that AI-driven
Business Intelligence has proven itself as a business enabler. It
finds answers to your business answers just by meticulous analysis
of your data. The 4Cs methodology from JetFerry.ai - will help you
achieve consensus and clarity on the nature and size of the problem
and the contours of an insight that will impact your business in a
meaningful manner.
5. Don't want to experiment / Not ready
No one wants to be the first "guinea pig". They don't want to be
one on whom all the experiments are being done. This is one of the
biggest reasons why going with a proven solution makes more sense.
Your risk is automatically mitigated as they have already crossed
the inexperience bridge. They are best placed to be your partner in
your Answers Journey.
Partner with experts in
providing enterprise answers, rather than transactional ones.
JetFerry.ai's Answers Journey delivers:
>> Have been patient and invested $1mn in tools and team, so far
>> Continue to be patient, but for how long do I need to do this?
>> Would consider a proven solution, if my concerns are addressed.
>> JetFerry.ai's Answers Journey delivers enterprise-class results
continually, not just transactionally.
